diff --git a/apps/openchallenges/challenge-service/.openapi-generator/FILES b/apps/openchallenges/challenge-service/.openapi-generator/FILES index 9e9bd572cf..294ac337e9 100644 --- a/apps/openchallenges/challenge-service/.openapi-generator/FILES +++ b/apps/openchallenges/challenge-service/.openapi-generator/FILES @@ -24,7 +24,6 @@ src/main/java/org/sagebionetworks/openchallenges/challenge/service/model/dto/Cha src/main/java/org/sagebionetworks/openchallenges/challenge/service/model/dto/ChallengeContributionDto.java src/main/java/org/sagebionetworks/openchallenges/challenge/service/model/dto/ChallengeContributionRoleDto.java src/main/java/org/sagebionetworks/openchallenges/challenge/service/model/dto/ChallengeContributionsPageDto.java -src/main/java/org/sagebionetworks/openchallenges/challenge/service/model/dto/ChallengeDifficultyDto.java src/main/java/org/sagebionetworks/openchallenges/challenge/service/model/dto/ChallengeDirectionDto.java src/main/java/org/sagebionetworks/openchallenges/challenge/service/model/dto/ChallengeDto.java src/main/java/org/sagebionetworks/openchallenges/challenge/service/model/dto/ChallengeIncentiveDto.java diff --git a/apps/openchallenges/challenge-service/requests.http b/apps/openchallenges/challenge-service/requests.http index c991f9d00d..34c7099731 100644 --- a/apps/openchallenges/challenge-service/requests.http +++ b/apps/openchallenges/challenge-service/requests.http @@ -24,10 +24,6 @@ GET {{basePath}}/challenges?status=active,upcoming GET {{basePath}}/challenges?platforms=synapse -### List the challenges with intermediate difficulty. - -GET {{basePath}}/challenges?difficulties=intermediate - ### List the challenges with a container image submissions. GET {{basePath}}/challenges?submissionTypes=container_image diff --git a/apps/openchallenges/challenge-service/src/main/java/org/sagebionetworks/openchallenges/challenge/service/api/ChallengeApiDelegate.java b/apps/openchallenges/challenge-service/src/main/java/org/sagebionetworks/openchallenges/challenge/service/api/ChallengeApiDelegate.java index 85b9740d87..245266e24b 100644 --- a/apps/openchallenges/challenge-service/src/main/java/org/sagebionetworks/openchallenges/challenge/service/api/ChallengeApiDelegate.java +++ b/apps/openchallenges/challenge-service/src/main/java/org/sagebionetworks/openchallenges/challenge/service/api/ChallengeApiDelegate.java @@ -36,7 +36,7 @@ default ResponseEntity getChallenge(Long challengeId) { for (MediaType mediaType : MediaType.parseMediaTypes(request.getHeader("Accept"))) { if (mediaType.isCompatibleWith(MediaType.valueOf("application/json"))) { String exampleString = - "{ \"avatarUrl\" : \"http://example.com/aeiou\", \"endDate\" : \"2017-07-21T00:00:00.000+00:00\", \"description\" : \"This is an example description of the challenge.\", \"platform\" : { \"name\" : \"name\", \"id\" : 1, \"slug\" : \"example-challenge-platform\" }, \"starredCount\" : 0, \"difficulty\" : \"intermediate\", \"createdAt\" : \"2022-07-04T22:19:11Z\", \"incentives\" : [ \"publication\", \"publication\" ], \"submissionTypes\" : [ \"container_image\", \"container_image\" ], \"websiteUrl\" : \"http://example.com/aeiou\", \"name\" : \"name\", \"id\" : 1, \"headline\" : \"Example challenge headline\", \"slug\" : \"awesome-challenge\", \"startDate\" : \"2017-07-21T00:00:00.000+00:00\", \"doi\" : \"doi\", \"status\" : \"active\", \"inputDataTypes\" : [ { \"name\" : \"gene expression\", \"id\" : 1, \"slug\" : \"gene-expression\" }, { \"name\" : \"gene expression\", \"id\" : 1, \"slug\" : \"gene-expression\" } ], \"updatedAt\" : \"2022-07-04T22:19:11Z\" }"; + "{ \"avatarUrl\" : \"https://openchallenges.io\", \"endDate\" : \"2017-07-21T00:00:00.000+00:00\", \"description\" : \"This is an example description of the challenge.\", \"platform\" : { \"name\" : \"name\", \"id\" : 1, \"slug\" : \"example-challenge-platform\" }, \"starredCount\" : 100, \"createdAt\" : \"2022-07-04T22:19:11Z\", \"incentives\" : [ \"publication\", \"publication\" ], \"submissionTypes\" : [ \"container_image\", \"container_image\" ], \"websiteUrl\" : \"https://openchallenges.io\", \"name\" : \"name\", \"id\" : 1, \"headline\" : \"Example challenge headline\", \"slug\" : \"awesome-challenge\", \"startDate\" : \"2017-07-21T00:00:00.000+00:00\", \"doi\" : \"https://doi.org/123/abc\", \"status\" : \"active\", \"inputDataTypes\" : [ { \"name\" : \"gene expression\", \"id\" : 1, \"slug\" : \"gene-expression\" }, { \"name\" : \"gene expression\", \"id\" : 1, \"slug\" : \"gene-expression\" } ], \"updatedAt\" : \"2022-07-04T22:19:11Z\" }"; ApiUtil.setExampleResponse(request, "application/json", exampleString); break; } diff --git a/apps/openchallenges/challenge-service/src/main/java/org/sagebionetworks/openchallenges/challenge/service/configuration/EnumConverterConfiguration.java b/apps/openchallenges/challenge-service/src/main/java/org/sagebionetworks/openchallenges/challenge/service/configuration/EnumConverterConfiguration.java index 4651e66d8c..b343c05368 100644 --- a/apps/openchallenges/challenge-service/src/main/java/org/sagebionetworks/openchallenges/challenge/service/configuration/EnumConverterConfiguration.java +++ b/apps/openchallenges/challenge-service/src/main/java/org/sagebionetworks/openchallenges/challenge/service/configuration/EnumConverterConfiguration.java @@ -2,7 +2,6 @@ import org.sagebionetworks.openchallenges.challenge.service.model.dto.ChallengeCategoryDto; import org.sagebionetworks.openchallenges.challenge.service.model.dto.ChallengeContributionRoleDto; -import org.sagebionetworks.openchallenges.challenge.service.model.dto.ChallengeDifficultyDto; import org.sagebionetworks.openchallenges.challenge.service.model.dto.ChallengeDirectionDto; import org.sagebionetworks.openchallenges.challenge.service.model.dto.ChallengeIncentiveDto; import org.sagebionetworks.openchallenges.challenge.service.model.dto.ChallengeInputDataTypeDirectionDto; @@ -39,16 +38,6 @@ public ChallengeContributionRoleDto convert(String source) { }; } - @Bean - Converter challengeDifficultyConverter() { - return new Converter() { - @Override - public ChallengeDifficultyDto convert(String source) { - return ChallengeDifficultyDto.fromValue(source); - } - }; - } - @Bean Converter challengeDirectionConverter() { return new Converter() { diff --git a/apps/openchallenges/challenge-service/src/main/java/org/sagebionetworks/openchallenges/challenge/service/model/dto/ChallengeDifficultyDto.java b/apps/openchallenges/challenge-service/src/main/java/org/sagebionetworks/openchallenges/challenge/service/model/dto/ChallengeDifficultyDto.java deleted file mode 100644 index 75ced8e623..0000000000 --- a/apps/openchallenges/challenge-service/src/main/java/org/sagebionetworks/openchallenges/challenge/service/model/dto/ChallengeDifficultyDto.java +++ /dev/null @@ -1,43 +0,0 @@ -package org.sagebionetworks.openchallenges.challenge.service.model.dto; - -import com.fasterxml.jackson.annotation.JsonCreator; -import com.fasterxml.jackson.annotation.JsonValue; -import java.util.*; -import javax.annotation.Generated; -import javax.validation.constraints.*; - -/** The difficulty level of a challenge. */ -@Generated(value = "org.openapitools.codegen.languages.SpringCodegen") -public enum ChallengeDifficultyDto { - GOOD_FOR_BEGINNERS("good_for_beginners"), - - INTERMEDIATE("intermediate"), - - ADVANCED("advanced"); - - private String value; - - ChallengeDifficultyDto(String value) { - this.value = value; - } - - @JsonValue - public String getValue() { - return value; - } - - @Override - public String toString() { - return String.valueOf(value); - } - - @JsonCreator - public static ChallengeDifficultyDto fromValue(String value) { - for (ChallengeDifficultyDto b : ChallengeDifficultyDto.values()) { - if (b.value.equals(value)) { - return b; - } - } - throw new IllegalArgumentException("Unexpected value '" + value + "'"); - } -} diff --git a/apps/openchallenges/challenge-service/src/main/java/org/sagebionetworks/openchallenges/challenge/service/model/dto/ChallengeDto.java b/apps/openchallenges/challenge-service/src/main/java/org/sagebionetworks/openchallenges/challenge/service/model/dto/ChallengeDto.java index ee69d770ee..6fbd9be280 100644 --- a/apps/openchallenges/challenge-service/src/main/java/org/sagebionetworks/openchallenges/challenge/service/model/dto/ChallengeDto.java +++ b/apps/openchallenges/challenge-service/src/main/java/org/sagebionetworks/openchallenges/challenge/service/model/dto/ChallengeDto.java @@ -31,28 +31,25 @@ public class ChallengeDto { private String name; @JsonProperty("headline") - private String headline; + private String headline = null; @JsonProperty("description") private String description; @JsonProperty("doi") - private String doi; + private String doi = null; @JsonProperty("status") private ChallengeStatusDto status; - @JsonProperty("difficulty") - private ChallengeDifficultyDto difficulty; - @JsonProperty("platform") private SimpleChallengePlatformDto platform = null; @JsonProperty("websiteUrl") - private String websiteUrl; + private String websiteUrl = null; @JsonProperty("avatarUrl") - private String avatarUrl; + private String avatarUrl = null; @JsonProperty("incentives") @Valid @@ -115,7 +112,7 @@ public ChallengeDto slug(String slug) { } /** - * The slug of the challenge. + * The unique slug of the challenge. * * @return slug */ @@ -125,7 +122,7 @@ public ChallengeDto slug(String slug) { @Schema( name = "slug", example = "awesome-challenge", - description = "The slug of the challenge.", + description = "The unique slug of the challenge.", required = true) public String getSlug() { return slug; @@ -211,11 +208,16 @@ public ChallengeDto doi(String doi) { } /** - * Get doi + * The DOI of the challenge. * * @return doi */ - @Schema(name = "doi", required = false) + @Size(max = 120) + @Schema( + name = "doi", + example = "https://doi.org/123/abc", + description = "The DOI of the challenge.", + required = false) public String getDoi() { return doi; } @@ -245,27 +247,6 @@ public void setStatus(ChallengeStatusDto status) { this.status = status; } - public ChallengeDto difficulty(ChallengeDifficultyDto difficulty) { - this.difficulty = difficulty; - return this; - } - - /** - * Get difficulty - * - * @return difficulty - */ - @NotNull - @Valid - @Schema(name = "difficulty", required = true) - public ChallengeDifficultyDto getDifficulty() { - return difficulty; - } - - public void setDifficulty(ChallengeDifficultyDto difficulty) { - this.difficulty = difficulty; - } - public ChallengeDto platform(SimpleChallengePlatformDto platform) { this.platform = platform; return this; @@ -292,11 +273,16 @@ public ChallengeDto websiteUrl(String websiteUrl) { } /** - * Get websiteUrl + * A URL to the website or image. * * @return websiteUrl */ - @Schema(name = "websiteUrl", required = false) + @Size(max = 500) + @Schema( + name = "websiteUrl", + example = "https://openchallenges.io", + description = "A URL to the website or image.", + required = false) public String getWebsiteUrl() { return websiteUrl; } @@ -311,11 +297,16 @@ public ChallengeDto avatarUrl(String avatarUrl) { } /** - * Get avatarUrl + * A URL to the website or image. * * @return avatarUrl */ - @Schema(name = "avatarUrl", required = false) + @Size(max = 500) + @Schema( + name = "avatarUrl", + example = "https://openchallenges.io", + description = "A URL to the website or image.", + required = false) public String getAvatarUrl() { return avatarUrl; } @@ -464,13 +455,15 @@ public ChallengeDto starredCount(Integer starredCount) { } /** - * The number of times the challenge has been starred by users. + * The number of times the challenge has been starred by users. minimum: 0 * * @return starredCount */ @NotNull + @Min(0) @Schema( name = "starredCount", + example = "100", description = "The number of times the challenge has been starred by users.", required = true) public Integer getStarredCount() { @@ -487,13 +480,17 @@ public ChallengeDto createdAt(OffsetDateTime createdAt) { } /** - * Get createdAt + * Datetime when metadata was added to the OC database. * * @return createdAt */ @NotNull @Valid - @Schema(name = "createdAt", example = "2022-07-04T22:19:11Z", required = true) + @Schema( + name = "createdAt", + example = "2022-07-04T22:19:11Z", + description = "Datetime when metadata was added to the OC database.", + required = true) public OffsetDateTime getCreatedAt() { return createdAt; } @@ -508,13 +505,17 @@ public ChallengeDto updatedAt(OffsetDateTime updatedAt) { } /** - * Get updatedAt + * Datetime when metadata was last modified in the OC database. * * @return updatedAt */ @NotNull @Valid - @Schema(name = "updatedAt", example = "2022-07-04T22:19:11Z", required = true) + @Schema( + name = "updatedAt", + example = "2022-07-04T22:19:11Z", + description = "Datetime when metadata was last modified in the OC database.", + required = true) public OffsetDateTime getUpdatedAt() { return updatedAt; } @@ -539,7 +540,6 @@ public boolean equals(Object o) { && Objects.equals(this.description, challenge.description) && Objects.equals(this.doi, challenge.doi) && Objects.equals(this.status, challenge.status) - && Objects.equals(this.difficulty, challenge.difficulty) && Objects.equals(this.platform, challenge.platform) && Objects.equals(this.websiteUrl, challenge.websiteUrl) && Objects.equals(this.avatarUrl, challenge.avatarUrl) @@ -563,7 +563,6 @@ public int hashCode() { description, doi, status, - difficulty, platform, websiteUrl, avatarUrl, @@ -588,7 +587,6 @@ public String toString() { sb.append(" description: ").append(toIndentedString(description)).append("\n"); sb.append(" doi: ").append(toIndentedString(doi)).append("\n"); sb.append(" status: ").append(toIndentedString(status)).append("\n"); - sb.append(" difficulty: ").append(toIndentedString(difficulty)).append("\n"); sb.append(" platform: ").append(toIndentedString(platform)).append("\n"); sb.append(" websiteUrl: ").append(toIndentedString(websiteUrl)).append("\n"); sb.append(" avatarUrl: ").append(toIndentedString(avatarUrl)).append("\n"); diff --git a/apps/openchallenges/challenge-service/src/main/java/org/sagebionetworks/openchallenges/challenge/service/model/dto/ChallengeSearchQueryDto.java b/apps/openchallenges/challenge-service/src/main/java/org/sagebionetworks/openchallenges/challenge/service/model/dto/ChallengeSearchQueryDto.java index fb4dc8a86a..9104963715 100644 --- a/apps/openchallenges/challenge-service/src/main/java/org/sagebionetworks/openchallenges/challenge/service/model/dto/ChallengeSearchQueryDto.java +++ b/apps/openchallenges/challenge-service/src/main/java/org/sagebionetworks/openchallenges/challenge/service/model/dto/ChallengeSearchQueryDto.java @@ -35,10 +35,6 @@ public class ChallengeSearchQueryDto { @JsonProperty("direction") private ChallengeDirectionDto direction = null; - @JsonProperty("difficulties") - @Valid - private List difficulties = null; - @JsonProperty("incentives") @Valid private List incentives = null; @@ -185,37 +181,6 @@ public void setDirection(ChallengeDirectionDto direction) { this.direction = direction; } - public ChallengeSearchQueryDto difficulties(List difficulties) { - this.difficulties = difficulties; - return this; - } - - public ChallengeSearchQueryDto addDifficultiesItem(ChallengeDifficultyDto difficultiesItem) { - if (this.difficulties == null) { - this.difficulties = new ArrayList<>(); - } - this.difficulties.add(difficultiesItem); - return this; - } - - /** - * An array of challenge difficulty levels used to filter the results. - * - * @return difficulties - */ - @Valid - @Schema( - name = "difficulties", - description = "An array of challenge difficulty levels used to filter the results.", - required = false) - public List getDifficulties() { - return difficulties; - } - - public void setDifficulties(List difficulties) { - this.difficulties = difficulties; - } - public ChallengeSearchQueryDto incentives(List incentives) { this.incentives = incentives; return this; @@ -516,7 +481,6 @@ public boolean equals(Object o) { && Objects.equals(this.sort, challengeSearchQuery.sort) && Objects.equals(this.sortSeed, challengeSearchQuery.sortSeed) && Objects.equals(this.direction, challengeSearchQuery.direction) - && Objects.equals(this.difficulties, challengeSearchQuery.difficulties) && Objects.equals(this.incentives, challengeSearchQuery.incentives) && Objects.equals(this.minStartDate, challengeSearchQuery.minStartDate) && Objects.equals(this.maxStartDate, challengeSearchQuery.maxStartDate) @@ -537,7 +501,6 @@ public int hashCode() { sort, sortSeed, direction, - difficulties, incentives, minStartDate, maxStartDate, @@ -559,7 +522,6 @@ public String toString() { sb.append(" sort: ").append(toIndentedString(sort)).append("\n"); sb.append(" sortSeed: ").append(toIndentedString(sortSeed)).append("\n"); sb.append(" direction: ").append(toIndentedString(direction)).append("\n"); - sb.append(" difficulties: ").append(toIndentedString(difficulties)).append("\n"); sb.append(" incentives: ").append(toIndentedString(incentives)).append("\n"); sb.append(" minStartDate: ").append(toIndentedString(minStartDate)).append("\n"); sb.append(" maxStartDate: ").append(toIndentedString(maxStartDate)).append("\n"); diff --git a/apps/openchallenges/challenge-service/src/main/java/org/sagebionetworks/openchallenges/challenge/service/model/entity/ChallengeEntity.java b/apps/openchallenges/challenge-service/src/main/java/org/sagebionetworks/openchallenges/challenge/service/model/entity/ChallengeEntity.java index ce4c3159aa..3439b6cb32 100644 --- a/apps/openchallenges/challenge-service/src/main/java/org/sagebionetworks/openchallenges/challenge/service/model/entity/ChallengeEntity.java +++ b/apps/openchallenges/challenge-service/src/main/java/org/sagebionetworks/openchallenges/challenge/service/model/entity/ChallengeEntity.java @@ -75,10 +75,6 @@ public class ChallengeEntity { @GenericField() private String status; - @Column(nullable = false) - @GenericField() - private String difficulty; - @ManyToOne(fetch = FetchType.LAZY) @JoinColumn(name = "platform_id", nullable = true) @IndexedEmbedded(includePaths = {"slug", "name"}) diff --git a/apps/openchallenges/challenge-service/src/main/java/org/sagebionetworks/openchallenges/challenge/service/model/mapper/ChallengeMapper.java b/apps/openchallenges/challenge-service/src/main/java/org/sagebionetworks/openchallenges/challenge/service/model/mapper/ChallengeMapper.java index 189e9a90d7..d2b943c619 100644 --- a/apps/openchallenges/challenge-service/src/main/java/org/sagebionetworks/openchallenges/challenge/service/model/mapper/ChallengeMapper.java +++ b/apps/openchallenges/challenge-service/src/main/java/org/sagebionetworks/openchallenges/challenge/service/model/mapper/ChallengeMapper.java @@ -1,6 +1,5 @@ package org.sagebionetworks.openchallenges.challenge.service.model.mapper; -import org.sagebionetworks.openchallenges.challenge.service.model.dto.ChallengeDifficultyDto; import org.sagebionetworks.openchallenges.challenge.service.model.dto.ChallengeDto; import org.sagebionetworks.openchallenges.challenge.service.model.dto.ChallengeIncentiveDto; import org.sagebionetworks.openchallenges.challenge.service.model.dto.ChallengeStatusDto; @@ -36,10 +35,7 @@ public ChallengeDto convertToDto(ChallengeEntity entity, Object... args) { BeanUtils.copyProperties(entity, dto, "stars", "inputDataTypes", "platform"); LOG.info("challenge dto before set: {}", dto); dto.setStatus(ChallengeStatusDto.fromValue(entity.getStatus())); - dto.setDifficulty(ChallengeDifficultyDto.fromValue(entity.getDifficulty())); - // if (entity.getPlatform() != null) { - // dto.setPlatform(platformMapper.convertToDto(entity.getPlatform())); - // } + dto.setPlatform(platformMapper.convertToDto(entity.getPlatform())); dto.submissionTypes( entity.getSubmissionTypes().stream() .map(o -> ChallengeSubmissionTypeDto.fromValue(o.getName())) diff --git a/apps/openchallenges/challenge-service/src/main/java/org/sagebionetworks/openchallenges/challenge/service/model/repository/CustomChallengeRepositoryImpl.java b/apps/openchallenges/challenge-service/src/main/java/org/sagebionetworks/openchallenges/challenge/service/model/repository/CustomChallengeRepositoryImpl.java index 302dad8356..0a0736d329 100644 --- a/apps/openchallenges/challenge-service/src/main/java/org/sagebionetworks/openchallenges/challenge/service/model/repository/CustomChallengeRepositoryImpl.java +++ b/apps/openchallenges/challenge-service/src/main/java/org/sagebionetworks/openchallenges/challenge/service/model/repository/CustomChallengeRepositoryImpl.java @@ -18,7 +18,6 @@ import org.hibernate.search.mapper.orm.session.SearchSession; import org.sagebionetworks.openchallenges.challenge.service.exception.BadRequestException; import org.sagebionetworks.openchallenges.challenge.service.model.dto.ChallengeCategoryDto; -import org.sagebionetworks.openchallenges.challenge.service.model.dto.ChallengeDifficultyDto; import org.sagebionetworks.openchallenges.challenge.service.model.dto.ChallengeDirectionDto; import org.sagebionetworks.openchallenges.challenge.service.model.dto.ChallengeIncentiveDto; import org.sagebionetworks.openchallenges.challenge.service.model.dto.ChallengeSearchQueryDto; @@ -55,9 +54,6 @@ private SearchResult getSearchResult( if (query.getStatus() != null && !query.getStatus().isEmpty()) { predicates.add(getChallengeStatusPredicate(pf, query)); } - if (query.getDifficulties() != null && !query.getDifficulties().isEmpty()) { - predicates.add(getChallengeDifficultyPredicate(pf, query)); - } if (query.getPlatforms() != null && !query.getPlatforms().isEmpty()) { predicates.add(getChallengePlatformPredicate(pf, query)); } @@ -132,24 +128,6 @@ private SearchPredicate getChallengeStatusPredicate( .toPredicate(); } - /** - * Matches the challenges whose difficulty is in the list of difficulties specified. - * - * @param pf - * @param query - * @return - */ - private SearchPredicate getChallengeDifficultyPredicate( - SearchPredicateFactory pf, ChallengeSearchQueryDto query) { - return pf.bool( - b -> { - for (ChallengeDifficultyDto difficulty : query.getDifficulties()) { - b.should(pf.match().field("difficulty").matching(difficulty.toString())); - } - }) - .toPredicate(); - } - /** * Matches the challenges whose platform is in the list of platforms specified. * diff --git a/apps/openchallenges/challenge-service/src/main/resources/db/challenges.csv b/apps/openchallenges/challenge-service/src/main/resources/db/challenges.csv index 2d76ca01c2..865a19984e 100644 --- a/apps/openchallenges/challenge-service/src/main/resources/db/challenges.csv +++ b/apps/openchallenges/challenge-service/src/main/resources/db/challenges.csv @@ -1,477 +1,477 @@ -"id","slug","name","headline","description","avatar_url","website_url","status","difficulty","platform","doi","start_date","end_date","created_at","updated_at" -"1","network-topology-and-parameter-inference","Network Topology and Parameter Inference","Optimize methods to estimate biology model parameters","Participants are asked to develop and/or apply optimization methods, including the selection of the most informative experiments, to accurately estimate parameters and predict outcomes of perturbations in Systems Biology models.","","https://www.synapse.org/#!Synapse:syn2821735","completed","intermediate","1","","2012-06-01","2012-10-01","2023-11-15 22:40:15","2023-11-16 18:31:42" -"2","breast-cancer-prognosis","Breast Cancer Prognosis","Predict breast cancer survival from clinical and genomic data","The goal of the breast cancer prognosis Challenge is to assess the accuracy of computational models designed to predict breast cancer survival, based on clinical information about the patient's tumor as well as genome-wide molecular profiling data including gene expression and copy number profiles.","","https://www.synapse.org/#!Synapse:syn2813426","completed","intermediate","1","","2012-07-12","2012-10-15","2023-11-14 20:36:32","2023-11-14 20:17:33" -"3","phil-bowen-als-prediction-prize4life","Phil Bowen ALS Prediction Prize4Life","Seeking treatment to halt ALS's fatal loss of motor function","Amyotrophic Lateral Sclerosis (ALS), or Lou Gehrig's disease, is a fatal neurological condition causing the death of nerve cells in the brain and spinal cord, resulting in a progressive loss of motor function while cognitive functions persist. Typically emerging around age 50, it affects about five in 100,000 people worldwide, with familial hereditary forms as the only known risk factors (5-10% of cases). There is currently no cure for ALS. The FDA-approved drug Riluzole extends life by a few months. ALS patients, on average, have a life expectancy of 2-5 years, with 10% experiencing slower disease progression. Astrophysicist Stephen Hawking, living with ALS for 49 years, is an exceptional case. The DREAM-Phil Bowen ALS Prediction Prize4Life, or ""ALS Prediction Prize,"" utilizes the PRO-ACT database with clinical data from over 7,500 ALS patients. This collaboration with DREAM aims to expedite ALS treatment discovery. Prize4Life, a non-profit, collaborates with NEALS and ALS Ther...","","https://www.synapse.org/#!Synapse:syn2826267","completed","intermediate","1","","2012-06-01","2012-10-01","2023-11-01 22:09:02","2023-11-13 17:16:16" -"4","drug-sensitivity-and-drug-synergy-prediction","Drug Sensitivity and Drug Synergy Prediction","Predicting drug sensitivity in human cell lines","Development of new cancer therapeutics currently requires a long and protracted process of experimentation and testing. Human cancer cell lines represent a good model to help identify associations between molecular subtypes, pathways, and drug response. In recent years there have been several efforts to generate genomic profiles of collections of cell lines and to determine their response to panels of candidate therapeutic compounds. These data provide the basis for the development of in silico models of sensitivity based either on the unperturbed genetic potential of a cancer cell, or by using perturbation data to incorporate knowledge of actual cell response. Making predictions from either of these data profiles will be beneficial in identifying single and combinatorial chemotherapeutic response in patients. To that end, the present challenge seeks computational methods, derived from the molecular profiling of cell lines both in a static state and in response to perturbation of ...","","https://www.synapse.org/#!Synapse:syn2785778","completed","intermediate","1","","2012-06-01","2012-10-01","2023-11-01 22:08:36","2023-11-16 17:58:39" -"5","niehs-ncats-unc-toxicogenetics","NIEHS-NCATS-UNC Toxicogenetics","Predicting cytotoxicity from genomic and chemical data","This challenge is designed to build predictive models of cytotoxicity as mediated by exposure to environmental toxicants and drugs. To approach this question, we will provide a dataset containing cytotoxicity estimates as measured in lymphoblastoid cell lines derived from 884 individuals following in vitro exposure to 156 chemical compounds. In subchallenge 1, participants will be asked to model interindividual variability in cytotoxicity based on genomic profiles in order to predict cytotoxicity in unknown individuals. In subchallenge 2, participants will be asked to predict population-level parameters of cytotoxicity across chemicals based on structural attributes of compounds in order to predict median cytotoxicity and mean variance in toxicity for unknown compounds.","","https://www.synapse.org/#!Synapse:syn1761567","completed","intermediate","1","","2013-06-10","2013-09-15","2023-11-01 22:08:45","2023-11-01 22:06:01" -"6","whole-cell-parameter-estimation","Whole-Cell Parameter Estimation","Seeking innovative parameter estimation methods for large models","The goal of this challenge is to explore and compare innovative approaches to parameter estimation of large, heterogeneous computational models. Participants are encouraged to develop and/or apply optimization methods, including the selection of the most informative experiments. The organizers encourage participants to form teams to collaboratively solve the challenge.","","https://www.synapse.org/#!Synapse:syn1876068","completed","intermediate","1","","2013-06-10","2013-09-23","2023-06-23 00:00:00","2023-11-01 22:06:23" -"7","hpn-dream-breast-cancer-network-inference","HPN-DREAM Breast Cancer Network Inference","Inferring causal signaling networks in breast cancer","The overall goal of the Heritage-DREAM breast cancer network inference challenge is to quickly and effectively advance our ability to infer causal signaling networks and predict protein phosphorylation dynamics in cancer. We provide extensive training data from experiments on four breast cancer cell lines stimulated with various ligands. The data comprise protein abundance time-courses under inhibitor perturbations.","","https://www.synapse.org/#!Synapse:syn1720047","completed","intermediate","1","","2013-06-10","2013-09-16","2023-06-23 00:00:00","2023-11-13 17:15:59" -"8","rheumatoid-arthritis-responder","Rheumatoid Arthritis Responder","Unlocking Anti-TNF response predictors in RA therapy","The goal of this project is to use a crowd-based competition framework to develop a validated molecular predictor of anti-TNF response in RA. There is an increasing need for predictors of response to therapy in inflammatory disease driven by the observation that most clinically defined diseases show variable response and the growing availability of alternative therapies. Anti-TNF drugs in Rheumatoid Arthritis represent a prototypical example of this opportunity. A number of studies have tried, over the past decade, to develop a robust predictor of response. We believe the time is right to try a different approach to developing such a biomarker with a crowd-sourced collaborative competition. This is based on DREAM and Sage Bionetworks' experience with running competitions and the availability of new unpublished large-scale data relating to RA treatment response.THIS CHALLENGE RAN FROM FEBRUARY TO OCTOBER 2014 AND IS NOW CLOSED.","","https://www.synapse.org/#!Synapse:syn1734172","completed","intermediate","1","","2014-02-10","2014-06-04","2023-06-23 00:00:00","2023-11-15 22:42:17" -"9","icgc-tcga-dream-mutation-calling","ICGC-TCGA DREAM Mutation Calling","Crowdsourcing challenge to improve cancer mutation detection","The ICGC-TCGA DREAM Genomic Mutation Calling Challenge (herein, The Challenge) is an international effort to improve standard methods for identifying cancer-associated mutations and rearrangements in whole-genome sequencing (WGS) data. Leaders of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) cancer genomics projects are joining with Sage Bionetworks and IBM-DREAM to initiate this innovative open crowd-sourced Challenge [1-3].","","https://www.synapse.org/#!Synapse:syn312572","completed","intermediate","1","","2013-12-14","2016-04-22","2023-06-23 00:00:00","2023-10-14 05:38:15" -"10","acute-myeloid-leukemia-outcome-prediction","Acute Myeloid Leukemia Outcome Prediction","Uncover drivers of AML using clinical and proteomic data","The AML Outcome Prediction Challenge provides a unique opportunity to access and interpret a rich dataset for AML patients that includes clinical covariates, select gene mutation status and proteomic data. Capitalizing on a unique AML reverse phase protein array (RPPA) dataset obtained at M.D. Anderson Cancer Center that captures 271 measurements for each patient, participants of the DREAM 9 Challenge will help uncover what drives AML. Outcomes of this Challenge have the potential to be used immediately to tailor therapies for newly diagnosed leukemia patients and to accelerate the development of new drugs for leukemia.","","https://www.synapse.org/#!Synapse:syn2455683","completed","intermediate","1","","2014-06-02","2014-09-15","2023-06-23 00:00:00","2023-10-14 05:38:16" -"11","broad-dream-gene-essentiality-prediction","Broad-DREAM Gene Essentiality Prediction","Crowdsourcing models to predict cancer cell gene dependencies","The goal of this project is to use a crowd-based competition to develop predictive models that can infer gene dependency scores in cancer cells (genes that are essential to cancer cell viability when suppressed) using features of those cell lines. An additional goal is to find a small set of biomarkers (gene expression, copy number, and mutation features) that can best predict a single gene or set of genes.","","https://www.synapse.org/#!Synapse:syn2384331","completed","intermediate","1","","2014-06-02","2014-09-29","2023-06-23 00:00:00","2023-10-14 05:38:16" -"12","alzheimers-disease-big-data","Alzheimer's Disease Big Data","Seeking accurate predictive biomarkers","The goal of the Alzheimer's Disease Big Data DREAM Challenge #1 (AD#1) was to apply an open science approach to rapidly identify accurate predictive AD biomarkers that can be used by the scientific, industrial and regulatory communities to improve AD diagnosis and treatment. AD#1 will be the first in a series of AD Data Challenges to leverage genetics and brain imaging in combination with cognitive assessments, biomarkers and demographic information from cohorts ranging from cognitively normal to mild cognitively impaired to individuals with AD.","","https://www.synapse.org/#!Synapse:syn2290704","completed","intermediate","1","","2014-06-02","2014-10-17","2023-06-23 00:00:00","2023-10-14 05:38:17" -"13","olfaction-prediction","Olfaction Prediction","Predicting smell from molecule features","The goal of the DREAM Olfaction Prediction Challenge is to find models that can predict how a molecule smells from its physical and chemical features. A model that allows us to predict a smell from a molecule will provide fundamental insights into how odor chemicals are transformed into a smell percept in the brain. Further, being able to predict how a chemical smells will greatly accelerate the design of new molecules to be used as fragrances. Currently, fragrance chemists synthesize many molecules to obtain a new ingredient, but most of these will not have the desired qualities.","","https://www.synapse.org/#!Synapse:syn2811262","completed","intermediate","1","","2015-01-15","2015-05-01","2023-11-01 22:11:08","2023-10-14 05:38:17" -"14","prostate-cancer","Prostate Cancer","Predict survival of docetaxel treatment in mCRPC patients","This challenge will attempt to improve the prediction of survival and toxicity of docetaxel treatment in patients with metastatic castration-resistant prostate cancer (mCRPC). The primary benefit of this Challenge will be to establish new quantitative benchmarks for prognostic modeling in mCRPC, with a potential impact for clinical decision making and ultimately understanding the mechanism of disease progression. Participating teams will be asked to submit predictive models based on clinical variables from the comparator arms of four phase III clinical trials with over 2,000 mCRPC patients treated with first-line docetaxel. The comparator arm of a clinical trial represents the patients that receive a treatment that is considered to be effective. This arm of the clinical trial is used to evaluate the effectiveness of the new therapy being tested.","","https://www.synapse.org/#!Synapse:syn2813558","completed","intermediate","1","","2015-03-16","2015-07-27","2023-06-23 00:00:00","2023-10-14 05:38:18" -"15","als-stratification-prize4life","ALS Stratification Prize4Life","Predicting ALS progression and survival with data","As illustrated by the overview figure below, (a) Challenge Data includes data from ALS clinical trials and ALS registries. ALS clinical trials consist of patients from clinical trials available open access on the PRO-ACT database and patients from 6 clinical trials not yet added into the database. Data from ALS registries was collected from patients in national ALS registries. (b) Data is divided into three subsets-training data provided to solvers in full, leaderboard, and validation data that is available only to the organizers and is reserved for the scoring of the challenge. (c) The goal of this challenge is then to predict the Clinical Targets, i.e. the disease progression as ALSFRS slope as well as survival. (d) For Building the Models, participants create two algorithms-one that selects features and one that predicts outcomes. To perform predictions, data from a given patient is fed into the selector . The selector selects 6 features and a cluster/model ID (3), e.g. from a...","","https://www.synapse.org/#!Synapse:syn2873386","completed","intermediate","1","","2015-06-22","2015-10-04","2023-06-23 00:00:00","2023-10-14 05:38:19" -"16","astrazeneca-sanger-drug-combination-prediction","AstraZeneca-Sanger Drug Combination Prediction","Predict effective drug combinations using genomic data","To accelerate the understanding of drug synergy, AstraZeneca has partnered with the European Bioinformatic Institute, the Sanger Institute, Sage Bionetworks, and the distributed DREAM community to launch the AstraZeneca-Sanger Drug Combination Prediction DREAM Challenge. This Challenge is designed to explore fundamental traits that underlie effective combination treatments and synergistic drug behavior using baseline genomic data, i.e. data collected pretreatment. As the basis of the Challenge, AstraZeneca is releasing ~11.5k experimentally tested drug combinations measuring cell viability over 118 drugs and 85 cancer cell lines (primarily colon, lung, and breast), and monotherapy drug response data for each drug and cell line. Moreover, in coordination with the Genomics of Drug Sensitivity in Cancer and COSMIC teams at the Sanger Institute, genomic data including gene expression, mutations (whole exome), copy-number alterations, and methylation data will be released into the publ...","","https://www.synapse.org/#!Synapse:syn4231880","completed","intermediate","1","","2015-09-03","2016-03-14","2023-06-23 00:00:00","2023-10-14 05:38:19" -"17","smc-dna-meta","SMC-DNA Meta","Seeking most accurate somatic mutation detection pipeline","The goal of this Challenge is to identify the most accurate meta-pipeline for somatic mutation detection, and establish the state-of-the-art. The algorithms in this Challenge must use as input mutations predicted by one or more variant callers and output mutation calls associated with cancer. An additional goal is to highlight the complementarity of the calling algorithms and help understand their individual advantages/deficiencies.","","https://www.synapse.org/#!Synapse:syn4588939","completed","intermediate","1","","2015-08-17","2016-04-10","2023-06-23 00:00:00","2023-10-14 05:38:20" -"18","smc-het","SMC-Het","Crowdsourcing challenge to improve tumor subclonal reconstruction","The ICGC-TCGA DREAM Somatic Mutation Calling-Tumour Heterogeneity Challenge (SMC-Het) is an international effort to improve standard methods for subclonal reconstruction-to quantify and genotype each individual cell population present within a tumor. Leaders of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) cancer genomics projects are joining with Sage Bionetworks and IBM-DREAM to initiate this innovative open crowd-sourced Challenge [1-3].","","https://www.synapse.org/#!Synapse:syn2813581","completed","intermediate","1","","2015-11-16","2016-06-30","2023-11-01 22:21:29","2023-10-14 05:38:21" -"19","respiratory-viral","Respiratory Viral","Early predictors of respiratory infection and contagiousness","Respiratory viruses are highly infectious and cause acute illness in millions of people every year. However, there is wide variation in the physiologic response to exposure at the individual level. Some people that are exposed to virus are able to completely avoid infection. Others contract virus but are able to fight it off without exhibiting any symptoms of illness such as coughing, sneezing, sore throat or fever. It is not well understood what characteristics may protect individuals from respiratory viral infection. These individual responses are likely influenced by multiple processes including both the basal state of the human host upon exposure and the dynamics of host immune response in the early hours immediately following exposure. Many of these processes play out in the peripheral blood through activation and recruitment of circulating immune cells. Global gene expression patterns measured in peripheral blood at the time of symptom onset-several days after viral exposure...","","https://www.synapse.org/#!Synapse:syn5647810","completed","intermediate","1","","2016-05-16","2016-09-28","2023-06-23 00:00:00","2023-11-14 20:16:42" -"20","disease-module-identification","Disease Module Identification","Crowdsourcing challenge to find disease modules in genomic networks","The Disease Module Identification DREAM Challenge is an open community effort to systematically assess module identification methods on a panel of state-of-the-art genomic networks and leverage the “wisdom of crowds” to discover novel modules and pathways underlying complex diseases.","","https://www.synapse.org/#!Synapse:syn6156761","completed","intermediate","1","https://doi.org/10.1038/s41592-019-0509-5","2016-06-24","2016-10-01","2023-11-01 22:21:32","2023-10-16 21:17:48" -"21","encode","ENCODE","Predict transcription factor binding sites from limited data","Transcription factors (TFs) are regulatory proteins that bind specific DNA sequence patterns (motifs) in the genome and affect transcription rates of target genes. Binding sites of TFs differ across cell types and experimental conditions. Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is an experimental method that is commonly used to obtain the genome-wide binding profile of a TF of interest in a specific cell type/condition. However, profiling the binding landscape of every TF in every cell type/condition is infeasible due to constraints on cost, material and effort. Hence, accurate computational prediction of in vivo TF binding sites is critical to complement experimental results.","","https://www.synapse.org/#!Synapse:syn6131484","completed","intermediate","1","","2016-07-07","2017-01-11","2023-11-01 22:21:32","2023-10-14 05:38:26" -"22","idea","Idea","Fostering collaborative solutions in health: the DREAM IDEA challenge","The DREAM Idea Challenge is designed to collaboratively shape and enable the solution of a question fundamental to improving human health. In the process, all proposals and their evaluation will be made publicly available for the explicit purpose of connecting modelers and experimentalists who want to address the same question. This Wall of Models will enable new collaborations, and help turn every good modeling idea into a success story. It will further serve as a basis for new DREAM challenges.","","https://www.synapse.org/#!Synapse:syn5659209","completed","advanced","1","","2016-06-15","2017-04-30","2023-06-23 00:00:00","2023-11-20 20:18:36" -"23","smc-rna","SMC-RNA","Crowdsourcing challenge to improve cancer mutation detection from rna data","The ICGC-TCGA DREAM Somatic Mutation Calling-RNA Challenge (SMC-RNA) is an international effort to improve standard methods for identifying cancer-associated rearrangements in RNA sequencing (RNA-seq) data. Leaders of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) cancer genomics projects are joining with Sage Bionetworks and IBM-DREAM to initiate this innovative open crowd-sourced Challenge [1-3].","","https://www.synapse.org/#!Synapse:syn2813589","completed","intermediate","1","","2016-06-29","2017-05-02","2023-06-23 00:00:00","2023-10-14 05:38:29" -"24","digital-mammography-dream-challenge","Digital Mammography DREAM Challenge","Improve mammography prediction to detect breast cancer early","The Digital Mammography DREAM Challenge will attempt to improve the predictive accuracy of digital mammography for the early detection of breast cancer. The primary benefit of this Challenge will be to establish new quantitative tools-machine learning, deep learning or other-that can help decrease the recall rate of screening mammography, with a potential impact on shifting the balance of routine breast cancer screening towards more benefit and less harm. Participating teams will be asked to submit predictive models based on over 640,000 de-identified digital mammography images from over 86000 subjects, with corresponding clinical variables.","","https://www.synapse.org/#!Synapse:syn4224222","completed","advanced","1","https://doi.org/10.1001/jamanetworkopen.2020.0265","2016-11-18","2017-05-16","2023-06-23 00:00:00","2023-10-14 05:38:29" -"25","multiple-myeloma","Multiple Myeloma","Develop precise risk model for myeloma patients","Multiple myeloma (MM) is a cancer of the plasma cells in the bone marrow, with about 25,000 newly diagnosed patients per year in the United States alone. The disease's clinical course depends on a complex interplay of clinical traits and molecular characteristics of the plasma cells.1 Since risk-adapted therapy is becoming standard of care, there is an urgent need for a precise risk stratification model to assist in therapeutic decision-making and research. While progress has been made, there remains a significant opportunity to improve patient stratification to optimize treatment and to develop new therapies for high-risk patients. A DREAM Challenge represents a chance not only to integrate available data and analytical approaches to tackle this important problem, but also provides the ability to benchmark potential methods to identify those with the greatest potential to yield patient care benefits in the future.","","https://www.synapse.org/#!Synapse:syn6187098","completed","intermediate","1","","2017-06-30","2017-11-08","2023-06-23 00:00:00","2023-10-14 05:38:31" -"26","ga4gh-dream-workflow-execution","GA4GH-DREAM Workflow Execution","Develop technologies to enable distributed genomic data analysis","The highly distributed and disparate nature of genomic and clinical data generated around the world presents an enormous challenge for those scientists who wish to integrate and analyze these data. The sheer volume of data often exceeds the capacity for storage at any one site and prohibits the efficient transfer between sites. To address this challenge, researchers must bring their computation to the data. Numerous groups are now developing technologies and best practice methodologies for running portable and reproducible genomic analysis pipelines as well as tools and APIs for discovering genomic analysis resources. Software development, deployment, and sharing efforts in these groups commonly rely on the use of modular workflow pipelines and virtualization based on Docker containers and related tools.","","https://www.synapse.org/#!Synapse:syn8507133","completed","intermediate","1","","2017-07-21","2017-12-31","2023-06-23 00:00:00","2023-10-14 05:38:31" -"27","parkinsons-disease-digital-biomarker","Parkinson's Disease Digital Biomarker","Develop Parkinson's digital signatures from sensor data for Parkinson's disease","The Parkinson's Disease Digital Biomarker DREAM Challenge is a first of it's kind challenge, designed to benchmark methods for the processing of sensor data for development of digital signatures reflective of Parkinson's Disease. Participants will be provided with raw sensor (accelerometer, gyroscope, and magnetometer) time series data recorded during the performance of pre-specified motor tasks, and will be asked to extract data features which are predictive of PD pathology. In contrast to traditional DREAM challenges, this one will focus on feature extraction rather than predictive modeling, and submissions will be evaluated based on their ability to predict disease phenotype using an array of standard machine learning algorithms.","","https://www.synapse.org/#!Synapse:syn8717496","completed","intermediate","1","","2017-07-06","2017-11-10","2023-06-23 00:00:00","2023-11-14 19:10:32" -"28","nci-cptac-proteogenomics","NCI-CPTAC Proteogenomics","Develop tools to extract insights from cancer proteomics data","Cancer is driven by aberrations in the genome [1,2], and these alterations manifest themselves largely in the changes in the structure and abundance of proteins, the main functional gene products. Hence, characterization and analyses of alterations in the proteome has the promise to shed light into cancer development and may improve development of both biomarkers and therapeutics. Measuring the proteome is very challenging, but recent rapid technology developments in mass spectrometry are enabling deep proteomics analysis [3]. Multiple initiatives have been launched to take advantage of this development to characterize the proteome of tumours, such as the Clinical Proteomic Tumor Analysis Consortium (CPTAC). These efforts hold the promise to revolutionize cancer research, but this will only be possible if the community develops computational tools powerful enough to extract the most information from the proteome, and to understand the association between genome, transcriptome and ...","","https://www.synapse.org/#!Synapse:syn8228304","completed","intermediate","1","","2017-06-26","2017-11-20","2023-11-01 22:21:37","2023-10-14 05:38:33" -"29","multi-targeting-drug","Multi-Targeting Drug","Seeking generalizable methods to predict multi-target compound binding","The objective of this challenge is to incentivize development of methods for predicting compounds that bind to multiple targets. In particular, methods that are generalizable to multiple prediction problems are sought. To achieve this, participants will be asked to predict 2 separate compounds, each having specific targets to which they should bind, and a list of anti-targets to avoid. Participants should use the same methods to produce answers for questions 1 and 2.","","https://www.synapse.org/#!Synapse:syn8404040","completed","intermediate","1","","2017-10-05","2018-02-26","2023-06-23 00:00:00","2023-10-14 05:38:33" -"30","single-cell-transcriptomics","Single Cell Transcriptomics","Reconstructing cell locations in Drosophila embryo from transcripts","In this Challenge on Single-Cell Transcriptomics, participants will reconstruct the location of single cells in the Drosophila embryo using single-cell transcriptomic data. Data will be made available in late August and participating challenge teams can work on the data and submit their results previous to the DREAM Conference. The best performers will be announced at the DREAM conference on Dec 8.","","https://www.synapse.org/#!Synapse:syn15665609","completed","intermediate","1","","2018-09-04","2018-11-21","2023-06-23 00:00:00","2023-11-16 18:38:46" -"31","idg-drug-kinase-binding","IDG Drug-Kinase Binding","Drug-kinase binding prediction for IDG drug-kinase binding","This IDG-DREAM Drug-Kinase Binding Prediction Challenge seeks to evaluate the power of statistical and machine learning models as a systematic and cost-effective means for catalyzing compound-target interaction mapping efforts by prioritizing most potent interactions for further experimental evaluation. The Challenge will focus on kinase inhibitors, due to their clinical importance [2], and will be implemented in a screening-based, pre-competitive drug discovery project in collaboration with theIlluminating the Druggable Genome (IDG) Kinase-focused Data and Resource Generation Center, consortium, with the aim to establish kinome-wide target profiles of small-molecule agents, with the goal of extending the druggability of the human kinome space.","","https://www.synapse.org/#!Synapse:syn15667962","completed","intermediate","1","","2018-10-01","2019-04-18","2023-06-23 00:00:00","2023-11-14 19:07:18" -"32","malaria","Malaria","Predict malaria drug resistance from parasite gene expression for malaria","The Malaria DREAM Challenge is open to anyone interested in contributing to the development of computational models that address important problems in advancing the fight against malaria. The overall goal of the first Malaria DREAM Challenge is to predict Artemisinin (Art) drug resistance level of a test set of malaria parasites using their in vitro transcription data and a training set consisting of published in vivo and unpublished in vitrotranscriptomes. The in vivodataset consists of ~1000 transcription samples from various geographic locations covering a wide range of life cycles and resistance levels, with other accompanying data such as patient age, geographic location, Art combination therapy used, etc [Mok et al (2015) Science]. The in vitro transcription dataset consists of 55 isolates, with transcription collected at two timepoints (6 and 24 hours post-invasion), in the absence or presence of an Art perturbation, for two biological replicates using a custom microarray a...","","https://www.synapse.org/#!Synapse:syn16924919","completed","intermediate","1","","2019-04-30","2019-08-15","2023-06-23 00:00:00","2023-10-14 05:38:35" -"33","preterm-birth-prediction-transcriptomics","Preterm Birth Prediction - Transcriptomics","Determine gestational age for preterm birth prediction","A basic need in pregnancy care is to establish gestational age, and inaccurate estimates may lead to unnecessary interventions and sub-optimal patient management. Current approaches to establish gestational age rely on patient's recollection of her last menstrual period and/or ultrasound, with the latter being not only costly but also less accurate if not performed during the first trimester of pregnancy. Therefore development of an inexpensive and accurate molecular clock of pregnancy would be of benefit to patients and health care systems. Participants in sub-challenge 1 (Prediction of gestational age) will be given whole blood gene topic_3170 collected from pregnant women to develop prediction models for the gestational age at blood draw. Another challenge in obstetrics, in both low and high-income countries, is identification and treatment of women at risk of developing the ‘great obstetrical syndromes‘. Of these, preterm birth (PTB), defined as giving birth prior to completio...","","https://www.synapse.org/#!Synapse:syn18380862","completed","good_for_beginners","1","","2019-05-04","2019-12-05","2023-06-23 00:00:00","2023-11-14 19:07:28" -"34","single-cell-signaling-in-breast-cancer","Single-Cell Signaling in Breast Cancer","Exploring heterogeneous signaling in single cancer cells","Signaling underlines nearly every cellular event. Individual cells, even if genetically identical, respond to perturbation in different ways. This underscores the relevance of cellular heterogeneity, in particular in how cells respond to drugs. This is of high relevance since the fact that a subset of cells do not respond (or only weakly) to drugs can render this drug an ineffective treatment. In spite of its relevance to many diseases, comprehensive studies on the heterogeneous signaling in single cells are still lacking. We have generated the, to our knowledge, currently largest single cell signaling dataset on a panel of 67 well-characterized breast cancer cell lines by mass cytometry (3'015 conditions, ~80 mio single cells, 38 markers; Bandura et al. 2009; Bendall et al., 2011; Bodenmiller et al., 2012; Lun et al., 2017; Lun et al., 2019). These cell lines are, among others, also characterized at the genomic, transcriptomic, and proteomic level (Marcotte et al., 2016). We ask ...","","https://www.synapse.org/#!Synapse:syn20366914","completed","intermediate","1","","2018-08-20","2019-11-15","2023-06-23 00:00:00","2023-10-14 05:38:37" -"35","ehr-dream-challenge-patient-mortality-prediction","EHR DREAM Challenge: Patient Mortality Prediction","New tools to reconstruct cell lineages from CRISPR mutations","The recent advent of new CRISPR-based molecular tools allows the reconstruction of cell lineages based on the phylogenetical analysis of DNA mutations induced by CRISPR during development and promises to solve the lineage of complex model organisms at single-cell resolution (see image from McKenna et al Science 2016). To date, however, no lineage reconstruction algorithms have been rigorously examined for their performance/robustness across diverse molecular tools, datasets, and number of cells/size of lineage trees. It also remains unclear whether new Machine-Learning algorithms that go beyond the classical ones developed for reconstructing phylogenetic trees, could consistently reconstruct cell lineages to a high degree of accuracy. The challenge-a partnership between The Allen Institute and DREAM-will comprise 3 subchallenges that consist of reconstructing cell lineage trees of different sizes and nature. In subchallenge 1, participants will be given experimental molecular data...","","https://www.synapse.org/#!Synapse:syn18405991","completed","intermediate","1","https://doi.org/10.1093/jamia/ocad159","2019-09-09","2020-01-23","2023-06-23 00:00:00","2023-11-02 18:25:23" -"36","allen-institute-cell-lineage-reconstruction","Allen Institute Cell Lineage Reconstruction","New tools enable reconstructing complex cell lineages at single-cell resolution","The recent advent of new CRISPR-based molecular tools allows the reconstruction of cell lineages based on the phylogenetical analysis of DNA mutations induced by CRISPR during development and promises to solve the lineage of complex model organisms at single-cell resolution. To date, however, no lineage reconstruction algorithms have been rigorously examined for their performance/robustness across diverse molecular tools, datasets, and number of cells/size of lineage trees. It also remains unclear whether new Machine-Learning algorithms that go beyond the classical ones developed for reconstructing phylogenetic trees, could consistently reconstruct cell lineages to a high degree of accuracy. The challenge-a partnership between The Allen Institute and DREAM-will comprise 3 subchallenges that consist of reconstructing cell lineage trees of different sizes and nature. In subchallenge 1, participants will be given experimental molecular data to reconstruct in vitro cell lineages of l...","","https://www.synapse.org/#!Synapse:syn20692755","completed","intermediate","1","","2019-10-15","2020-02-06","2023-06-23 00:00:00","2023-11-02 18:25:24" -"37","tumor-deconvolution","Tumor Deconvolution","Deconvolve bulk tumor data into immune components","The extent of stromal and immune cell infiltration within solid tumors has prognostic and predictive significance. Unfortunately, expression profiling of tumors has, until very recently, largely been undertaken using bulk techniques (e.g., microarray and RNA-seq). Unlike single-cell methods (e.g., single-cell RNA-seq, FACS, mass cytometry, or immunohistochemistry), bulk approaches average expression across all cells (cancer, stromal, and immune) within the sample and, hence, do not directly quantitate tumor infiltration. This information can be recovered by computational tumor deconvolution methods, which would thus allow interrogation of immune subpopulations across the large collection of public bulk topic_3170sets. The goal of this Challenge is to evaluate the ability of computational methods to deconvolve bulk topic_3170, reflecting a mixture of cell types, into individual immune components. Methods will be assessed based on in vitro and in silico admixtures specifically gener...","","https://www.synapse.org/#!Synapse:syn15589870","completed","intermediate","1","","2019-06-26","2020-04-30","2023-06-23 00:00:00","2023-11-14 19:07:39" -"38","ctd2-pancancer-drug-activity","CTD2 Pancancer Drug Activity","Benchmark algorithms predicting drug targets from gene data","Over the last two years, the Columbia CTD2 Center developed PANACEA (Pancancer Analysis of Chemical Entity Activity), a comprehensive repertoire of dose response curves and molecular profiles representative of cellular responses to drug perturbations. PANACEA covers a broad spectrum of cellular contexts representative of poor outcome malignancies, including rare ones such as GIST sarcoma and gastroenteropancreatic neuroendocrine tumors (GEP-NETs). PANACEA is uniquely suited to support DREAM Challenges related to the elucidation of drug mechanism of action (MOA), drug sensitivity, and drug synergy. The goal of the CTD2 Pancancer Drug Activity DREAM Challenge is to foster the development and benchmarking of algorithms to predict targets of chemotherapeutic compounds from post-treatment transcriptional data.","","https://www.synapse.org/#!Synapse:syn20968331","completed","good_for_beginners","1","","2019-12-02","2020-02-13","2023-06-23 00:00:00","2023-10-20 23:11:10" -"39","ctd2-beataml","CTD2 BeatAML","Seeking new drug targets for precision AML treatment","In the era of precision medicine, AML patients have few therapeutic options, with “7 + 3” induction chemotherapy having been the standard for decades (Bertoli et al. 2017). While several agents targeting the myeloid marker CD33 or alterations in FLT3 or IDH2 have demonstrated efficacy in patients (Wei and Tiong 2017), responses are uncertain in some populations (Castaigne et al. 2012) and relapse remains prevalent (Stone et al. 2017). These drugs highlight both the promise of targeted therapies in AML and the urgent need for additional treatment options that are tailored to more refined patient subpopulations in order to achieve durable responses. The BeatAML initiative was launched as a comprehensive study of the relationship between molecular alterations and ex-vivo drug sensitivity in patients with AML. One of the primary goals of this multi-center study was to develop a discovery cohort that could yield new drug target hypotheses and predictive biomarkers of therapeutic respon...","","https://www.synapse.org/#!Synapse:syn20940518","completed","good_for_beginners","1","","2019-12-19","2020-04-28","2023-06-23 00:00:00","2023-10-14 05:38:42" -"40","metadata-automation","Metadata Automation","Semi-automating metadata annotation for enhanced data sharing in cancer research","The Cancer Research Data Commons (CRDC) will collate data across diverse groups of cancer researchers, each collecting biomedical data in different formats. This means the data must be retrospectively harmonized and transformed to enable this data to be submitted. In addition, to be findable by the broader scientific community, coherent information (metadata) is necessary about the data fields and values. Coherent metadata annotation of the data fields and their values can enable computational data transformation, query, and analysis. Creation of this type of descriptive metadata can require biomedical expertise to determine the best annotations and thus is a time-consuming and manual task which is both an obstacle and a bottleneck in data sharing and submissions. Goal-Using structured biomedical data files, challenge participants will develop tools to semi-automate annotation of metadata fields and values, using available research data annotations (e.g. caDSR CDEs) as well as es...","","https://www.synapse.org/#!Synapse:syn18065891","completed","intermediate","1","","2020-01-14","2020-06-02","2023-06-23 00:00:00","2023-10-14 05:38:42" -"41","automated-scoring-of-radiographic-joint-damage","Automated Scoring of Radiographic Joint Damage","Develop automated method to quantify rheumatoid arthritis joint damage","The purpose of the RA2-DREAM Challenge is to develop an automated method to quickly and accurately quantify the degree of joint damage associated with rheumatoid arthritis (RA). Based on radiographs of the hands and feet, a novel, automated scoring method could be applied broadly for patient care and research. We challenge participants to develop algorithms to automatically assess joint space narrowing and erosions using a large set of existing radiographs with damage scores generated by visual assessment of images by trained readers using standard protocols. The end result will be a generalizable, publicly available, automated method to generate accurate, reproducible and unbiased RA damage scores to replace the current tedious, expensive, and non-scalable method of scoring by human visual inspection.","","https://www.synapse.org/#!Synapse:syn20545111","completed","intermediate","1","","2019-11-04","2020-05-21","2023-06-23 00:00:00","2023-10-18 00:38:55" -"42","beat-pd","BEAT-PD","Develop mobile sensors to remotely monitor Parkinson's disease","Recent advances in mobile health have demonstrated great potential to leverage sensor-based technologies for quantitative, remote monitoring of health and disease-particularly for diseases affecting motor function such as Parkinson's disease. Such approaches have been rolled out using research-grade wearable sensors and, increasingly, through the use of smartphones and consumer wearables, such as smart watches and fitness trackers. These devices not only provide the ability to measure much more detailed disease phenotypes but also provide the ability to follow patients longitudinally with much higher frequency than is possible through clinical exams. However, the conversion of sensor-based data streams into digital biomarkers is complex and no methodological standards have yet evolved to guide this process. Parkinson's disease (PD) is a neurodegenerative disease that primarily affects the motor system but also exhibits other symptoms. Typical motor symptoms of the disease include...","","https://www.synapse.org/#!Synapse:syn20825169","completed","intermediate","1","","2020-01-13","2020-05-13","2023-06-23 00:00:00","2023-10-14 05:38:45" -"43","ctd2-pancancer-chemosensitivity","CTD2 Pancancer Chemosensitivity","Predict drug sensitivity from cell line gene expression","Over the last two years, the Columbia CTD2 Center developed PANACEA (Pancancer Analysis of Chemical Entity Activity), a comprehensive repertoire of dose response curves and molecular profiles representative of cellular responses to drug perturbations. PANACEA covers a broad spectrum of cellular contexts representative of poor outcome malignancies, including rare ones such as GIST sarcoma and gastroenteropancreatic neuroendocrine tumors (GEP-NETs). PANACEA is uniquely suited to support DREAM Challenges related to the elucidation of drug mechanism of action (MOA), drug sensitivity, and drug synergy. The goal of this Challenge is to foster development and benchmarking of algorithms to predict the sensitivity, as measured by the area under the dose-response curve, of a cell line to a compound based on the baseline transcriptional profiles of the cell line. The drug perturbational RNAseq profiles of 11 cell lines for 30 chosen compounds will be provided to challenge participants, with...","","https://www.synapse.org/#!Synapse:syn21763589","completed","good_for_beginners","1","","2020-04-28","2020-07-27","2023-06-23 00:00:00","2023-10-14 05:38:45" -"44","ehr-dream-challenge-covid-19","EHR DREAM Challenge: COVID-19","Develop tools to predict COVID-19 risk without sharing data","The rapid rise of COVID-19 has challenged healthcare globally. The underlying risks and outcomes of infection are still incompletely characterized even as the world surpasses 4 million infections. Due to the importance and emergent need for better understanding of the condition and the development of patient specific clinical risk scores and early warning tools, we have developed a platform to support testing analytic and machine learning hypotheses on clinical data without data sharing as a platform to rapidly discover and implement approaches for care. We have previously applied this approach in the successful EHR DREAM Challenge focusing on Patient Mortality Prediction with UW Medicine. We have the goal of incorporating machine learning and predictive algorithms into clinical care and COVID-19 is an important and highly urgent challenge. In our first iteration, we will facilitate understanding risk factors that lead to a positive test utilizing electronic health recorded dat...","","https://www.synapse.org/#!Synapse:syn21849255","completed","intermediate","1","https://doi.org/10.1001/jamanetworkopen.2021.24946","2020-04-30","2021-07-01","2023-06-23 00:00:00","2023-11-01 14:57:29" -"45","anti-pd1-response-prediction","Anti-PD1 Response Prediction","Predicting lung cancer response to immuno-oncology therapy","While durable responses and prolonged survival have been demonstrated in some lung cancer patients treated with immuno-oncology (I-O) anti-PD-1 therapy, there remains a need to improve the ability to predict which patients are more likely to receive benefit from treatment with I-O. The goal of this challenge is to leverage clinical and biomarker data to develop predictive models of response to I-O therapy in lung cancer and ultimately gain insights that may facilitate potential novel monotherapies or combinations with I-O.","","https://www.synapse.org/#!Synapse:syn18404605","completed","intermediate","1","","2020-11-17","2021-02-25","2023-06-23 00:00:00","2023-11-02 18:25:16" -"46","brats-2021-challenge","BraTS 2021 Challenge","Developing ML methods to analyze brain tumor MRI scans","Glioblastoma, and diffuse astrocytic glioma with molecular features of glioblastoma (WHO Grade 4 astrocytoma), are the most common and aggressive malignant primary tumor of the central nervous system in adults, with extreme intrinsic heterogeneity in appearance, shape, and histology. Glioblastoma patients have very poor prognosis, and the current standard of care treatment comprises surgery, followed by radiotherapy and chemotherapy. The International Brain Tumor Segmentation (BraTS) Challenges —which have been running since 2012— assess state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans.","","https://www.synapse.org/#!Synapse:syn25829067","completed","advanced","1","","2021-07-07","2021-10-15","2023-06-23 00:00:00","2023-10-14 05:38:48" -"47","cancer-data-registry-nlp","Cancer Data Registry NLP","Predicting lung cancer response to immuno-oncology therapy","A critical bottleneck in translational and clinical research is access to large volumes of high-quality clinical data. While structured data exist in medical EHR systems, a large portion of patient information including patient status, treatments, and outcomes is contained in unstructured text fields. Research in Natural Language Processing (NLP) aims to unlock this hidden and often inaccessible information. However, numerous challenges exist in developing and evaluating NLP methods, much of it centered on having “gold-standard” metrics for evaluation, and access to data that may contain personal health information (PHI). This DREAM Challenge will focus on the development and evaluation of of NLP algorithms that can improve clinical trial matching and recruitment.","","https://www.synapse.org/#!Synapse:syn18361217","upcoming","intermediate","1","","\N","\N","2023-06-23 00:00:00","2023-10-14 05:38:49" -"48","barda-community-challenge-pediatric-covid-19-data-challenge","BARDA Community Challenge - Pediatric COVID-19 Data Challenge","Models to predict severe COVID-19 in children sought","While most children with COVID-19 are asymptomatic or have mild symptoms, healthcare providers have difficulty determining which among their pediatric patients will progress to moderate or severe COVID-19 early in the progression. Some of these patients develop multisystem inflammatory syndrome in children (MIS-C), a life-threatening inflammation of organs and tissues. Methods to distinguish children at risk for severe COVID-19 complications, including conditions such as MIS-C, are needed for earlier interventions to improve pediatric patient outcomes. Multiple HHS divisions are coming together for a data challenge competition that will leverage de-identified electronic health record data to develop, train and validate computational models that can predict severe COVID-19 complications in children, equipping healthcare providers with the information and tools they need to identify pediatric patients at risk.","","https://www.synapse.org/#!Synapse:syn25875374/wiki/611225","completed","intermediate","1","","2021-08-19","2021-12-17","2023-06-23 00:00:00","2023-10-14 05:38:50" -"49","brats-continuous-evaluation","BraTS Continuous Evaluation","Seeking innovations to improve brain tumor diagnosis and treatment","Brain tumors are among the deadliest types of cancer. Specifically, glioblastoma, and diffuse astrocytic glioma with molecular features of glioblastoma (WHO Grade 4 astrocytoma), are the most common and aggressive malignant primary tumor of the central nervous system in adults, with extreme intrinsic heterogeneity in appearance, shape, and histology, with a median survival of approximately 15 months. Brain tumors in general are challenging to diagnose, hard to treat and inherently resistant to conventional therapy because of the challenges in delivering drugs to the brain, as well as the inherent high heterogeneity of these tumors in their radiographic, morphologic, and molecular landscapes. Years of extensive research to improve diagnosis, characterization, and treatment have decreased mortality rates in the U.S by 7% over the past 30 years. Although modest, these research innovations have not translated to improvements in survival for adults and children in low-and middle-income...","","https://www.synapse.org/brats_ce","completed","advanced","1","","2022-01-01","\N","2023-06-23 00:00:00","2023-10-14 05:38:51" -"50","fets-2022","FeTS 2022","Federated Learning Challenge 2022: advancing brain tumor segmentation algorithms","FeTS 2022 focuses on benchmarking methods for federated learning (FL), and particularly i) weight aggregation methods for federated training, and ii) algorithmic generalizability on out-of-sample data based on federated evaluation. In line with its last instance (FeTS 2021-the 1st FL challenge ever organized), FeTS 2022 targets the task of brain tumor segmentation and builds upon i) the centralized dataset of >8,000 clinically-acquired multi-institutional MRI scans (from the RSNA-ASNR-MICCAI BraTS 2021 challenge) with their real-world partitioning, and ii) the collaborative network of remote independent institutions included in a real-world federation. Participants are welcome to compete in either of the two challenge tasks- Task 1 (“Federated Training”) seeks effective weight aggregation methods for the creation of a consensus model given a pre-defined segmentation algorithm for training, while also (optionally) accounting for network outages. Task 2 (“Federated Evaluation”) see...","","https://www.synapse.org/#!Synapse:syn28546456/wiki/617093","completed","advanced","1","","2022-04-08","2022-08-15","2023-06-23 00:00:00","2023-10-18 00:36:14" -"51","random-promotor","Random Promotor","Deciphering gene regulation: training models to predict gene expression patterns","Decoding how gene expression is regulated is critical to understanding disease. Regulatory DNA is decoded by the cell in a process termed “cis-regulatory logic”, where proteins called Transcription Factors (TFs) bind to specific DNA sequences within the genome and work together to produce as output a level of gene expression for downstream adjacent genes. This process is exceedingly complex to model as a large number of parameters is needed to fully describe the process (see Rationale, de Boer et al. 2020; Zeitingler J. 2020). Understanding the cis-regulatory logic of the human genome is an important goal and would provide insight into the origins of many diseases. However, learning models from human data is challenging due to limitations in the diversity of sequences present within the human genome (e.g. extensive repetitive DNA), the vast number of cell types that differ in how they interpret regulatory DNA, limited reporter assay data, and substantial technical biases present ...","","https://www.synapse.org/#!Synapse:syn28469146/wiki/617075","completed","intermediate","1","","2022-05-02","2022-08-07","2023-06-23 00:00:00","2023-10-14 05:38:53" -"52","preterm-birth-prediction-microbiome","Preterm Birth Prediction - Microbiome","Seeking innovations to improve brain tumor diagnosis and treatment","Globally, about 11% of infants every year are born preterm, defined as birth prior to 37 weeks of gestation, totaling nearly 15 million births.(5) In addition to the emotional and financial toll on families, preterm births have higher rates of neonatal death, nearly 1 million deaths each year, and long-term health consequences for some children. Infants born preterm are at risk for a variety of adverse outcomes, such as respiratory illnesses, cerebral palsy, infections, and blindness, with infants born very preterm (i.e., before 32 weeks) at increased risk of these conditions.(6) The ability to accurately predict which women are at a higher risk for preterm birth would help healthcare providers to treat in a timely manner those at higher risk of delivering preterm. Currently available treatments for pregnant women at risk of preterm delivery include corticosteroids for fetal maturation and magnesium sulfate provided prior to 32 weeks to prevent cerebral palsy.(7) There are several...","","https://www.synapse.org/#!Synapse:syn26133770/wiki/612541","completed","advanced","1","","2022-07-19","2022-09-16","2023-06-23 00:00:00","2023-10-14 05:38:54" -"53","finrisk","FINRISK - Heart Failure and Microbiome","Predict incident risk for heart failure in a finnish adults","Cardiovascular diseases are the leading cause of death both in men and women worldwide. Heart failure (HF) is the most common form of heart disease, characterised by the heart's inability to pump a sufficient supply of blood to meet the needs of the body. The lifetime risk of developing HF is roughly 20%, yet, it remains difficult to diagnose due to its and a lack of agreement of diagnostic criteria. As the diagnosis of HF is dependent on ascertainment of clinical histories and appropriate screening of symptomatic individuals, identifying those at risk of HF is essential. This DREAM challenge focuses on the prediction of HF using a combination of gut microbiome and clinical variables. This challenge is designed to predict incident risk for heart failure in a large human population study of Finnish adults, FINRISK 2002 (Borodulin et al., 2018). The FINRISK study has been conducted in Finland to investigate the risk factors for cardiovascular disease every 5 years since 1972. A rand...","","https://www.synapse.org/#!Synapse:syn27130803/wiki/616705","completed","advanced","1","","2022-09-20","2023-01-30","2023-06-23 00:00:00","2023-11-14 19:07:49" -"54","scrna-seq-and-scatac-seq-data-analysis","scRNA-seq and scATAC-seq Data Analysis","Assess computational methods for scrna-seq and scatac-seq analysis","Understanding transcriptional regulation at individual cell resolution is fundamental to understanding complex biological systems such as tissues and organs. Emerging high-throughput sequencing technologies now allow for transcript quantification and chromatin accessibility at the single cell level. These technologies present unique challenges due to inherent data sparsity. Proper signal correction is key to accurate gene expression quantification via scRNA-seq, which propagates into downstream analyses such as differential gene expression analysis and cell-type identification. In the even more sparse scATAC-seq data, the correct identification of informative features is key to assessing cell heterogeneity at the chromatin level. The aims of this challenge will be two-fold- 1) To evaluate computational methods for signal correction and peak identification in scRNA-seq and scATAC-seq, respectively; 2) To assess the impact of these methods on downstream analysis","","https://www.synapse.org/#!Synapse:syn26720920/wiki/615338","completed","advanced","1","","2022-11-29","2023-02-08","2023-06-23 00:00:00","2023-10-14 05:38:56" -"55","cough-diagnostic-algorithm-for-tuberculosis","COugh Diagnostic Algorithm for Tuberculosis","Predict TB status using features extracted from audio of elicited coughs","Tuberculosis (TB), a communicable disease caused by Mycobacterium tuberculosis, is a major cause of ill health and one of the leading causes of death worldwide. Until the COVID-19 pandemic, TB was the leading cause of death from a single infectious agent, ranking even above HIV/AIDS. In 2020, an estimated 9.9 million people fell ill with TB and 1.3 million died of TB worldwide. However, approximately 40% of people with TB were not diagnosed or reported to public health authorities because of challenges in accessing health facilities or failure to be tested or treated when they do. The development of low-cost, non-invasive digital screening tools may improve some of the gaps in diagnosis. As cough is a common symptom of TB, it has the potential to be used as a biomarker for diagnosis of disease. Several previous studies have demonstrated the potential for cough sounds to be used to screen for TB[1-3], though these were typically done in small samples or limited settings. Further de...","","https://www.synapse.org/#!Synapse:syn31472953/wiki/617828","active","advanced","1","","2022-10-16","\N","2023-06-23 00:00:00","2023-12-06 00:58:30" -"56","nih-long-covid-computational-challenge","NIH Long COVID Computational Challenge","Understanding prevalence and outcomes of post-COVID syndrome","The overall prevalence of post-acute sequelae of SARS-CoV-2 (PASC) is currently unknown, but there is growing evidence that more than half of COVID-19 survivors experience at least one symptom of PASC/Long COVID at six months after recovery of the acute illness. Reports also reflect an underlying heterogeneity of symptoms, multi-organ involvement, and persistence of PASC/Long COVID in some patients. Research is ongoing to understand prevalence, duration, and clinical outcomes of PASC/Long COVID. Symptoms of fatigue, cognitive impairment, shortness of breath, and cardiac damage, among others, have been observed in patients who had only mild initial disease. The breadth and complexity of data created in today's health care encounters require advanced analytics to extract meaning from longitudinal data on symptoms, laboratory results, images, functional tests, genomics, mobile health/wearable devices, written notes, electronic health records (EHR), and other relevant data types. Adva...","","https://www.synapse.org/#!Synapse:syn33576900/wiki/618451","completed","intermediate","1","","2022-08-25","2022-12-15","2023-06-23 00:00:00","2023-10-18 00:39:03" -"57","bridge2ai","Bridge2AI","What makes a good color palette?","What makes a good color palette?","","","upcoming","good_for_beginners","1","","\N","\N","2023-06-23 00:00:00","2023-11-20 20:19:26" -"58","rare-x-open-data-science","RARE-X Open Data Science","Unlocking rare disease mysteries through open science collaboration","The Xcelerate RARE-A Rare Disease Open Science Data Challenge is bringing together researchers and data scientists in a collaborative and competitive environment to make the best use of patient-provided data to solve big unknowns in healthcare. The Challenge will launch to researchers in late May 2023, focused on rare pediatric neurodevelopmental diseases.","","https://www.synapse.org/#!Synapse:syn51198355/wiki/621435","completed","intermediate","1","","2023-05-17","2023-08-16","2023-06-23 00:00:00","2023-10-14 05:38:59" -"59","cagi5-regulation-saturation","CAGI5: Regulation saturation","Predicting effects of variants in disease-linked enhancers and promoters","17,500 single nucleotide variants (SNVs) in 5 human disease associated enhancers (including IRF4, IRF6, MYC, SORT1) and 9 promoters (including TERT, LDLR, F9, HBG1) were assessed in a saturation mutagenesis massively parallel reporter assay. Promoters were cloned into a plasmid upstream of a tagged reporter construct, and reporter expression was measured relative to the plasmid DNA to determine the impact of promoter variants. Enhancers were placed upstream of a minimal promoter and assayed similarly. The challenge is to predict the functional effects of these variants in the regulatory regions as measured from the reporter expression.","","https://genomeinterpretation.org/cagi5-regulation-saturation.html","completed","intermediate","\N","","2018-01-04","2018-05-03","2023-06-23 00:00:00","2023-12-06 01:09:41" -"60","cagi5-calm1","CAGI5: CALM1","Predicting effects of calmodulin variants on yeast growth","Calmodulin is a calcium-sensing protein that modulates the activity of a large number of proteins in the cell. It is involved in many cellular processes, and is especially important for neuron and muscle cell function. Variants that affect calmodulin function have been found to be causally associated with cardiac arrhythmias. A large library of calmodulin missense variants was assessed with respect to their effects on protein function using a high-throughput yeast complementation assay. The challenge is to predict the functional effects of these calmodulin variants on competitive growth in a high-throughput yeast complementation assay.","","https://genomeinterpretation.org/cagi5-calm1.html","completed","intermediate","\N","","2017-10-21","2017-12-20","2023-06-23 00:00:00","2023-10-18 15:35:49" -"61","cagi5-pcm1","CAGI5: PCM1","Assessing PCM1 variants' impact on zebrafish ventricle","The PCM1 (Pericentriolar Material 1) gene is a component of centriolar satellites occurring around centrosomes in vertebrate cells. Several studies have implicated PCM1 variants as a risk factor for schizophrenia. Ventricular enlargement is one of the most consistent abnormal structural brain findings in schizophrenia Therefore 38 transgenic human PCM1 missense mutations implicated in schizophrenia were assayed in a zebrafish model to determine their impact on the posterior ventricle area. The challenge is to predict whether variants implicated in schizophrenia impact zebrafish ventricular area.","","https://genomeinterpretation.org/cagi5-pcm1.html","completed","intermediate","\N","","2017-11-09","2018-04-19","2023-06-23 00:00:00","2023-10-18 15:35:49" -"62","cagi5-frataxin","CAGI5: Frataxin","Predicting ΔΔGH20 for Frataxin Variants","Fraxatin is a highly-conserved protein found in prokaryotes and eukaryotes that is required for efficient regulation of cellular iron homeostasis. Humans with a frataxin deficiency have the cardio-and neurodegenerative disorder Friedreich's ataxia. A library of eight missense variants was assessed by near and far-UV circular dichroism and intrinsic fluorescence spectra to determine thermodynamic stability at different concentration of denaturant. These were used to calculate a ΔΔGH20 value, the difference in unfolding free energy (ΔGH20) between the mutant and wild-type proteins for each variant. The challenge is to predict ΔΔGH20 for each frataxin variant.","","https://genomeinterpretation.org/cagi5-frataxin.html","completed","intermediate","\N","","2017-11-30","2018-04-18","2023-06-23 00:00:00","2023-10-18 15:35:50" -"63","cagi5-tpmt","CAGI5: TPMT and p10","Predicting TPMT and PTEN protein stability variants","The gene p10 encodes for PTEN (Phosphatase and TEnsin Homolog), an important secondary messenger molecule promoting cell growth and survival through signaling cascades including those controlled by AKT and mTOR. Thiopurine S-methyl transferase (TPMT) is a key enzyme involved in the metabolism of thiopurine drugs and functions by catalyzing the S-methylation of aromatic and heterocyclic sulfhydryl groups. A library of thousands of PTEN and TPMT mutations was assessed to measure the stability of the variant protein using a multiplexed variant stability profiling (VSP) assay, which detects the presence of EGFP fused to the mutated PTEN and TPMT protein respectively. The stability of the variant protein dictates the abundance of the fusion protein and thus the EGFP level of the cell. The challenge is to predict the effect of each variant on TPMT and/or PTEN protein stability.","","https://genomeinterpretation.org/cagi5-tpmt.html","completed","intermediate","\N","","2017-11-30","2017-12-01","2023-06-23 00:00:00","2023-10-14 05:39:03" -"64","cagi5-annotate-all-missense","CAGI5: Annotate all nonsynonymous variants","Annotate all nonsynonymous variants","dbNSFP describes 810,848,49 possible protein-altering variants in the human genome. The challenge is to predict the functional effect of every such variant. For the vast majority of these missense variants, the functional impact is not currently known, but experimental and clinical evidence are accruing rapidly. Rather than drawing upon a single discrete dataset as typical with CAGI, predictions will be assessed by comparing with experimental or clinical annotations made available after the prediction submission date, on an ongoing basis. if predictors assent, predictions will also incorporated into dbNSFP.","","https://genomeinterpretation.org/cagi5-annotate-all-missense.html","completed","intermediate","\N","","2017-11-30","2018-05-09","2023-06-23 00:00:00","2023-10-14 05:39:04" -"65","cagi5-gaa","CAGI5: GAA","Predict enzyme activity of GAA mutants in Pompe disease","Acid alpha-glucosidase (GAA) is a lysosomal alpha-glucosidase. Some mutations in GAA cause a rare disorder, Pompe disease, (Glycogen Storage Disease II). Rare GAA missense variants found in a human population sample have been assayed for enzymatic activity in transfected cell lysates. The assessment of this challenge will include evaluations that recognize novelty of approach. The challenge is to predict the fractional enzyme activity of each mutant protein compared to the wild-type enzyme.","","https://genomeinterpretation.org/cagi5-gaa.html","completed","intermediate","\N","","2017-11-09","2018-04-25","2023-06-23 00:00:00","2023-10-14 05:39:04" -"66","cagi5-chek2","CAGI5: CHEK2","Estimate CHEK2 gene variant probabilities in Latino breast cancer cases","Variants in the CHEK2 gene are associated with breast cancer. This challenge includes CHEK2 gene variants from approximately 1200 Latino breast cancer cases and 1200 ethnically matched controls. This challenge is to estimate the probability of each gene variant occurring in an individual from the cancer affected cohort.","","https://genomeinterpretation.org/cagi5-chek2.html","completed","intermediate","\N","","2017-12-20","2018-04-24","2023-06-23 00:00:00","2023-10-14 05:39:07" -"67","cagi5-enigma","CAGI5: ENIGMA","Predict cancer risk from BRCA1/2 gene variants","Breast cancer is the most prevalent cancer among women worldwide. The association between germline mutations in the BRCA1 and BRCA2 genes and the development of cancer has been well established. The most common high-risk mutations associated with breast cancer are those in the autosomal dominant breast cancer genes 1 and 2 (BRCA1 and BRCA2). Mutations in these genes are found in 1-3% of breast cancer cases. The challenge is to predict which variants are associated with increased risk for breast cancer.","","https://genomeinterpretation.org/cagi5-enigma.html","completed","intermediate","\N","","2017-12-20","2018-05-01","2023-06-23 00:00:00","2023-10-14 05:39:08" -"68","cagi5-mapsy","CAGI5: MaPSy","Predict the impact of genetic variants on splicing mechanisms","The Massively Parallel Splicing Assay (MaPSy) approach was used to screen 797 reported exonic disease mutations using a mini-gene system, assaying both in vivo via transfection in tissue culture, and in vitro via incubation in cell nuclear extract. The challenge is to predict the degree to which a given variant causes changes in splicing.","","https://genomeinterpretation.org/cagi5-mapsy.html","completed","intermediate","\N","","2017-11-29","2018-05-07","2023-06-23 00:00:00","2023-10-14 05:39:08" -"69","cagi5-vex-seq","CAGI5: Vex-seq","Predict splicing changes from variants in globin gene","A barcoding approach called Variant exon sequencing (Vex-seq) was applied to assess effect of 2,059 natural single nucleotide variants and short indels on splicing of a globin mini-gene construct transfected into HepG2 cells. This is reported as ΔΨ (delta PSI, or Percent Spliced In), between the variant Ψand the reference Ψ. The challenge is to predict ΔΨ for each variant.","","https://genomeinterpretation.org/cagi5-vex-seq.html","completed","intermediate","\N","","2017-12-14","2018-05-02","2023-06-23 00:00:00","2023-10-16 17:51:58" -"70","cagi5-sickkids5","CAGI5: SickKids clinical genomes","Predict genetic disorders from 30 child genomes and phenotypes","This challenge involves 30 children with suspected genetic disorders who were referred for clinical genome sequencing. Predictors are given the 30 genome sequences, and are also provided with the phenotypic descriptions as shared with the diagnostic laboratory. The challenge is to predict what class of disease is associated with each genome, and which genome corresponds to which clinical description. Predictors may additionally identify the diagnostic variant(s) underlying the predictions, and identify predictive secondary variants conferring high risk of other diseases whose phenotypes are not reported in the clinical descriptions.","","https://genomeinterpretation.org/cagi5-sickkids5.html","completed","intermediate","\N","","2017-12-22","2018-04-26","2023-06-23 00:00:00","2023-10-14 05:39:10" -"71","cagi5-intellectual-disability","CAGI5: ID Panel","Predict phenotypes and variants from gene panel sequences","The challenge presented here is to use computational methods to predict a patient's clinical phenotype and the causal variant(s) based on analysis of their gene panel sequence data. Sequence data for 74 genes associated with intellectual disability (ID) and/or Autism spectrum disorders (ASD) from a cohort of 150 patients with a range of neurodevelopmental presentations (ID, autism, epilepsy, etc..) have been made available for this challenge. For each patient, predictors must report the causative variants and which of seven phenotypes are present.","","https://genomeinterpretation.org/cagi5-intellectual-disability.html","completed","intermediate","\N","","2017-12-22","2018-04-30","2023-06-23 00:00:00","2023-10-18 15:28:06" -"72","cagi5-clotting-disease","CAGI5: Clotting disease exomes","Predict venous thromboembolism risk in African Americans","African Americans have a higher incidence of developing venous thromboembolisms (VTE), which includes deep vein thrombosis (DVT) and pulmonary embolism (PE), than people of European ancestry. Participants are provided with exome data and clinical covariates for a cohort of African Americans who have been prescribed Warfarin either because they had experienced a VTE event or had been diagnosed with atrial fibrillation (which predisposes to clotting). The challenge is to distinguish between these conditions. At present, in contrast to European ancestry, there are no genetic methods for anticipating which African Americans are most at risk of a venous thromboembolism, and the results of this challenge may contribute to the development of such tools.","","https://genomeinterpretation.org/cagi5-clotting-disease.html","completed","intermediate","\N","","2017-11-23","2018-04-28","2023-06-23 00:00:00","2023-10-18 15:30:55" -"73","cagi6-sickkids","CAGI6: SickKids clinical genomes and transcriptomes","Identify genes causing rare diseases using transcriptomics","This challenge involves data from 79 children who were referred to The Hospital for Sick Children's (SickKids) Genome Clinic for genome sequencing because of suspected but undiagnosed genetic disorders. Research subjects are consented for sharing of their sequence data and phenotype information with researchers working to understand the molecular causes of rare disease. When a candidate disease variant believed to be related to the phenotype is identified, the variant is adjudicated and confirmed in a clinical setting. In this challenge, transcriptomic and phenotype data from a subset of the “solved” (diagnosed) and “unsolved” SickKids patients will be provided, along with corresponding genomic sequence data. The challenge is to use a transcriptome-driven approach to identify the gene(s) and molecular mechanisms underlying the phenotypic descriptions in each case. For the unsolved cases, prioritized variants from the participating teams will be examined to see if additional diagno...","","https://genomeinterpretation.org/cagi6-sickkids.html","completed","intermediate","1","","2021-08-04","2021-12-31","2023-06-23 00:00:00","2023-11-02 18:02:23" -"74","cagi6-cam","CAGI6: CaM","Predict the impact of point mutations on calmodulin stability","Calmodulin (CaM) is a ubiquitous calcium (Ca2+) sensor protein interacting with more than 200 molecular partners, thereby regulating a variety of biological processes. Missense point mutations in the genes encoding CaM have been associated with ventricular tachycardia and sudden cardiac death. A library encompassing up to 17 point mutations was assessed by far-UV circular dichroism (CD) by measuring melting temperature (Tm) and percentage of unfolding (%unfold) upon thermal denaturation at pH and salt concentration that mimic the physiological conditions. The challenge is to predict: the Tm and %unfold values for isolated CaM variants under Ca2+-saturating conditions (Ca2+-CaM) and in the Ca2+-free (apo) state; whether the point mutation stabilizes or destabilizes the protein (based on Tm and %unfold).","","https://genomeinterpretation.org/cagi6-cam.html","completed","intermediate","1","","2021-06-08","2021-10-11","2023-06-23 00:00:00","2023-10-18 15:32:37" -"75","cami-ii","CAMI II","Assemble and classify microbial genomes in complex samples","CAMI II offers several challenges-an assembly, a genome binning, a taxonomic binning and a taxonomic profiling challenge, on several multi-sample data sets from different environments, including long and short read data. This includes a marine data set and a high-strain diversity data set, with a third data set to follow later. A pathogen detection challenge on a clinical sample is also provided.","","https://www.microbiome-cosi.org/cami/cami/cami2","completed","intermediate","3","","2019-01-14","2021-01-31","2023-06-23 00:00:00","2023-10-17 23:15:00" -"76","camda18-metasub-forensics","CAMDA18-MetaSUB Forensics","Build a metagenomic map of mass-transit systems globally","The MetaSUB International Consortium is building a longitudinal metagenomic map of mass-transit systems and other public spaces across the globe. The consortium maintains a strategic partnership with CAMDA and this year provides data from global City Sampling Days for the first-ever multi-city forensic analyses.","","http://camda2018.bioinf.jku.at/doku.php/contest_dataset#metasub_forensics_challenge","completed","intermediate","\N","","\N","\N","2023-06-23 00:00:00","2023-11-01 20:37:34" -"77","camda18-cmap-drug-safety","CAMDA18-CMap Drug Safety","Predict drug toxicity using cell-based gene expression data","Attrition in drug discovery and development due to safety / toxicity issues remains a significant concern, and there are strong efforts to identify and mitigate risk as early as possible. Drug-induced liver injury (DILI) is one of the primary problems in drug development and regulatory clearance due to the poor performance of existing preclinical models. There is a pressing need to evaluate alternative methods for predicting DILI, with great hopes being placed in modern approaches from statistics and machine learning applied to genome scale profiling data. A critical question thus is if we can better integrate, understand, and exploit information from cell-based screens like the Broad Institute Connectivity Map (CMap, Science 313, Nature Reviews Cancer 7). This CAMDA challenge focuses on understanding or predicting drug induced liver injury in humans from cell-based screens, specifically the CMap gene expression responses of two different cancer cell lines (MCF7 and PC3) to 276 d...","","http://camda2018.bioinf.jku.at/doku.php/contest_dataset#cmap_drug_safety_challenge","completed","intermediate","\N","","\N","\N","2023-06-23 00:00:00","2023-11-01 20:37:35" -"78","camda18-cancer-data-integration","CAMDA18-Cancer Data Integration","Unify data integration approaches for breast cancer and neuroblastoma","Examine the power of data integration in a real-world clinical settings. Many approaches work well on some data-sets yet not on others. We here challenge you to demonstrate a unified single approach to data-integration that matches or outperforms the current state of the art on two different diseases, breast cancer and neuroblastoma. Breast cancer affects about 3 million women every year (McGuire et al, Cancers 7), and this number is growing fast, especially in developed countries. Can you improve on the large Metabric study (Curtis et al., Nature 486, and Dream Challenge, Margolin et al, Sci Transl Med 5)? The cohort is biologically heterogeneous with all five distinct PAM50 breast cancer subtypes represented. Matched profiles for microarray and copy number data as well as clinical information (survival times, multiple prognostic markers, therapy data) are available for about 2,000 patients. Neuroblastoma is the most common extracranial solid tumor in children. The base study com...","","http://camda2018.bioinf.jku.at/doku.php/contest_dataset#cancer_data_integration_challenge","completed","intermediate","\N","","\N","\N","2023-06-23 00:00:00","2023-11-01 20:37:36" -"79","cafa-4","CAFA 4","Assess algorithms for predicting protein function","The goal of the Critical Assessment of Functional Annotation(CAFA) challenge is to evaluate automated protein function prediction algorithms in the task of predicting Gene Ontology and Human Phenotype Ontology terms for a given set of protein sequences. For the GO-based predictions, the evaluation will be carried out for the Molecular Function Ontology, Biological Process Ontology and Cellular Component Ontology. Participants develop protein function prediction algorithms using training protein sequence data and submit their predictions on target protein sequence data.","","https://www.biofunctionprediction.org/cafa/","completed","intermediate","1","","2019-10-21","2020-02-12","2023-06-23 00:00:00","2023-10-14 05:39:20" -"80","casp13","CASP13","CASP assesses protein structure prediction methods","CASP (Critical Assessment of Structure Prediction) is a community wide experiment to determine and advance the state of the art in modeling protein structure from amino acid sequence. Every two years, participants are invited to submit models for a set of proteins for which the experimental structures are not yet public. Independent assessors then compare the models with experiment. Assessments and results are published in a special issue of the journal PROTEINS. In the most recent CASP round, CASP12, nearly 100 groups from around the world submitted more than 50,000 models on 82 modeling targets","","https://predictioncenter.org/casp13/index.cgi","completed","intermediate","\N","","2018-04-18","2018-08-20","2023-06-23 00:00:00","2023-10-17 22:52:29" -"81","casp14","CASP14","Assess progress in protein structure prediction","CASP (Critical Assessment of Structure Prediction) is a community wide experiment to determine and advance the state of the art in modeling protein structure from amino acid sequence. Every two years, participants are invited to submit models for a set of proteins for which the experimental structures are not yet public. Independent assessors then compare the models with experiment. Assessments and results are published in a special issue of the journal PROTEINS. In the most recent CASP round, CASP14, nearly 100 groups from around the world submitted more than 67,000 models on 90 modeling targets.","","https://predictioncenter.org/casp14/index.cgi","completed","intermediate","\N","","2020-05-04","2020-09-07","2023-06-23 00:00:00","2023-10-17 22:47:26" -"82","cfsan-pathogen-detection","CFSAN Pathogen Detection","Rapidly identify food sources of outbreaks","In the U.S. alone, one in six individuals, an estimated 48 million people, fall prey to foodborne illness, resulting in 128,000 hospitalizations and 3,000 deaths per year. Economic burdens are estimated cumulatively at $152 billion dollars annually, including $39 billion due to contamination of fresh and processed produce. One longstanding problem is the ability to rapidly identify the food-source associated with the outbreak being investigated. The faster an outbreak is identified and the increased certainty that a given source (e.g., papayas from Mexico) and patients are linked, the faster the outbreak can be stopped, limiting morbidity and mortality. In the last few years, the application of next-generation sequencing (NGS) technology for whole genome sequencing (WGS) of foodborne pathogens has revolutionized food pathogen outbreak surveillance. WGS of foodborne pathogens enables high-resolution identification of pathogens isolated from food or environmental samples. These pat...","","https://precision.fda.gov/challenges/2","completed","intermediate","6","","2018-02-15","2018-04-26","2023-06-23 00:00:00","2023-10-14 05:39:23" -"83","cdrh-biothreat","CDRH Biothreat","Identify infectious diseases from clinical samples using sequencing technology","Many infectious diseases have similar signs and symptoms, making it challenging for healthcare providers to identify the disease-causing agent. Clinical samples are often tested by multiple test methods to help reveal the microbe that is causing the infectious disease. The results of these test methods can help healthcare professionals determine the best treatment for patients. Today, High-Throughput Sequencing (HTS) or Next Generation Sequencing (NGS) technology has the capability, as a single test, to accomplish what might have required several different tests in the past. NGS technology may allow the diagnosis of infections without prior knowledge of disease(s) cause. NGS technology can potentially reveal the presence of all microorganisms in a patient sample. Using infectious disease NGS (ID-NGS) technology, each microbial pathogen may be identified by its unique genomic fingerprint. The vision of ID-NGS technology is to further improve patient care by delivering diagnostics ...","","https://precision.fda.gov/challenges/3","completed","intermediate","6","","2018-08-03","2018-10-18","2023-06-23 00:00:00","2023-10-14 05:39:24" -"84","multi-omics-enabled-sample-mislabeling-correction","Multi-omics Enabled Sample Mislabeling Correction","Identify and correct sample and data mislabeling events","In biomedical research, sample mislabeling (accidental swapping of patient samples) or data mislabeling (accidental swapping of patient omics data) has been a long-standing problem that contributes to irreproducible results and invalid conclusions. These problems are particularly prevalent in large scale multi-omics studies, in which multiple different omics experiments are carried out at different time periods and/or in different labs. Human errors could arise during sample transferring, sample tracking, large-scale data generation, and data sharing/management. Thus, there is a pressing need to identify and correct sample and data mislabeling events to ensure the right data for the right patient. Simultaneous use of multiple types of omics platforms to characterize a large set of biological samples, as utilized in The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC) projects, has been demonstrated as a powerful approach to understanding the ...","","https://precision.fda.gov/challenges/4","completed","intermediate","6","https://doi.org/10.1038/s41591-018-0180-x","2018-09-24","2018-12-19","2023-06-23 00:00:00","2023-11-14 19:07:58" -"85","biocompute-object-app-a-thon","BioCompute Object App-a-thon","Seeking standards for reproducible bioinformatics analysis","Like scientific laboratory experiments, bioinformatics analysis results and interpretation are faced with reproducibility challenges due to the variability in multiple computational parameters, including input format, prerequisites, platform dependencies, and more. Even small changes in these computational parameters may have a large impact on the results and carry big implications for their scientific validity. Because there are currently no standardized schemas for reporting computational scientific workflows and parameters together with their results, the ways in which these workflows are communicated is highly variable, incomplete, and difficult or impossible to reproduce. The US Food and Drug Administration (FDA) High Performance Virtual Environment (HIVE) group and George Washington University (GW) have partnered to establish a framework for community-based standards development and harmonization of high-throughput sequencing (HTS) computations and data formats based arou...","","https://precision.fda.gov/challenges/7/","completed","intermediate","6","https://doi.org/10.1101/2020.11.02.365528","2019-05-14","2019-10-18","2023-06-23 00:00:00","2023-10-14 05:39:25" -"86","brain-cancer-predictive-modeling-and-biomarker-discovery","Brain Cancer Predictive Modeling and Biomarker Discovery","Seeking novel biomarkers to advance precision medicine for brain tumors","An estimated 86,970 new cases of primary brain and other central nervous system tumors are expected to be diagnosed in the US in 2019. Brain tumors comprise a particularly deadly subset of all cancers due to limited treatment options and the high cost of care. Only a few prognostic and predictive markers have been successfully implemented in the clinic so far for gliomas, the most common malignant brain tumor type. These markers include MGMT promoter methylation in high-grade astrocytomas, co-deletion of 1p/19q in oligodendrogliomas, and mutations in IDH1 or IDH2 genes (Staedtke et al. 2016). There remains significant potential for identifying new clinical biomarkers in gliomas. Clinical investigators at Georgetown University are seeking to advance precision medicine techniques for the prognosis and treatment of brain tumors through the identification of novel multi-omics biomarkers. In support of this goal, precisionFDA and the Georgetown Lombardi Comprehensive Cancer Center and ...","","https://precision.fda.gov/challenges/8/","completed","advanced","6","","2019-11-01","2020-02-14","2023-06-23 00:00:00","2023-10-14 05:39:25" -"87","gaining-new-insights-by-detecting-adverse-event-anomalies","Gaining New Insights by Detecting Adverse Event Anomalies","Seeking algorithms to detect adverse events in FDA data","The Food and Drug Administration (FDA) calls on the public to develop computational algorithms for automatic detection of adverse event anomalies using publicly available data.","","https://precision.fda.gov/challenges/9/","completed","intermediate","6","","2020-01-17","2020-05-18","2023-06-23 00:00:00","2023-10-14 05:39:27" -"88","calling-variants-in-difficult-to-map-regions","Calling Variants in Difficult-to-Map Regions","Precision benchmarking: evaluating variant calling in complex genomic regions","This challenge calls on the public to assess variant calling pipeline performance on a common frame of reference, with a focus on benchmarking in difficult-to-map regions, segmental duplications, and the Major Histocompatibility Complex (MHC).","","https://precision.fda.gov/challenges/10/","completed","intermediate","6","https://doi.org/10.1016/j.xgen.2022.100129","2020-05-01","2020-06-15","2023-06-23 00:00:00","2023-10-14 05:39:28" -"89","vha-innovation-ecosystem-and-covid-19-risk-factor-modeling","VHA Innovation Ecosystem and COVID-19 Risk Factor Modeling","AI for COVID-19: predicting health outcomes in the veteran population","The novel coronavirus disease 2019 (COVID-19) is a respiratory disease caused by a new type of coronavirus, known as “severe acute respiratory syndrome coronavirus 2,” or SARS-CoV-2. On March 11, 2020, the World Health Organization (WHO) declared the outbreak a global pandemic. As of Monday, June 1, the Johns Hopkins University COVID-19 dashboard reports over 6.21 million total confirmed cases worldwide, including over 1.79 million cases in the United States. Although most people have mild to moderate symptoms, the disease can cause severe medical complications leading to death in some people. The Centers for Disease Control and Prevention (CDC) have identified several groups at elevated risk for severe illness, including people 65 years and older, individuals living in nursing homes or long term care facilities, and those with serious underlying medical conditions, such as severe obesity, diabetes, chronic lung disease or moderate to severe asthma, chronic kidney or liver disease...","","https://precision.fda.gov/challenges/11/","completed","intermediate","6","","2020-06-02","2020-07-03","2023-06-23 00:00:00","2023-10-14 05:39:28" -"90","covid-19-precision-immunology-app-a-thon","COVID-19 Precision Immunology App-a-thon","Seeking insights on COVID-19 pathophysiology to enable effective strategies","The novel coronavirus disease 2019 (COVID-19), a respiratory disease caused by a new type of coronavirus, known as “severe acute respiratory syndrome coronavirus 2” or SARS-CoV-2, was declared a global pandemic by the World Health Organization on March 11, 2020. To date, the Johns Hopkins University COVID-19 dashboard reports over 62 million confirmed cases worldwide, with a wide range of disease severity from asymptomatic to deaths (over 1.46 million). To effectively combat the widespread transmission of COVID-19 infection and save lives especially of those vulnerable individuals, it is imperative to better understand its pathophysiology to enable effective diagnosis, prognosis and treatment strategies using rapidly shared data.","","https://precision.fda.gov/challenges/12/","completed","intermediate","6","","2020-11-30","2021-01-29","2023-06-23 00:00:00","2023-10-14 05:39:29" -"91","smarter-food-safety-low-cost-tech-enabled-traceability","Smarter Food Safety Low Cost Tech-Enabled Traceability","Seeking affordable tech solutions for food traceability","The motivation is tapping into new technologies and integrating data streams will help to advance the widespread, consistent implementation of traceability systems across the food industry. However, the affordability of such technologies, particularly for smaller companies, can be a barrier to implementing tech-enabled traceability systems. FDA's New Era of Smarter Food Safety initiative strives to work with stakeholders to explore low-cost or no-cost options so that our approaches are inclusive of and viable for human and animal food operations of all sizes. Democratizing the benefits of digitizing data will allow the entire food system to move more rapidly towards digital traceability systems. The primary goal is to encourage stakeholders, including technology providers, public health advocates, entrepreneurs, and innovators from all disciplines and around the world, to develop traceability hardware, software, or data analytics platforms that are low-cost or no-cost to the en...","","https://precision.fda.gov/challenges/13","completed","intermediate","6","","2021-06-01","2021-07-30","2023-06-23 00:00:00","2023-10-17 23:05:49" -"92","tumor-mutational-burden-tmb-challenge-phase-1","Tumor Mutational Burden (TMB) Challenge Phase 1","Standardize tumor mutational burden (TMB) calculation in cancer research","Tumor mutational burden (TMB) is generally defined as the number of mutations detected in a patient's tumor sample per megabase of DNA sequenced. However different algorithms use different methods for calculating TMB. Mutations in genes in tumor cells may lead to the creation of neoantigens, which have the potential to activate an immune system response against the tumor, and the likelihood of an immune system response may increase with the number of mutations. Thus, TMB is a biomarker for some immunotherapy drugs, called immune checkpoint inhibitors, such as those that target the PD-1 and PD-L1 pathways (Chan et al., 2019). An outstanding problem is the lack of standardization for TMB calculation and reporting between different assays. To address this problem, the Friends of Cancer Research convened a working group of industry and regulatory stakeholders to develop guidance and tools for TMB harmonization. Results from the first phase of this effort were presented at AACR 2020 (...","","https://precision.fda.gov/challenges/17","completed","advanced","6","","2021-06-21","2021-09-13","2023-06-23 00:00:00","2023-11-02 18:28:46" -"93","kits21","KiTS21","Contest seeks best kidney tumor segmentation system","The 2021 Kidney and Kidney Tumor Segmentation challenge (abbreviated KiTS21) is a competition in which teams compete to develop the best system for automatic semantic segmentation of renal tumors and surrounding anatomy. Kidney cancer is one of the most common malignancies in adults around the world, and its incidence is thought to be increasing [1]. Fortunately, most kidney tumors are discovered early while they're still localized and operable. However, there are important questions concerning management of localized kidney tumors that remain unanswered [2], and metastatic renal cancer remains almost uniformly fatal [3]. Kidney tumors are notorious for their conspicuous appearance in computed tomography (CT) imaging, and this has enabled important work by radiologists and surgeons to study the relationship between tumor size, shape, and appearance and its prospects for treatment [4,5,6]. It's laborious work, however, and it relies on assessments that are often subjective and impr...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/594/rendering_dimmed.png","https://kits21.grand-challenge.org/","completed","advanced","5","","2021-08-23","2021-09-17","2023-06-23 00:00:00","2023-11-28 00:32:11" -"94","realnoisemri","RealNoiseMRI","Brain MRI reconstruction challenge with realistic noise","In recent years, there is a growing focus on the application of fast magnetic resonance imaging (MRI) based on prior knowledge. In the 1980s and 2000s the community used either purely mathematical models such as the partial Fourier transform or solutions derived through advanced engineering such as parallel imaging to speed up MRI acquisition. Since the mid-2000's, compressed sensing and artificial intelligence have been employed to speed up MRI acquisition. These newer methods rely on under sampling the data acquired in Fourier (aka k-) space and then interpolating or augmenting k-space data based on training data content. One of the underlying problems for the development of fast imaging techniques, that just as in e.g. [1], it is common to use a fully sampled image as ground truth and then under sample it in k-space in order to simulate under sampled data. The problem with this approach is that in cases were the under sampled data is corrupted, through e.g. motion, this under s...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/597/Logo_Challenge.png","https://realnoisemri.grand-challenge.org/","completed","intermediate","5","","2021-09-21","2021-12-06","2023-06-23 00:00:00","2023-11-27 20:40:05" -"95","deep-generative-model-challenge-for-da-in-surgery","Deep Generative Model Challenge for DA in Surgery","Challenge aims to adapt algorithms from simulation to mitral valve surgery","Mitral regurgitation (MR) is the second most frequent indication for valve surgery in Europe and may occur for organic or functional causes [1]. Mitral valve repair, although considerably more difficult, is prefered over mitral valve replacement, since the native tissue of the valve is preserved. It is a complex on-pump heart surgery, often conducted only by a handful of surgeons in high-volume centers. Minimally invasive procedures, which are performed with endoscopic video recordings, became more and more popular in recent years. However, data availability and data privacy concerns are still an issue for the development of automatic scene analysis algorithms. The AdaptOR challenge aims to address these issues by formulating a domain adaptation problem from simulation to surgery. We provide a smaller number of datasets from real surgeries, and a larger number of annotated recordings of training and planning sessions from a physical mitral valve simulator. The goal is to reduce th...","","https://adaptor2021.github.io/","completed","intermediate","1","","2021-04-01","2021-07-16","2023-06-23 00:00:00","2023-10-14 05:39:34" -"96","aimdatathon","AIM Datathon 2020","AI in Medicine (AIM) Datathon 2020","Join the AI in Medicine ( AIM ) Datathon 2020","","https://www.kaggle.com/competitions/aimdatathon","completed","intermediate","8","","2020-11-09","2020-11-22","2023-06-23 00:00:00","2023-11-15 22:43:19" -"97","opc-recurrence","Oropharynx Cancer (OPC) Radiomics Challenge :: Local Recurrence Prediction","Determine whether a tumor will be controlled by definitive radiation therapy","Determine from CT data whether a tumor will be controlled by definitive radiation therapy.","","https://www.kaggle.com/competitions/opc-recurrence","completed","intermediate","8","","2016-07-26","2016-09-12","2023-06-23 00:00:00","2023-11-14 19:11:07" -"98","oropharynx-radiomics-hpv","Oropharynx Cancer (OPC) Radiomics Challenge :: Human Papilloma Virus (HPV) Status Prediction","Predict hpv phenotype of oropharynx tumors; compare to ground truth data","Predict from CT data the HPV phenotype of oropharynx tumors; compare to ground-truth results previously obtained by p16 or HPV testing.","","https://www.kaggle.com/competitions/oropharynx-radiomics-hpv","completed","intermediate","8","","2016-07-26","2016-09-12","2023-06-23 00:00:00","2023-11-14 19:11:17" -"99","data-science-bowl-2017","Data Science Bowl 2017","Can you improve lung cancer detection?","Can you improve lung cancer detection?","","https://www.kaggle.com/competitions/data-science-bowl-2017","completed","intermediate","8","","2017-01-12","2017-04-12","2023-06-23 00:00:00","2023-10-14 05:39:38" -"100","predict-impact-of-air-quality-on-death-rates","Predict impact of air quality on mortality rates","Predict CVD and cancer caused mortality rates in England using air quality data","Predict CVD and cancer caused mortality rates in England using air quality data available from Copernicus Atmosphere Monitoring Service","","https://www.kaggle.com/competitions/predict-impact-of-air-quality-on-death-rates","completed","intermediate","8","","2017-02-13","2017-05-05","2023-06-23 00:00:00","2023-10-14 05:39:38" -"101","intel-mobileodt-cervical-cancer-screening","Intel & MobileODT Cervical Cancer Screening","Which cancer treatment will be most effective?","Which cancer treatment will be most effective?","","https://www.kaggle.com/competitions/intel-mobileodt-cervical-cancer-screening","completed","intermediate","8","","2017-03-15","2017-06-21","2023-06-23 00:00:00","2023-10-14 05:39:39" -"102","msk-redefining-cancer-treatment","Personalized Medicine-Redefining Cancer Treatment","Predict the effect of genetic variants to enable personalized medicine","Predict the effect of Genetic Variants to enable Personalized Medicine","","https://www.kaggle.com/competitions/msk-redefining-cancer-treatment","completed","intermediate","8","","2017-06-26","2017-10-02","2023-06-23 00:00:00","2023-11-02 18:32:51" -"103","mubravo","Predicting Cancer Diagnosis","Bravo's machine learning competition!","Bravo's machine learning competition!","","https://www.kaggle.com/competitions/mubravo","completed","intermediate","8","","2018-07-31","2018-08-13","2023-06-23 00:00:00","2023-10-14 05:39:41" -"104","histopathologic-cancer-detection","Histopathologic Cancer Detection","Identify metastatic tissue in histopathologic scans of lymph node sections","Identify metastatic tissue in histopathologic scans of lymph node sections","","https://www.kaggle.com/competitions/histopathologic-cancer-detection","completed","intermediate","8","","2018-11-16","2019-03-30","2023-06-23 00:00:00","2023-10-14 05:39:41" -"105","tjml1920-decision-trees","TJML 2019-20 Breast Cancer Detection Competition","Use a decision tree to identify malignant breast cancer tumors","Use a decision tree to identify malignant breast cancer tumors","","https://www.kaggle.com/competitions/tjml1920-decision-trees","completed","intermediate","8","","2019-09-22","2019-10-16","2023-06-23 00:00:00","2023-10-14 05:39:42" -"106","prostate-cancer-grade-assessment","Prostate cANcer graDe Assessment (PANDA) Challenge","Prostate cancer diagnosis using the gleason grading system","Prostate cancer diagnosis using the Gleason grading system","","https://www.kaggle.com/competitions/prostate-cancer-grade-assessment","completed","intermediate","8","","2020-04-21","2020-07-22","2023-06-23 00:00:00","2023-10-14 05:39:43" -"107","breast-cancer","Breast Cancer","Use cell nuclei categories to predict breast cancer tumor","Use cell nuclei categories to predict breast cancer tumor.","","https://www.kaggle.com/competitions/breast-cancer","completed","intermediate","8","","2020-08-12","2020-08-13","2023-06-23 00:00:00","2023-10-14 05:39:43" -"108","breast-cancer-detection","Breast Cancer Detection","Breast cancer detection","breast cancer detection","","https://www.kaggle.com/competitions/breast-cancer-detection","completed","intermediate","8","","2020-09-25","2020-12-31","2023-06-23 00:00:00","2023-10-14 05:39:44" -"109","hrpred","Prediction of High Risk Patients","Classification of high and low risk cancer patients","Classification of high and low risk cancer patients","","https://www.kaggle.com/competitions/hrpred","completed","intermediate","8","","2020-11-25","2020-12-05","2023-06-23 00:00:00","2023-10-14 05:39:44" -"110","ml4moleng-cancer","MIT ML4MolEng-Predicting Cancer Progression","MIT 3.100, 10.402, 20.301 In class ML competition (Spring 2021)","MIT 3.100, 10.402, 20.301 In class ML competition (Spring 2021)","","https://www.kaggle.com/competitions/ml4moleng-cancer","completed","intermediate","8","","2021-05-06","2021-05-21","2023-06-23 00:00:00","2023-11-16 18:41:14" -"111","uw-madison-gi-tract-image-segmentation","UW-Madison GI Tract Image Segmentation","Track healthy organs in medical scans to improve cancer treatment","Track healthy organs in medical scans to improve cancer treatment","","https://www.kaggle.com/competitions/uw-madison-gi-tract-image-segmentation","completed","intermediate","8","","2022-04-14","2022-07-14","2023-06-23 00:00:00","2023-10-14 05:39:46" -"112","rsna-miccai-brain-tumor-radiogenomic-classification","RSNA-MICCAI Brain Tumor Radiogenomic Classification","Predict the status of a genetic biomarker important for brain cancer treatment","The Brain Tumor Segmentation (BraTS) challenge celebrates its 10th anniversary, and this year is jointly organized by the Radiological Society of North America (RSNA), the American Society of Neuroradiology (ASNR), and the Medical Image Computing and Computer Assisted Interventions (MICCAI) society. The RSNA-ASNR-MICCAI BraTS 2021 challenge utilizes multi-institutional pre-operative baseline multi-parametric magnetic resonance imaging (mpMRI) scans, and focuses on the evaluation of state-of-the-art methods for (Task 1) the segmentation of intrinsically heterogeneous brain glioblastoma sub-regions in mpMRI scans. Furthemore, this BraTS 2021 challenge also focuses on the evaluation of (Task 2) classification methods to predict the MGMT promoter methylation status. Participants are free to choose whether they want to focus only on one or both tasks.","","https://www.kaggle.com/competitions/rsna-miccai-brain-tumor-radiogenomic-classification","completed","advanced","8","","2021-07-13","2021-10-15","2023-06-23 00:00:00","2023-10-14 05:39:46" -"113","breastcancer","Breast Cancer - Beginners ML","Beginners hands-on experience with ML basics","Beginners hands-on experience with ML basics","","https://www.kaggle.com/competitions/breastcancer","completed","intermediate","8","","2021-12-21","2022-02-12","2023-06-23 00:00:00","2023-10-18 21:18:15" -"114","ml-olympiad-health-and-education","ML Olympiad -Let's Fight lung cancer","Use your ml expertise to help us step another step toward defeating cancer","Use your ML expertise to help us step another step toward defeating cancer [ Starts on the 14th February ]","","https://www.kaggle.com/competitions/ml-olympiad-health-and-education","completed","intermediate","8","","2022-01-31","2022-03-19","2023-06-23 00:00:00","2023-11-15 18:45:55" -"115","cs98-22-dl-task1","CS98X-22-DL-Task1","This competition is related to task 1 in coursework-breast cancer classification","This competition is related to Task 1 in coursework-breast cancer classification","","https://www.kaggle.com/competitions/CS98-22-DL-Task1","completed","intermediate","8","","2022-02-28","2022-04-11","2023-06-23 00:00:00","2023-10-14 05:39:48" -"116","parasitedetection-iiitb2019","Parasite detection","Detect if cell image has parasite or is uninfected","detect if cell image has parasite or is uninfected","","https://www.kaggle.com/competitions/parasitedetection-iiitb2019","completed","intermediate","8","","2019-10-13","2019-11-25","2023-06-23 00:00:00","2023-10-14 05:39:49" -"117","hpa-single-cell-image-classification","Human Protein Atlas -Single Cell Classification","Find individual human cell differences in microscope images","Find individual human cell differences in microscope images","","https://www.kaggle.com/competitions/hpa-single-cell-image-classification","completed","intermediate","8","","2021-01-26","2021-05-11","2023-06-23 00:00:00","2023-10-14 05:39:50" -"118","stem-cell-predcition","Stem Cell Predcition","Classify stem and non-stem cells using RNA-seq data","Classify stem and non-stem cells using RNA-seq data","","https://www.kaggle.com/competitions/stem-cell-predcition","completed","intermediate","8","","2021-04-01","2021-07-01","2023-06-23 00:00:00","2023-10-14 05:39:50" -"119","sartorius-cell-instance-segmentation","Sartorius - Cell Instance Segmentation","Detect single neuronal cells in microscopy images","In this competition, you’ll detect and delineate distinct objects of interest in biological images depicting neuronal cell types commonly used in the study of neurological disorders. More specifically, you'll use phase contrast microscopy images to train and test your model for instance segmentation of neuronal cells. Successful models will do this with a high level of accuracy. If successful, you'll help further research in neurobiology thanks to the collection of robust quantitative data. Researchers may be able to use this to more easily measure the effects of disease and treatment conditions on neuronal cells. As a result, new drugs could be discovered to treat the millions of people with these leading causes of death and disability.","","https://www.kaggle.com/competitions/sartorius-cell-instance-segmentation","completed","intermediate","8","","2021-10-14","2021-12-30","2023-06-23 00:00:00","2023-10-16 18:05:17" -"120","pvelad","Photovoltaic cell anomaly detection","Photovoltaic cell anomaly detection","Hosted by Hebei University of Technology (AIHebut research group) and Beihang University (NAVE research group)","","https://www.kaggle.com/competitions/pvelad","completed","intermediate","8","","2022-03-15","2022-07-30","2023-06-23 00:00:00","2023-10-14 05:39:51" -"121","blood-mnist","Blood-MNIST","Classifying blood cell types using weights and biases","Classifying blood cell types using Weights and Biases","","https://www.kaggle.com/competitions/blood-mnist","completed","intermediate","8","","2022-03-19","2022-03-19","2023-06-23 00:00:00","2023-11-14 20:33:37" -"122","insilicomolhack","MolHack","Apply deep learning to speedup drug validation","Apply deep learning to speedup drug validation","","https://www.kaggle.com/competitions/insilicomolhack","completed","intermediate","8","","2018-04-02","2018-05-25","2023-06-23 00:00:00","2023-10-14 05:39:53" -"123","codata2019challenge","Cell Response Classification","From recorded timeseries of many cells in a well, predict which drug treatme","From recorded timeseries of many cells in a well, predict which drug treatment has been applied","","https://www.kaggle.com/competitions/codata2019challenge","completed","intermediate","8","","2019-04-08","2019-05-07","2023-06-23 00:00:00","2023-10-14 05:39:53" -"124","drug-solubility-challenge","Drug solubility challenge","Crucial role of solubility in drug formulation for optimal efficacy","Solubility is vital to achieve desired concentration of drug for anticipated pharmacological response.","","https://www.kaggle.com/competitions/drug-solubility-challenge","completed","intermediate","8","","2019-05-18","2019-10-18","2023-06-23 00:00:00","2023-10-14 05:39:54" -"125","kinase-inhibition-challenge","Kinase inhibition challenge","Unlocking the therapeutic potential of protein kinases: big data insights","Protein kinases have become a major class of drug targets, accumulating a huge amount of data","","https://www.kaggle.com/competitions/kinase-inhibition-challenge","completed","intermediate","8","","2019-05-20","2019-12-28","2023-06-23 00:00:00","2023-10-14 05:39:54" -"126","ai-drug-discovery","AI Drug Discovery Workshop and Coding Challenge","Fostering core AI programming proficiency for drug discovery advancements","Developing Fundamental AI Programming Skills for Drug Discovery","","https://www.kaggle.com/competitions/ai-drug-discovery","completed","intermediate","8","","2021-11-12","2021-12-31","2023-06-23 00:00:00","2023-11-02 18:41:48" -"127","protein-compound-affinity","Structure-free protein-ligand affinity prediction - Task 1 Fitting","Developing new AI models for drug discovery","Developing new AI models for drug discovery, main portal (Task-1 fitting)","","https://www.kaggle.com/competitions/protein-compound-affinity","completed","intermediate","8","","2021-12-06","2021-12-31","2023-06-23 00:00:00","2023-11-14 20:34:30" -"128","cisc873-dm-f21-a5","CISC873-DM-F21-A5","Anti-cancer drug activity prediction","Anti-Cancer Drug Activity Prediction","","https://www.kaggle.com/competitions/cisc873-dm-f21-a5","completed","intermediate","8","","2021-11-26","2021-12-10","2023-06-23 00:00:00","2023-10-14 05:39:56" -"129","pro-lig-aff-task2-mse","Structure-free protein-ligand affinity prediction - Task 2 Fitting","Developing new AI models for drug discovery","Developing new AI models for drug discovery (Task-2 fitting)","","https://www.kaggle.com/competitions/pro-lig-aff-task2-mse","completed","intermediate","8","","2021-12-08","2021-12-31","2023-06-23 00:00:00","2023-11-15 22:42:37" -"130","pro-lig-aff-task1-pearsonr","Structure-free protein-ligand affinity prediction - Task 1 Ranking","Developing new AI models for drug discovery","Developing new AI models for drug discovery (Task-1 ranking)","","https://www.kaggle.com/competitions/pro-lig-aff-task1-pearsonr","completed","intermediate","8","","2021-12-08","2021-12-31","2023-06-23 00:00:00","2023-11-15 22:42:40" -"131","pro-lig-aff-task2-pearsonr","Structure-free protein-ligand affinity prediction - Task 2 Ranking","Developing new AI models for drug discovery","Developing new AI models for drug discovery (Task-2 ranking)","","https://www.kaggle.com/competitions/pro-lig-aff-task2-pearsonr","completed","intermediate","8","","2021-12-08","2021-12-31","2023-06-23 00:00:00","2023-11-15 22:42:43" -"132","pro-lig-aff-task3-spearmanr","Structure-free protein-ligand affinity prediction - Task 3 Ranking","Developing new AI models for drug discovery","Developing new AI models for drug discovery (Task-3 ranking)","","https://www.kaggle.com/competitions/pro-lig-aff-task3-spearmanr","completed","intermediate","8","","2021-12-08","2021-12-31","2023-06-23 00:00:00","2023-11-15 22:42:44" -"133","hhp","Heritage Health Prize","Identify patients who will be admitted to a hospital within the next year","Identify patients who will be admitted to a hospital within the next year using historical claims data. (Enter by 06-59-59 UTC Oct 4 2012)","","https://www.kaggle.com/competitions/hhp","completed","intermediate","8","","2011-04-04","2013-04-04","2023-06-23 00:00:00","2023-11-14 19:11:25" -"134","pf2012","Practice Fusion Analyze This! 2012 - Prediction Challenge","Propose innovative predictive modeling challenges","Start digging into electronic health records and submit your ideas for the most promising, impactful or interesting predictive modeling competitions","","https://www.kaggle.com/competitions/pf2012","completed","intermediate","8","","2012-06-07","2012-06-30","2023-06-23 00:00:00","2023-11-14 19:11:32" -"135","pf2012-at","Practice Fusion Analyze This! 2012 - Open Challenge","Propose innovative predictive modeling challenges","Start digging into electronic health records and submit your creative, insightful, and visually striking analyses.","","https://www.kaggle.com/competitions/pf2012-at","completed","intermediate","8","","2012-06-07","2012-09-10","2023-06-23 00:00:00","2023-11-14 19:21:00" -"136","seizure-detection","UPenn and Mayo Clinic's Seizure Detection Challenge","Detect seizures in intracranial EEG recordings","Detect seizures in intracranial EEG recordings","","https://www.kaggle.com/competitions/seizure-detection","completed","intermediate","8","","2014-05-19","2014-08-19","2023-06-23 00:00:00","2023-10-14 05:40:02" -"137","seizure-prediction","American Epilepsy Society Seizure Prediction Challenge","Predict seizures in intracranial EEG recordings","Predict seizures in intracranial EEG recordings","","https://www.kaggle.com/competitions/seizure-prediction","completed","intermediate","8","","2014-08-25","2014-11-17","2023-06-23 00:00:00","2023-10-14 05:40:03" -"138","deephealth-1","Deep Health - alcohol","Find correlations and patterns with medical data","Find Correlations and patterns with Medical data","","https://www.kaggle.com/competitions/deephealth-1","completed","intermediate","8","","2017-02-13","2017-02-19","2023-06-23 00:00:00","2023-10-16 18:14:48" -"139","deep-health-3","Deep Health - Diabetes 2","Deep health hackathon: predicting future diabetes occurrences challenge","This competition is for those attending the Deep Health Hackathon. Predict the next occurrence of diabetes","","https://www.kaggle.com/competitions/deep-health-3","completed","intermediate","8","","2017-02-15","2017-02-19","2023-06-23 00:00:00","2023-10-16 18:14:50" -"140","d012554-2021","D012554 - 2021","Classify the health of a fetus using CTG data","Classify the health of a fetus using CTG data","","https://www.kaggle.com/competitions/d012554-2021","completed","intermediate","8","","2021-04-11","2021-05-09","2023-06-23 00:00:00","2023-10-16 18:15:04" -"141","idao-2022-bootcamp-insomnia","IDAO 2022. ML Bootcamp - Insomnia","Predict sleep disorder on given human health data","Predict sleep disorder on given human health data","","https://www.kaggle.com/competitions/idao-2022-bootcamp-insomnia","completed","intermediate","8","","2021-12-04","2021-12-05","2023-06-23 00:00:00","2023-10-16 18:15:12" -"142","tweet-mental-health-classification","Tweet Mental Health Classification","Build models to classify tweets to determine mental health","Build Models to classify tweets to determine mental health","","https://www.kaggle.com/competitions/tweet-mental-health-classification","completed","intermediate","8","","2021-12-27","2022-01-31","2023-06-23 00:00:00","2023-10-14 05:40:07" -"143","ml-olympiad-good-health-and-well-being","ML Olympiad - GOOD HEALTH AND WELL BEING","Use your ML expertise to classify if a patient has heart disease or not","Use your ML expertise to classify if a patient has heart disease or not","","https://www.kaggle.com/competitions/ml-olympiad-good-health-and-well-being","completed","intermediate","8","","2022-02-03","2022-03-01","2023-06-23 00:00:00","2023-10-16 18:15:20" -"144","rsna-breast-cancer-detection","RSNA Screening Mammography Breast Cancer Detection","Find breast cancers in screening mammograms","Find breast cancers in screening mammograms","","https://www.kaggle.com/competitions/rsna-breast-cancer-detection","completed","intermediate","8","","2022-11-28","2023-02-27","2023-06-23 00:00:00","2023-10-14 05:40:12" -"145","biocreative-vii-text-mining-drug-and-chemical-protein-interactions-drugprot","BioCreative VII: Text mining drug and chemical-protein interactions (DrugProt)","Develop systems to extract drug-gene relations from text","With the rapid accumulation of biomedical literature, it is getting increasingly challenging to exploit efficiently drug-related information described in the scientific literature. One of the most relevant aspects of drugs and chemical compounds are their relationships with certain biomedical entities, in particular genes and proteins. The aim of the DrugProt track (similar to the previous CHEMPROT task of BioCreative VI) is to promote the development and evaluation of systems that are able to automatically detect in relations between chemical compounds/drug and genes/proteins. There are a range of different types of drug-gene/protein interactions, and their systematic extraction and characterization is essential to analyze, predict and explore key biomedical properties underlying high impact biomedical applications. These application scenarios include use cases related to drug discovery, drug repurposing, drug design, metabolic engineering, modeling drug response, pharmacogenet...","","https://biocreative.bioinformatics.udel.edu/tasks/biocreative-vii/track-1/","completed","intermediate","\N","","2021-06-15","2021-09-22","2023-06-23 00:00:00","2023-11-01 20:37:37" -"146","extended-literature-ai-for-drug-induced-liver-injury","Extended Literature AI for Drug Induced Liver Injury","Develop ML tools to analyze drug texts for liver injury data","Unexpected Drug-Induced Liver Injury (DILI) still is one of the main killers of promising novel drug candidates. It is a clinically significant disease that can lead to severe outcomes such as acute liver failure and even death. It remains one of the primary liabilities in drug development and regulatory clearance due to the limited performance of mandated preclinical models even today. The free text of scientific publications is still the main medium carrying DILI results from clinical practice or experimental studies. The textual data still has to be analysed manually. This process, however, is tedious and prone to human mistakes or omissions, as results are very rarely available in a standardized form or organized form. There is thus great hope that modern techniques from machine learning or natural language processing could provide powerful tools to better process and derive the underlying knowledge within free form texts. The pressing need to faster process potential drug can...","","http://camda2022.bioinf.jku.at/contest_dataset#extended_literature_ai_for_drug_induced_liver_injury","completed","intermediate","\N","","\N","2022-05-20","2023-06-23 00:00:00","2023-11-01 20:37:38" -"147","anti-microbial-resistance-forensics","Anti-Microbial Resistance Forensics","Classifying bacteriophages to understand microbial evolution","Bacteriophages, being the re-occuring mystery in the history of science are believed to be they key for understanding of microbial evolution and the transfer of AMR genes. Recent studies show that there is a significant correlation between occurence of Phages and AMR genes, indicating that they are indeed taking part in the spread of them. While taking part in AMR dissemination the phages are also considered as the potential alternative to antibiotics. In such contradictory world there is a huge potential as well as urgent need for precise classification, description and analysis of capabilities. Due to pandemic of SARS-CoV-2, advance in phylogenetic algorithms and k-mer based methods have been extremely rapid and those improvements are witing to be adapted to different branches of life sciences.","","http://camda2022.bioinf.jku.at/contest_dataset#anti-microbial_resistance_forensics","completed","intermediate","\N","","\N","2022-05-20","2023-06-23 00:00:00","2023-10-14 05:40:14" -"148","disease-maps-to-modelling-covid-19","Disease Maps to Modelling COVID-19","Suggest drugs candidate for repurposing","The Disease Maps to modeling COVID-19 Challenge provides highly detailed expert-curated molecular mechanistic maps for COVID-19. Combine them with available omic data to expand the current biological knowledge on COVID-19 mechanism of infection and downstream consequences. The main topic for this year's challenge is drug repurposing with the possibility of Real World Data based validation of the most promising candidates suggested.","","http://camda2022.bioinf.jku.at/contest_dataset#disease_maps_to_modelling_covid-19","completed","intermediate","\N","","\N","2022-05-20","2023-06-23 00:00:00","2023-11-14 19:23:47" -"149","crowdsourced-evaluation-of-inchi-based-tautomer-identification","Crowdsourced Evaluation of InChI-based Tautomer Identification","Test a modified InChi algorithm","This challenge focuses on the International Chemical Identifier (InChI), which was developed and is maintained under the auspices of the International Union of Pure and Applied Chemistry (IUPAC) and the InChI Trust. The InChI Trust, the IUPAC Working Group on Tautomers, and the U.S. Food and Drug Administration (FDA) call on the scientific community dealing with chemical repositories/data sets and analytics of compounds to test the recently modified InChI algorithm, which was designed for advanced recognition of tautomers. Participants will evaluate this algorithm against real chemical samples in this Crowdsourced Evaluation of InChI-based Tautomer Identification.","","https://precision.fda.gov/challenges/29","completed","intermediate","6","","2022-11-01","2023-03-01","2023-06-23 00:00:00","2023-11-14 19:21:10" -"150","nctr-indel-calling-from-oncopanel-sequencing-challenge-phase-2","NCTR Indel Calling from Oncopanel Sequencing Challenge Phase 2","Calling from oncopanel sequencing data","The high value of clinically actionable information obtained by oncopanel sequencing makes it a crucial tool for precision oncology[1,2]. With the surge in availability of oncopanels, it is critical to ensure that they have been thoroughly tested and are properly used. FDA has initiated the Sequencing Quality Control phase II (SEQC2) project[3] to develop standard analysis protocols and quality control metrics for fit-for-purpose use of Next Generation Sequencing (NGS) data including oncopanel sequencing to inform regulatory science research and precision medicine. The Oncopanel Sequencing Working Group of FDA-led SEQC2 has developed a reference sample[4] suitable for benchmarking oncopanels and comprehensively assessed the analytical performance of several oncopanels[1,2]. The genomic deoxyribonucleic acid (gDNA) reference sample was derived from ten Universal Human Reference RNA (UHRR, Agilent Technologies, Inc) cell-lines and made publicly available by Agilent. Substantial gen...","","https://precision.fda.gov/challenges/22","completed","intermediate","6","","2022-07-11","2022-07-26","2023-06-23 00:00:00","2023-11-15 22:53:48" -"151","nctr-indel-calling-from-oncopanel-sequencing-data-challenge-phase-1","NCTR Indel Calling from Oncopanel Sequencing Data Challenge Phase 1","Identify indels in oncopanel sequencing datasets","The high value of clinically actionable information obtained by oncopanel sequencing makes it a crucial tool for precision oncology[1,2]. With the surge in availability of oncopanels, it is critical to ensure that they have been thoroughly tested and are properly used. FDA has initiated the Sequencing Quality Control phase II (SEQC2) project[3] to develop standard analysis protocols and quality control metrics for fit-for-purpose use of Next Generation Sequencing (NGS) data including oncopanel sequencing to inform regulatory science research and precision medicine. The Oncopanel Sequencing Working Group of FDA-led SEQC2 has developed a reference sample[4] suitable for benchmarking oncopanels and comprehensively assessed the analytical performance of several oncopanels[1,2]. The genomic deoxyribonucleic acid (gDNA) reference sample was derived from ten Universal Human Reference RNA (UHRR, Agilent Technologies, Inc) cell-lines and made publicly available by Agilent. Substantial gen...","","https://precision.fda.gov/challenges/21","completed","intermediate","6","","2022-05-02","2022-07-08","2023-06-23 00:00:00","2023-11-14 19:24:33" -"152","vha-innovation-ecosystem-and-precisionfda-covid-19-risk-factor-modeling-challenge-phase-2","VHA Innovation Ecosystem and precisionFDA COVID-19 Risk Factor Modeling Challenge Phase 2","Validate the top performing models on two additional VA sites' data","The novel coronavirus disease 2019 (COVID-19) is a respiratory disease caused by a new type of coronavirus, known as “severe acute respiratory syndrome coronavirus 2,” or SARS-CoV-2. On March 11, 2020, the World Health Organization (WHO) declared the outbreak a global pandemic. As of January 22nd, 2022, the Johns Hopkins University COVID-19 dashboard reports over 338 million total confirmed cases worldwide. Although most people have mild to moderate symptoms, the disease can cause severe medical complications leading to death in some people. The Centers for Disease Control and Prevention (CDC) have identified several risk factors for severe COVID-19 illness, including people 65 years and older, individuals living in nursing homes or long-term care facilities, and those with serious underlying medical conditions. The Veteran population has a higher prevalence of several of the known risk factors for severe COVID-19 illness, such as advanced age, heart disease, and diabetes. Identif...","","https://precision.fda.gov/challenges/20","completed","intermediate","6","","2021-04-14","2022-01-28","2023-06-23 00:00:00","2023-11-14 19:24:37" -"153","tumor-mutational-burden-tmb-challenge-phase-2","Tumor Mutational Burden (TMB) Challenge Phase 2","Evaluating various computational pipelines for TMB estimation","Tumor mutational burden (TMB) is generally defined as the number of mutations detected in a patient's tumor sample per megabase of DNA sequenced. However different algorithms use different methods for calculating TMB. Mutations in genes in tumor cells may lead to the creation of neoantigens, which have the potential to activate an immune system response against the tumor, and the likelihood of an immune system response may increase with the number of mutations. Thus, TMB is a biomarker for some immunotherapy drugs, called immune checkpoint inhibitors, such as those that target the PD-1 and PD-L1 pathways (Chan et al., 2019). An outstanding problem is the lack of standardization for TMB calculation and reporting between different assays. To address this problem, the Friends of Cancer Research convened a working group of industry and regulatory stakeholders to develop guidance and tools for TMB harmonization. Results from the first phase of this effort were presented at AACR 2020 (s...","","https://precision.fda.gov/challenges/18","completed","intermediate","6","","2021-07-19","2021-09-12","2023-06-23 00:00:00","2023-11-14 19:24:44" -"154","predicting-gene-expression-using-millions-of-random-promoter-sequences","Predicting Gene Expression Using Millions of Random Promoter Sequences","Decoding gene expression regulation to understand disease","Decoding how gene expression is regulated is critical to understanding disease. Regulatory DNA is decoded by the cell in a process termed “cis-regulatory logic”, where proteins called Transcription Factors (TFs) bind to specific DNA sequences within the genome and work together to produce as output a level of gene expression for downstream adjacent genes. This process is exceedingly complex to model as a large number of parameters is needed to fully describe the process (see Rationale, de Boer et al. 2020; Zeitingler J. 2020). Understanding the cis-regulatory logic of the human genome is an important goal and would provide insight into the origins of many diseases. However, learning models from human data is challenging due to limitations in the diversity of sequences present within the human genome (e.g. extensive repetitive DNA), the vast number of cell types that differ in how they interpret regulatory DNA, limited reporter assay data, and substantial technical biases present i...","","https://www.synapse.org/#!Synapse:syn28469146/wiki/617075","completed","intermediate","1","","2022-06-15","2022-08-07","2023-06-23 00:00:00","2023-10-14 05:40:21" -"155","brats-2023","BraTS 2023","Benchmarking brain tumor segmentation with expanded dataset","The International Brain Tumor Segmentation (BraTS) challenge. BraTS, since 2012, has focused on the generation of a benchmarking environment and dataset for the delineation of adult brain gliomas. The focus of this year’s challenge remains the generation of a common benchmarking environment, but its dataset is substantially expanded to ~4,500 cases towards addressing additional i) populations (e.g., sub-Saharan Africa patients), ii) tumors (e.g., meningioma), iii) clinical concerns (e.g., missing data), and iv) technical considerations (e.g., augmentations). Specifically, the focus of BraTS 2023 is to identify the current state-of-the-art algorithms for addressing (Task 1) the same adult glioma population as in the RSNA-ANSR-MICCAI BraTS challenge, as well as (Task 2) the underserved sub-Saharan African brain glioma patient population, (Task 3) intracranial meningioma, (Task 4) brain metastasis, (Task 5) pediatric brain tumor patients, (Task 6) global & local missing data, (Task 7...","","https://www.synapse.org/brats","completed","advanced","1","","2023-06-01","2023-08-25","2023-06-23 00:00:00","2023-10-26 23:20:21" -"156","cagi7","CAGI7","The seventh round of CAGI","There have been six editions of CAGI experiments, held between 2010 and 2022. The seventh round of CAGI is planned to take place over the Summer of 2024.","","https://genomeinterpretation.org/challenges.html","upcoming","intermediate","1","","\N","\N","2023-08-04 21:47:38","2023-11-20 20:19:08" -"157","casp15","CASP15","Establish the state-of-art in modeling proteins and protein complexes","CASP14 (2020) saw an enormous jump in the accuracy of single protein and domain models such that many are competitive with experiment. That advance is largely the result of the successful application of deep learning methods, particularly by the AlphaFold and, since that CASP, RosettaFold. As a consequence, computed protein structures are becoming much more widely used in a broadening range of applications. CASP has responded to this new landscape with a revised set of modeling categories. Some old categories have been dropped (refinement, contact prediction, and aspects of model accuracy estimation) and new ones have been added (RNA structures, protein ligand complexes, protein ensembles, and accuracy estimation for protein complexes). We are also strengthening our interactions with our partners CAPRI and CAMEO. We hope that these changes will maximize the insight that CASP15 provides, particularly in new applications of deep learning.","","https://predictioncenter.org/casp15/index.cgi","completed","intermediate","\N","","2022-04-18","\N","2023-08-04 21:52:12","2023-09-28 23:09:59" -"158","synthrad2023","SynthRAD2023","Automatic generation of synthetic computed tomography (sCT) for radiotherapy","This challenge aims to provide the first platform offering public data evaluation metrics to compare the latest developments in sCT generation methods. The accepted challenge design approved by MICCAI can be found at https://doi.org/10.5281/zenodo.7746019. A type 2 challenge will be run, where the participant needs to submit their algorithm packaged in a docker both for validation and test.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/678/SynthRAD_square_logo_MnAqldI.png","https://synthrad2023.grand-challenge.org/","completed","intermediate","5","","2023-04-01","2023-08-22","2023-08-04 21:54:31","2023-11-14 19:24:54" -"159","synthetic-data-for-instrument-segmentation-in-surgery-syn-iss","Synthetic Data for Instrument Segmentation in Surgery (Syn-ISS)","Surgical instrument segmentation with synthetic data","A common limitation noted by the surgical data science community is the size of datasets and the resources needed to generate training data at scale for building reliable and high-performing machine learning models. Beyond unsupervised and self-supervised approaches another solution within the broader machine learning community has been a growing volume of literature in the use of synthetic data (simulation) for training algorithms than can be applied to real world data. Synthetic data has multiple benefits like free groundtruth at large scale, possibility to collect larger sample of rare events, include anatomical variations, etc. A first step towards proving the validity of using synthetic data for real world applications is to demonstrate the feasibility within the simulation world itself. Our proposed challenge is to train machine learning methods for instrument segmentation using synthetic datasets and test their performance on synthetic datasets. That is, the challenge parti...","","https://www.synapse.org/#!Synapse:syn50908388/wiki/620516","completed","intermediate","1","","2023-07-19","2023-09-07","2023-08-04 23:49:44","2023-11-14 19:25:04" -"160","pitvis","PitVis","Surgical workflow and instrument recognition in endonasal surgery","The pituitary gland, found just off the base of the brain, is commonly known as “the master gland”, performing essential functions required for sustaining human life. Clinically relevant tumours that have grown on the pituitary gland have an estimated prevalence of 1 in 1000 of the population, and if left untreated can be life-limiting. The “gold standard” treatment is endoscopic pituitary surgery, where the tumour is directly removed by entering through a nostril. This surgery is particularly challenging due to the small working space which limits both vision and instrument manoeuvrability and thus can lead to poor surgical technique causing adverse outcomes for the patient. Computer-assisted intervention can help overcome these challenges by providing guidance for senior surgeons and operative staff during surgery, and for junior surgeons during training.","","https://www.synapse.org/#!Synapse:syn51232283/wiki/","completed","intermediate","1","","2023-06-29","2023-09-10","2023-08-04 23:58:01","2023-10-26 23:20:30" -"161","mvseg2023","MVSEG2023","Single frame 3D trans-esophageal echocardiography","Mitral valve (MV) disease is a common pathologic problem occurring in approximately 2 % of the general population but climbing to 10 % in those over the age of 75. The preferred intervention for mitral regurgitation is valve repair, due to superior patient outcomes compared to those following valve replacement. Mitral valve interventions are technically challenging due to the functional and anatomical complexity of mitral pathologies. Repair must be tailored to the patient-specific anatomy and pathology, which requires considerable expert training and experience. Automatic segmentation of the mitral valve leaflets from 3D transesophageal echocardiography (TEE) may play an important role in treatment planning, as well as physical and computational modelling of patient-specific valve pathologies and potential repair approaches. This may have important implications in the drive towards personalized care and has the potential to impact clinical outcomes for those undergoing mitral val...","","https://www.synapse.org/#!Synapse:syn51186045/wiki/621356","completed","intermediate","1","","2023-05-29","2023-08-07","2023-08-05 0-04-36","2023-11-14 19:25:13" -"162","crossmoda23","crossMoDA23","Medical imaging benchmark for unsupervised domain adaptation","Domain Adaptation (DA) has recently raised strong interest in the medical imaging community. By encouraging algorithms to be robust to unseen situations or different input data domains, Domain Adaptation improves the applicability of machine learning approaches to various clinical settings. While a large variety of DA techniques has been proposed, most of these techniques have been validated either on private datasets or on small publicly available datasets. Moreover, these datasets mostly address single-class problems. To tackle these limitations, the crossMoDA challenge introduced the first large and multi-class dataset for unsupervised cross-modality Domain Adaptation. From an application perspective, crossMoDA focuses on MRI segmentation for Vestibular Schwannoma. Compared to the previous crossMoDA instance, which made use of multi-institutional data acquired in controlled conditions for radiosurgery planning and focused on a 2 class segmentation task (tumour and cochlea), the...","","https://www.synapse.org/#!Synapse:syn51236108/wiki/621615","completed","intermediate","1","","2023-04-15","2023-07-10","2023-08-05 0-13-23","2023-11-14 19:27:00" -"163","icr-identify-age-related-conditions","ICR - Identifying Age-Related Conditions","Detect conditions with measurements of anonymous characteristics of a subject","The goal of this competition is to predict if a person has any of three medical conditions. You are being asked to predict if the person has one or more of any of the three medical conditions (Class 1), or none of the three medical conditions (Class 0). You will create a model trained on measurements of health characteristics. To determine if someone has these medical conditions requires a long and intrusive process to collect information from patients. With predictive models, we can shorten this process and keep patient details private by collecting key characteristics relative to the conditions, then encoding these characteristics.","","https://www.kaggle.com/competitions/icr-identify-age-related-conditions","completed","intermediate","8","","2023-05-11","2023-08-10","2023-08-05 0-32-01","2023-11-14 19:25:37" -"164","cafa-5-protein-function-prediction","CAFA 5: Protein Function Prediction","Predict the biological function of a protein","The goal of this competition is to predict the function of a set of proteins. You will develop a model trained on the amino-acid sequences of the proteins and on other data. Your work will help ​​researchers better understand the function of proteins, which is important for discovering how cells, tissues, and organs work. This may also aid in the development of new drugs and therapies for various diseases.","","https://www.kaggle.com/competitions/cafa-5-protein-function-prediction","completed","intermediate","8","","2023-04-18","2023-08-21","2023-08-05 5-18-40","2023-10-19 00:13:14" -"165","rsna-2023-abdominal-trauma-detection","RSNA 2023 Abdominal Trauma Detection","Detect and classify traumatic abdominal injuries","Traumatic injury is the most common cause of death in the first four decades of life and a major public health problem around the world. There are estimated to be more than 5 million annual deaths worldwide from traumatic injury. Prompt and accurate diagnosis of traumatic injuries is crucial for initiating appropriate and timely interventions, which can significantly improve patient outcomes and survival rates. Computed tomography (CT) has become an indispensable tool in evaluating patients with suspected abdominal injuries due to its ability to provide detailed cross-sectional images of the abdomen. Interpreting CT scans for abdominal trauma, however, can be a complex and time-consuming task, especially when multiple injuries or areas of subtle active bleeding are present. This challenge seeks to harness the power of artificial intelligence and machine learning to assist medical professionals in rapidly and precisely detecting injuries and grading their severity. The development...","","https://www.kaggle.com/competitions/rsna-2023-abdominal-trauma-detection","completed","intermediate","8","","2023-07-26","2023-10-13","2023-08-05 5-24-09","2023-09-28 23:14:12" -"166","hubmap-hacking-the-human-vasculature","HuBMAP: Hacking the Human Vasculature","Microvascular structures from healthy human kidney tissue images","The goal of this competition is to segment instances of microvascular structures, including capillaries, arterioles, and venules. You'll create a model trained on 2D PAS-stained histology images from healthy human kidney tissue slides. Your help in automating the segmentation of microvasculature structures will improve researchers' understanding of how the blood vessels are arranged in human tissues.","","https://www.kaggle.com/competitions/hubmap-hacking-the-human-vasculature","completed","intermediate","8","","2023-05-22","2023-07-31","2023-08-05 5-31-12","2023-11-14 19:25:45" -"167","amp-parkinsons-disease-progression-prediction","AMP(R)-Parkinson's Disease Progression Prediction","Predict clinical and molecular progression of the disease","The goal of this competition is to predict MDS-UPDR scores, which measure progression in patients with Parkinson's disease. The Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) is a comprehensive assessment of both motor and non-motor symptoms associated with Parkinson's. You will develop a model trained on data of protein and peptide levels over time in subjects with Parkinson’s disease versus normal age-matched control subjects. Your work could help provide important breakthrough information about which molecules change as Parkinson’s disease progresses.","","https://www.kaggle.com/competitions/amp-parkinsons-disease-progression-prediction","completed","intermediate","8","","2023-02-16","2023-05-18","2023-08-05 5-37-12","2023-11-14 19:25:52" -"168","open-problems-multimodal","Open Problems -Multimodal Single-Cell Integration","Predict how DNA, RNA & protein measurements co-vary in single cells","The goal of this competition is to predict how DNA, RNA, and protein measurements co-vary in single cells as bone marrow stem cells develop into more mature blood cells. You will develop a model trained on a subset of 300,000-cell time course dataset of CD34+ hematopoietic stem and progenitor cells (HSPC) from four human donors at five time points generated for this competition by Cellarity, a cell-centric drug creation company. In the test set, taken from an unseen later time point in the dataset, competitors will be provided with one modality and be tasked with predicting a paired modality measured in the same cell. The added challenge of this competition is that the test data will be from a later time point than any time point in the training data. Your work will help accelerate innovation in methods of mapping genetic information across layers of cellular state. If we can predict one modality from another, we may expand our understanding of the rules governing these complex re...","","https://www.kaggle.com/competitions/open-problems-multimodal","completed","intermediate","8","","2022-08-15","2022-11-15","2023-08-05 5-43-25","2023-10-10 19:52:41" -"169","multi-atlas-labeling-beyond-the-cranial-vault","Multi-Atlas Labeling Beyond the Cranial Vault","Innovative multi-atlas labeling for soft tissue segmentation on clinical CT","Multi-atlas labeling has proven to be an effective paradigm for creating segmentation algorithms from training data. These approaches have been extraordinarily successful for brain and cranial structures (e.g., our prior MICCAI workshops-MLSF’11, MAL’12, SATA’13). After the original challenges closed, the data continue to drive scientific innovation; 144 groups have registered for the 2012 challenge (brain only) and 115 groups for the 2013 challenge (brain/heart/canine leg). However, innovation in application outside of the head and to soft tissues has been more limited. This workshop will provide a snapshot of the current progress in the field through extended discussions and provide researchers an opportunity to characterize their methods on a newly created and released standardized dataset of abdominal anatomy on clinically acquired CT. The datasets will be freely available both during and after the challenge. We have two separate new challenges-abdomen and cervix on routinely ...","","https://www.synapse.org/#!Synapse:syn3193805/wiki/89480","active","intermediate","1","","2015-04-15","\N","2023-08-07 20:21:22","2023-10-10 19:52:39" -"170","hubmap-organ-segmentation","HuBMAP + HPA: Hacking the Human Body","Segment multi-organ functional tissue units","In this competition, you’ll identify and segment functional tissue units (FTUs) across five human organs. You'll build your model using a dataset of tissue section images, with the best submissions segmenting FTUs as accurately as possible. If successful, you'll help accelerate the world’s understanding of the relationships between cell and tissue organization. With a better idea of the relationship of cells, researchers will have more insight into the function of cells that impact human health. Further, the Human Reference Atlas constructed by HuBMAP will be freely available for use by researchers and pharmaceutical companies alike, potentially improving and prolonging human life.","","https://www.kaggle.com/competitions/hubmap-organ-segmentation","completed","intermediate","8","","2022-06-22","2022-09-22","2023-08-08 16:30:22","2023-11-02 18:44:27" -"171","hubmap-kidney-segmentation","HuBMAP: Hacking the Kidney","Identify glomeruli in human kidney tissue images","This competition, “Hacking the Kidney, starts by mapping the human kidney at single cell resolution. Your challenge is to detect functional tissue units (FTUs) across different tissue preparation pipelines. An FTU is defined as a “three-dimensional block of cells centered around a capillary, such that each cell in this block is within diffusion distance from any other cell in the same block” ([de Bono, 2013](https://www.ncbi.nlm.nih.gov/pubmed/24103658)). The goal of this competition is the implementation of a successful and robust glomeruli FTU detector. You will also have the opportunity to present your findings to a panel of judges for additional consideration. Successful submissions will construct the tools, resources, and cell atlases needed to determine how the relationships between cells can affect the health of an individual. Advancements in HuBMAP will accelerate the world’s understanding of the relationships between cell and tissue organization and function and human health.","","https://www.kaggle.com/competitions/hubmap-kidney-segmentation","completed","intermediate","8","","2020-11-16","2021-05-10","2023-08-08 17:31:46","2023-10-12 18:14:16" -"172","ventilator-pressure-prediction","Google Brain: Ventilator Pressure Prediction","Simulate a ventilator connected to a sedated patient's lung","In this competition, you’ll simulate a ventilator connected to a sedated patient's lung. The best submissions will take lung attributes compliance and resistance into account. If successful, you'll help overcome the cost barrier of developing new methods for controlling mechanical ventilators. This will pave the way for algorithms that adapt to patients and reduce the burden on clinicians during these novel times and beyond. As a result, ventilator treatments may become more widely available to help patients breathe.","","https://www.kaggle.com/competitions/ventilator-pressure-prediction","completed","intermediate","8","","2021-09-22","2021-11-03","2023-08-08 17:53:33","2023-11-02 18:44:22" -"173","stanford-covid-vaccine","OpenVaccine - COVID-19 mRNA Vaccine Degradation Prediction","Urgent need to bring the COVID-19 vaccine to mass production","In this competition, we are looking to leverage the data science expertise of the Kaggle community to develop models and design rules for RNA degradation. Your model will predict likely degradation rates at each base of an RNA molecule, trained on a subset of an Eterna dataset comprising over 3000 RNA molecules (which span a panoply of sequences and structures) and their degradation rates at each position. We will then score your models on a second generation of RNA sequences that have just been devised by Eterna players for COVID-19 mRNA vaccines. These final test sequences are currently being synthesized and experimentally characterized at Stanford University in parallel to your modeling efforts--Nature will score your models!","","https://www.kaggle.com/competitions/stanford-covid-vaccine","completed","intermediate","8","","2020-09-10","2020-10-06","2023-08-08 18:06:17","2023-10-12 18:14:27" -"174","openvaccine","OpenVaccine","To develop mRNA vaccines stable enough to be deployed to everyone in the world","mRNA vaccines are a relatively new technology that have come into the limelight with the onset of COVID-19. They were the first COVID-19 vaccines to start clinical trials (initially formulated in a matter of days) and the first to be approved and distributed. mRNA vaccines have the potential to transform immunization, being significantly faster to formulate and produce, cheaper, and more effective-including against mutant strains. However, there is one key bottleneck to their widespread viability and our ability to immunize the entire world-poor refrigerator stability in prefilled syringes. The OpenVaccine challenge aims to allow a worldwide community of game players to create an enhanced vaccine to be injected into millions of people. The challenge-design an mRNA that codes for the same amino acid sequence of the spike protein, but is 2x-10x+ more stable. Through a number of academic partnerships and the launch of a Kaggle machine learning challenge to create best-in-class algori...","","https://eternagame.org/challenges/10845741","completed","intermediate","13","https://doi.org/10.1038/s41467-022-28776-w","\N","2021-12-12","2023-08-08 18:22:49","2023-11-14 19:26:10" -"175","opentb","OpenTB","Detect a gene sequence found to be present only in people with active TB","OpenTB used a recently reported gene signature for active tuberculosis based on three RNAs in the blood. This signature could form the basis for a fast, color-based test for TB, similar to an over-the-counter pregnancy test. What was needed was a sensor that could detect the concentrations of three RNAs, carry out the needed calculation, and report the result by binding another molecule. Over four rounds, players designed RNA sensors that can do the math on these 3 genes. Through experimental feedback, they honed their skills and techniques, which resulted in the creation of multiple designs that have been shown to be successful. These findings are being prepared to be published, and future work will be done to develop diagnostic devices integrating these designs","","https://eternagame.org/challenges/10845742","completed","intermediate","13","","2016-05-04","2018-04-15","2023-08-08 18:43:09","2023-11-14 19:32:31" -"176","opencrispr","OpenCRISPR","Discover RNAs to make gene editing more precisely controllable","CRISPR gene editing is a RNA-based method that can target essentially any gene in a living organism for genetic changes. Since its first demonstration, CRISPR has been revolutionizing biology and promises to change how we tackle numerous human diseases from malaria to cancer. Stanford's Center for Personal Dynamic Regulomes and UC Berkeley's Innovative Genomics Institute have challenged Eterna players to solve a remaining hurdle in making this technology safe for use. Scientists want the power to turn on and off CRISPR on demand with small molecules. This is almost a perfect match to the small-molecule switches that the Eterna community has worked on. In fact, the MS2 RNA hairpin often used in Eterna is routinely used to recruit new functionality to CRISPR complexes through other molecules tethered to the MS2 protein. The puzzles began with OpenCRISPR Controls, looking for solutions to lock in or lock out the MS2 RNA hairpin within a special loop in the CRISPR RNA. We hope the res...","","https://eternagame.org/challenges/10845743","completed","intermediate","13","https://doi.org/10.1021/acssynbio.9b00142","2017-08-26","\N","2023-08-08 18:43:14","2023-11-14 19:33:25" -"177","openknot","OpenKnot","Build a diverse library of RNAs that form pseudoknot structures","RNA pseudoknots have significant biological importance in various processes. They participate in gene regulation by influencing translation initiation or termination in mRNA molecules. Pseudoknots also play a role in programmed ribosomal frameshifting, leading to the production of different protein products from a single mRNA. RNA viruses, including SARS-CoV-2 and Dengue virus, utilize pseudoknots to regulate their replication and control the synthesis of viral proteins. Additionally, certain RNA molecules with pseudoknot structures exhibit enzymatic activity, acting as ribozymes and catalyzing biochemical reactions. These functions highlight the crucial role of RNA pseudoknots in gene expression, proteomic diversity, viral replication, and enzymatic processes. Several unanswered scientific questions surround RNA pseudoknots. One key area of inquiry is understanding the folding pathways of pseudoknots and how they form from linear RNA sequences. Elucidating the structural dynamics...","","https://eternagame.org/challenges/11843006","active","intermediate","13","","2022-06-17","\N","2023-08-08 18:43:22","2023-11-14 19:32:46" -"178","openaso","OpenASO","Design principles for RNA-based therapeutics","The DNA genome is the blueprint for building and operating cells, but this information must be decoded into RNA molecules to be useful. Transcription is the process of decoding DNA genomic information into RNA, resulting in RNA transcripts. Genes are specific sequences of DNA that contain information to produce a specific RNA transcript. The fate of most mRNA molecules in the cell is to be translated by ribosomes into protein molecules. However, mRNA splicing is a crucial step that occurs between the formation of an RNA transcript and protein translation. This step is essential because genes contain non-protein coding introns and protein-coding exons. Splicing removes introns and joins exons to produce a mature mRNA molecule that can be decoded into the correct protein molecule. When the splicing process is corrupted due to genetic mutations, the resulting RNA can become toxic, leading to the synthesis of non-functional proteins or no protein at all, causing various human diseases...","","https://eternagame.org/challenges/11546273","active","intermediate","13","","2023-02-20","\N","2023-08-08 18:43:25","2023-11-14 19:32:51" -"179","openribosome","OpenRibosome","Learn and change the ribosome's RNAs","Our modern world has many challenges-challenges like climate change, increasing waste production, and human health. Imagine-we could replace petrochemistry with biology, single-use plastics with selectively degradable polymers, broad chemotherapeutics with targeted medicines for fighting specific cancer cells, and complex health equipment with point-of-care diagnostics. These innovations and many more can empower us to confront the challenges affecting humanity, our world, and beyond. But how do we actually create these smart materials and medicines? Is it possible to do so by repurposing one of Nature's molecular machines? We think we can. The answer? Customized ribosomes. In Nature, ribosomes are the catalysts for protein assembly. And proteins are more or less similar, chemically, to the smart materials and medicines we want to synthesize. If we could modify ribosomes to build polymers with diverse components-beyond the canonical amino acids us","","https://eternagame.org/challenges/11043833","active","intermediate","13","https://doi.org/10.1038/s41467-023-35827-3","2019-01-31","\N","2023-08-08 18:43:27","2023-11-14 19:33:01" -"180","lish-moa","Mechanisms of Action (MoA) Prediction","Improve the algorithm that classifies drugs based on their biological activity","Can you improve the algorithm that classifies drugs based on their biological activity?","","https://www.kaggle.com/competitions/lish-moa","completed","intermediate","8","","2020-09-03","2020-11-30","2023-08-08 19:09:31","2023-11-14 19:33:49" -"181","recursion-cellular-image-classification","Recursion Cellular Image Classification","CellSignal-Disentangling biological signal in cellular images","This competition will have you disentangling experimental noise from real biological signals. Your entry will classify images of cells under one of 1,108 different genetic perturbations. You can help eliminate the noise introduced by technical execution and environmental variation between experiments. If successful, you could dramatically improve the industry’s ability to model cellular images according to their relevant biology. In turn, applying AI could greatly decrease the cost of treatments, and ensure these treatments get to patients faster.","","https://www.kaggle.com/competitions/recursion-cellular-image-classification","completed","intermediate","8","","2019-06-27","2019-09-26","2023-08-08 19:38:42","2023-11-14 19:34:11" -"182","tlvmc-parkinsons-freezing-gait-prediction","Parkinson's Freezing of Gait Prediction","Event detection from wearable sensor data","The goal of this competition is to detect freezing of gait (FOG), a debilitating symptom that afflicts many people with Parkinson’s disease. You will develop a machine learning model trained on data collected from a wearable 3D lower back sensor. Your work will help researchers better understand when and why FOG episodes occur. This will improve the ability of medical professionals to optimally evaluate, monitor, and ultimately, prevent FOG events.","","https://www.kaggle.com/competitions/tlvmc-parkinsons-freezing-gait-prediction","completed","intermediate","8","","2023-03-09","2023-06-08","2023-08-08 19:47:54","2023-10-10 19:53:08" -"183","chaimeleon","CHAIMELEON Open Challenges","AI-powered solutions driving innovation in cancer diagnosis and treatment","The CHAIMELEON Open Challenges is a competition designed to train and refine AI models to answer clinical questions about five types of cancer-prostate, lung, breast, colon, and rectal. Participants are challenged to collaborate and develop innovative AI-powered solutions that can significantly impact cancer diagnosis, management, and treatment. They will be evaluated considering a balance between the performance of their AI algorithms to predict different clinical endpoints such as disease staging, treatment response or progression free survival and their trustworthiness. The challenges are open to the whole scientific and tech community interested in AI. They are a unique opportunity to showcase how AI can be used to advance medical research and improve patient outcomes within the CHAIMELEON project.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/744/Logo_Grand_Challenge_-_2.png","https://chaimeleon.grand-challenge.org/","completed","intermediate","5","","2023-11-02","2023-11-30","2023-08-09 17:13:09","2023-11-14 19:34:50" -"184","topcow23","Topology-Aware Anatomical Segmentation of the Circle of Willis for CTA and MRA","Segment the Circle of Willis (CoW) vessel components for both CTA and MRA","The aim of the challenge is to extract the CoW angio-architecture from 3D angiographic imaging by segmentation of the vessel components. There are two sub-tasks-binary segmentation of CoW vessels, and multi-class CoW anatomical segmentation. We release a new dataset of joint-modalities, CTA and MRA of the same patient cohort, both with annotations of the anatomy of CoW. Our challenge has two tracks for the same segmentation task, namely CTA track and MRA track. We made use of the clinical information from both modalities during our annotation. And participants can pick whichever modality they want, both CTA and MRA, and choose to tackle the task for either modality.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/733/TopCow_logo.jpg","https://topcow23.grand-challenge.org/","completed","intermediate","5","","2023-08-20","2023-09-25","2023-08-09 17:16:22","2023-11-08 00:53:26" -"185","circle-of-willis-intracranial-artery-classification-and-quantification-challenge-2023","Circle of Willis Intracranial Artery Classification and Quantification Challenge 2023","Classify the circle of Willis (CoW) configuration and quantification","The purpose of this challenge is to compare automatic methods for classification of the circle of Willis (CoW) configuration and quantification of the CoW major artery diameters and bifurcation angles.","","https://crown.isi.uu.nl/","completed","intermediate","\N","","2023-05-01","2023-08-15","2023-08-09 22:13:24","2023-09-28 23:24:54" -"186","making-sense-of-electronic-health-record-ehr-race-and-ethnicity-data","Making Sense of Electronic Health Record (EHR) Race and Ethnicity Data","Make sense of electronic health record race and ethnicity data","The urgency of the coronavirus disease 2019 (COVID-19) pandemic has heightened interest in the use of real-world data (RWD) to obtain timely information about patients and populations and has focused attention on EHRs. The pandemic has also heightened awareness of long-standing racial and ethnic health disparities along a continuum from underlying social determinants of health, exposure to risk, access to insurance and care, quality of care, and responses to treatments. This highlighted the potential that EHRs can be used to describe and contribute to our understanding of racial and ethnic health disparities and their solutions. The OMB Revisions to the Standards for the Classification of Federal Data on Race and Ethnicity provides minimum standards for maintaining, collecting, and presenting data on race and ethnicity for all Federal reporting purposes, and defines the two separate constructs of race and ethnicity.","","https://precision.fda.gov/challenges/30","completed","intermediate","6","","2023-05-31","2023-06-23","2023-08-10 18:28:06","2023-11-14 19:34:58" -"187","the-veterans-cardiac-health-and-ai-model-predictions-v-champs","The Veterans Cardiac Health and AI Model Predictions (V-CHAMPS)","Predict cardiovascular health related outcomes in veterans","To better understand the risk and protective factors in the Veteran population, the VHA IE and its collaborating partners are calling upon the public to develop AI/ML models to predict cardiovascular health outcomes, including readmission and mortality, using synthetically generated Veteran health records. The Challenge consists of two Phases-Phase 1 is focused on synthetic data. In this Phase of the Challenge, AI/ML models will be developed by Challenge participants and trained and tested on the synthetic data sets provided to them, with a view towards predicting outcome variables for Veterans who have been diagnosed with chronic heart failure (please note that in Phase 1, the data is synthetic Veteran health records). Phase 2 will focus on validating and further exploring the limits of the AI/ML models. During this Phase, high-performing AI/ML models from Phase 1 will be brought into the VA system and validated on the real-world Veterans health data within the VHA. These models...","","https://precision.fda.gov/challenges/31","completed","intermediate","6","","2023-05-25","2023-08-02","2023-08-10 21:41:10","2023-11-14 19:35:53" -"188","predicting-high-risk-breast-cancer-phase-1","Predicting High Risk Breast Cancer - Phase 1","Predicting High Risk Breast Cancer-a Nightingale OS & AHLI data challenge","Every year, 40 million women get a mammogram; some go on to have an invasive biopsy to better examine a concerning area. Underneath these routine tests lies a deep—and disturbing—mystery. Since the 1990s, we have found far more ‘cancers’, which has in turn prompted vastly more surgical procedures and chemotherapy. But death rates from metastatic breast cancer have hardly changed. When a pathologist looks at a biopsy slide, she is looking for known signs of cancer-tubules, cells with atypical looking nuclei, evidence of rapid cell division. These features, first identified in 1928, still underlie critical decisions today-which women must receive urgent treatment with surgery and chemotherapy? And which can be prescribed “watchful waiting”, sparing them invasive procedures for cancers that would not harm them? There is already evidence that algorithms can predict which cancers will metastasize and harm patients on the basis of the biopsy image. Fascinatingly, these algorithms also h...","","https://app.nightingalescience.org/contests/3jmp2y128nxd","completed","intermediate","14","","2022-06-01","2023-01-12","2023-08-22 17:07:00","2023-10-12 17:55:10" -"189","predicting-high-risk-breast-cancer-phase-2","Predicting High Risk Breast Cancer - Phase 2","Predicting High Risk Breast Cancer-a Nightingale OS & AHLI data challenge","Every year, 40 million women get a mammogram; some go on to have an invasive biopsy to better examine a concerning area. Underneath these routine tests lies a deep—and disturbing—mystery. Since the 1990s, we have found far more ‘cancers’, which has in turn prompted vastly more surgical procedures and chemotherapy. But death rates from metastatic breast cancer have hardly changed. When a pathologist looks at a biopsy slide, she is looking for known signs of cancer-tubules, cells with atypical looking nuclei, evidence of rapid cell division. These features, first identified in 1928, still underlie critical decisions today-which women must receive urgent treatment with surgery and chemotherapy? And which can be prescribed “watchful waiting”, sparing them invasive procedures for cancers that would not harm them? There is already evidence that algorithms can predict which cancers will metastasize and harm patients on the basis of the biopsy image. Fascinatingly, these algorithms also...","","https://app.nightingalescience.org/contests/vd8g98zv9w0p","completed","intermediate","14","","2023-02-03","2023-05-13","2023-08-22 17:07:01","2023-10-12 17:55:08" -"190","dream-2-in-silico-network-inference","DREAM 2 - In Silico Network Inference","Predict the connectivity and properties of in-silico networks","Three in-silico networks were created and endowed with a dynamics that simulate biological interactions. The challenge consists of predicting the connectivity and some of the properties of one or more of these three networks.","","https://www.synapse.org/#!Synapse:syn2825394/wiki/71150","completed","intermediate","1","","2007-03-25","\N","2023-08-24 18:54:05","2023-10-12 17:55:03" -"191","dream-3-in-silico-network-challenge","DREAM 3 - In Silico Network Challenge","Reverse engineering of gene networks from biological data","The goal of the in silico challenges is the reverse engineering of gene networks from steady state and time series data. Participants are challenged to predict the directed unsigned network topology from the given in silico generated gene topic_3170sets.","","https://www.synapse.org/#!Synapse:syn2853594/wiki/71567","completed","intermediate","1","https://doi.org/10.1089/cmb.2008.09TT","2008-06-09","\N","2023-08-25 16:43:41","2023-11-14 19:35:58" -"192","dream-4-in-silico-network-challenge","DREAM 4 - In Silico Network Challenge","Reverse engineer gene regulatory networks","The goal of the in silico network challenge is to reverse engineer gene regulation networks from simulated steady-state and time-series data. Participants are challenged to infer the network structure from the given in silico gene topic_3170sets. Optionally, participants may also predict the response of the networks to a set of novel perturbations that were not included in the provided datasets.","","https://www.synapse.org/#!Synapse:syn3049712/wiki/74628","completed","intermediate","1","https://doi.org/10.1073/pnas.0913357107","2009-06-09","\N","2023-08-25 16:43:42","2023-11-14 19:36:02" -"193","dream-5-network-inference-challenge","DREAM 5 - Network Inference Challenge","Reverse engineer gene regulatory networks","The goal of this Network Inference Challenge is to reverse engineer gene regulatory networks from gene topic_3170sets. Participants are given four microarray compendia and are challenged to infer the structure of the underlying transcriptional regulatory networks. Three of the four compendia were obtained from microorganisms, some of which are pathogens of clinical relevance. The fourth compendium is based on an in-silico (i.e., simulated) network. Each compendium consists of hundreds of microarray experiments, which include a wide range of genetic, drug, and environmental perturbations (or in the in-silico network case, simulations thereof). Network predictions will be evaluated on a subset of known interactions for each organism, or on the known network for the in-silico case.","","https://www.synapse.org/#!Synapse:syn2787209/wiki/70349","completed","intermediate","1","https://doi.org/10.1038/nmeth.2016","2010-06-09","2010-10-31","2023-08-25 16:43:43","2023-11-14 19:36:08" -"194","nlp-sandbox-date-annotation","NLP Sandbox Date Annotation","Identify dates in clinical notes","An NLP Sandbox Date Annotator takes as input a clinical note and outputs a list of predicted date annotations found in the clinical note.","","https://www.synapse.org/#!Synapse:syn22277123/wiki/609134","completed","intermediate","1","https://doi.org/10.7303/syn22277123","2021-06-04","2023-09-01","2023-08-25 16:45:22","2023-11-15 22:41:56" -"195","nlp-sandbox-person-name-annotation","NLP Sandbox Person Name Annotation","Identify person names in clinical notes","An NLP Sandbox Person Name Annotator takes as input a clinical note and outputs a list of predicted person name annotations found in the clinical note.","","https://www.synapse.org/#!Synapse:syn22277123/wiki/609134","completed","intermediate","1","https://doi.org/10.7303/syn22277123","2021-06-04","2023-09-01","2023-09-08 16:44:20","2023-09-28 23:59:20" -"196","nlp-sandbox-location-annotation","NLP Sandbox Location Annotation","Identify location information in clinical notes","An NLP Sandbox Location Annotator takes as input a clinical note and outputs a list of predicted location annotations found in the clinical note.","","https://www.synapse.org/#!Synapse:syn22277123/wiki/609134","completed","intermediate","1","https://doi.org/10.7303/syn22277123","2021-06-04","2023-09-01","2023-09-08 16:44:21","2023-09-28 23:59:21" -"197","nlp-sandbox-contact-annotation","NLP Sandbox Contact Annotation","Identify contact information in clinical notes","An NLP Sandbox contact annotator takes as input a clinical note and outputs a list of predicted contact annotations found in the clinical note.","","https://www.synapse.org/#!Synapse:syn22277123/wiki/609134","completed","intermediate","1","https://doi.org/10.7303/syn22277123","2021-06-04","2023-09-01","2023-09-08 16:44:22","2023-09-28 23:59:21" -"198","nlp-sandbox-id-annotation","NLP Sandbox ID Annotation","Identify identifiers in clinical notes","An NLP Sandbox ID annotator takes as input a clinical note and outputs a list of predicted ID annotations found in the clinical note.","","https://www.synapse.org/#!Synapse:syn22277123/wiki/609134","completed","intermediate","1","https://doi.org/10.7303/syn22277123","2021-06-04","2023-09-01","2023-09-08 16:44:22","2023-09-28 23:59:22" -"199","dream-2-bcl6-transcriptomic-target-prediction","DREAM 2 - BCL6 Transcriptomic Target Prediction","Predict BCL6 transcriptomic targets from biological data","A number of potential transcriptional targets of BCL6, a gene that encodes for a transcription factor active in B cells, have been identified with ChIP-on-chip data and functionally validated by perturbing the BCL6 pathway with CD40 and anti-IgM, and by over-expressing exogenous BCL6 in Ramos cell. We subselected a number of targets found in this way (the gold standard positive set), and added a number decoys (genes that have no evidence of being BCL6 targets, named the gold standard negative set), compiling a list of 200 genes in total. Given this list of 200 genes, the challenge consists of identifying which ones are the true targets and which ones are the decoys, using an independent panel of gene topic_3170.","","https://www.synapse.org/#!Synapse:syn3034857/wiki/","completed","intermediate","1","https://doi.org/10.1073/pnas.0437996100","2007-04-19","\N","2023-09-12 21:26:22","2023-10-12 17:53:55" -"200","dream-2-protein-protein-interaction-network-inference","DREAM 2 - Protein-Protein Interaction Network Inference","Predict a protein-protein interaction network of 47 proteins","For many pairs of bait and prey genes, yeast protein-protein interactions were tested in an unbiased fashion using a high saturation, high-stringency variant of the yeast two-hybrid (Y2H) method. A high confidence subset of gene pairs that were found to interact in at least three repetitions of the experiment but that hadn’t been reported in the literature was extracted. There were 47 yeast genes involved in these pairs. Including self interactions, there are a total of 47*48/2 possible pairs of genes that can be formed with these 47 genes. As mentioned above some of these gene pairs were seen to consistently interact in at least three repetitions of the Y2H experiments-these gene pairs form the gold standard positive set. A second set among these gene pairs were seen never to interact in repeated experiments and were not reported as interacting in the literature; we call this the gold standard negative set. Finally in a third set of gene pairs, which we shall call the undecided s...","","https://www.synapse.org/#!Synapse:syn2825374/wiki/","completed","intermediate","1","https://doi.org/10.1126/science.1158684","2007-05-24","\N","2023-09-12 21:26:28","2023-10-12 17:54:00" -"201","dream-2-genome-scale-network-inference","DREAM 2 - Genome-Scale Network Inference","Reconstruct genome-scale networks from microarray data","A panel of single-channel microarrays was collected for a particular microorganism, including some already published and some in-print data. The data was appropriately normalized (to the logarithmic scale). The challenge consists of reconstructing a genome-scale transcriptional network for this organism. The accuracy of network inference will be judged using chromatin precipitation and otherwise experimentally verified Transcription Factor (TF)-target interactions.","","https://www.synapse.org/#!Synapse:syn3034894/wiki/74418","completed","intermediate","1","https://doi.org/10.1371/journal.pbio.0050008","2007-06-05","2007-10-31","2023-09-12 21:26:34","2023-10-12 17:54:03" -"202","dream-2-synthetic-five-gene-network-inference","DREAM 2 - Synthetic Five-Gene Network Inference","Inferring five-gene networks from synthetic data","A synthetic-biology network consisting of 5 interacting genes was created and transfected to an in-vivo model organism. The challenge consists of predicting the connectivity of the five-gene network from in-vivo measurements.","","https://www.synapse.org/#!Synapse:syn3034869/wiki/74411","completed","intermediate","1","https://doi.org/10.1016/j.cell.2009.01.055","2007-06-20","2007-10-31","2023-09-12 21:26:56","2023-10-12 17:54:05" -"203","dream-3-signaling-cascade-identification","DREAM 3 - Signaling Cascade Identification","Inferring signaling cascade dynamics from flow cytometry data","The concentration of four intracellular proteins or phospho-proteins (X1, X2, X3 and X4) participating in a signaling cascade were measured in about 104 cells by antibody staining and flow cytometry. The idea of this challenge is to explore what key aspects of the dynamics and topology of interactions of a signaling cascade can be inferred from incomplete flow cytometry data.","","https://www.synapse.org/#!Synapse:syn3033068/wiki/74362","completed","intermediate","1","","2008-06-01","2008-10-31","2023-09-12 21:27:04","2023-10-12 17:54:08" -"204","dream-3-gene-expression-prediction","DREAM 3 - Gene Expression Prediction","Predicting gene expression from gene datasets","Gene expression time course data is provided for four different strains of yeast (S. Cerevisiae), after perturbation of the cells. The challenge is to predict the rank order of induction/repression of a small subset of genes (the prediction targets) in one of the four strains, given complete data for three of the strains, and data for all genes except the prediction targets in the other strain. You are also allowed to use any information that is in the public domain and are expected to be forthcoming about what information was used.","","https://www.synapse.org/#!Synapse:syn3033083/wiki/74369","completed","intermediate","1","","2008-06-01","2008-10-31","2023-09-12 21:27:12","2023-10-12 17:54:10" -"205","dream-4-predictive-signaling-network-modelling","DREAM 4 - Predictive Signaling Network Modelling","Cell-type specific high-throughput experimental data","This challenge explores the extent to which our current knowledge of signaling pathways, collected from a variety of cell types, agrees with cell-type specific high-throughput experimental data. Specifically, we ask the challenge participants to create a cell-type specific model of signal transduction using the measured activity levels of signaling proteins in HepG2 cell lines. The model, which can leverage prior information encoded in a generic signaling pathway provided in the challenge, should be biologically interpretable as a network, and capable of predicting the outcome of new experiments.","","https://www.synapse.org/#!Synapse:syn2825304/wiki/71129","completed","intermediate","1","","2009-03-09","\N","2023-09-12 21:27:14","2023-10-12 17:54:30" -"206","dream-3-signaling-response-prediction","DREAM 3 - Signaling Response Prediction","Predict missing protein concentrations from a large corpus of measurements","Approximately 10,000 intracellular measurements (fluorescence signals proportional to the concentrations of phosphorylated proteins) and extracellular measurements (concentrations of cytokines released in response to cell stimulation) were acquired in human normal hepatocytes and the hepatocellular carcinoma cell line HepG2 cells. The datasets consist of measurements of 17 phospho-proteins (at 0 min, 30 min, and 3 hrs) and 20 cytokines (at 0 min, 3 hrs, and 24 hrs) in two cell types (normal and cancer) after perturbations to the pathway induced by the combinatorial treatment of 7 stimuli and 7 selective inhibitors.","","https://www.synapse.org/#!Synapse:syn2825325/wiki/","completed","intermediate","1","https://doi.org/10.1126%2Fscisignal.2002212","2009-03-09","\N","2023-09-12 21:27:20","2023-10-12 17:54:33" -"207","dream-4-peptide-recognition-domain-prd-specificity-prediction","DREAM 4 - Peptide Recognition Domain (PRD) Specificity Prediction","Predict binding specificity of peptide-antibody interactions","Many important protein-protein interactions are mediated by peptide recognition domains (PRD), which bind short linear sequence motifs in other proteins. For example, SH3 domains typically recognize proline-rich motifs, PDZ domains recognize hydrophobic C-terminal tails, and kinases recognize short sequence regions around a phosphorylatable residue (Pawson, 2003). Given the sequence of the domains, the challenge consists of predicting a position weight matrix (PWM) that describes the specificity profile of each of the given domains to their target peptides. Any publicly accessible peptide specificity information available for the domain may be used.","","https://www.synapse.org/#!Synapse:syn2925957/wiki/72976","completed","intermediate","1","","2009-06-01","2009-10-31","2023-09-12 21:27:35","2023-10-12 17:54:35" -"208","dream-5-transcription-factor-dna-motif-recognition-challenge","DREAM 5 - Transcription-Factor, DNA-Motif Recognition Challenge","Predict binding intensities for transcription factors from motifs","Transcription factors (TFs) control the expression of genes through sequence-specific interactions with genomic DNA. Different TFs bind preferentially to different sequences, with the majority recognizing short (6-12 base), degenerate ‘motifs’. Modeling the sequence specificities of TFs is a central problem in understanding the function and evolution of the genome, because many types of genomic analyses involve scanning for potential TF binding sites. Models of TF binding specificity are also important for understanding the function and evolution of the TFs themselves. The challenge consists of predicting the signal intensities for the remaining TFs.","","https://www.synapse.org/#!Synapse:syn2887863/wiki/72185","completed","intermediate","1","https://doi.org/10.1038/nbt.2486","2011-06-01","2011-09-30","2023-09-12 21:27:41","2023-10-12 17:54:36" -"209","dream-5-epitope-antibody-recognition-ear-challenge","DREAM 5 - Epitope-Antibody Recognition (EAR) Challenge","Predict the binding specificity of peptide-antibody interactions","Humoral immune responses are mediated through antibodies. About 1010 to 1012 different antigen binding sites called paratopes are generated by genomic recombination. These antibodies are capable to bind to a variety of structures ranging from small molecules to protein complexes, including any posttranslational modification thereof. When studying protein-antibody interactions, two types of epitopes (the region paratopes interact with) are to be distinguished from each other-i) conformational and ii) linear epitopes. All potential linear epitopes of a protein can be represented by short peptides derived from the primary amino acid sequence. These peptides can be synthesized and arrayed on solid supports, e.g. glass slides (see Lorenz et al., 2009 [1]). By incubating these peptide arrays with antibody mixtures such as human serum or plasma, peptides can be determined that interact with antibodies in a specific fashion.","","https://www.synapse.org/#!Synapse:syn2820433/wiki/71017","completed","intermediate","1","","2010-06-09","\N","2023-09-12 21:27:44","2023-10-12 17:54:39" -"210","dream-gene-expression-prediction-challenge","DREAM Gene Expression Prediction Challenge","Predict gene expression levels from promoter sequences in eukaryotes","The level by which genes are transcribed is determined in large part by the DNA sequence upstream to the gene, known as the promoter region. Although widely studied, we are still far from a quantitative and predictive understanding of how transcriptional regulation is encoded in gene promoters. One obstacle in the field is obtaining accurate measurements of transcription derived by different promoters. To address this, an experimental system was designed to measure the transcription derived by different promoters, all of which are inserted into the same genomic location upstream to a reporter gene -a yellow florescence protein gene (YFP). The challenge consists of the prediction of the promoter activity given a promoter sequence and a specific experimental condition. To study a set of promoters that share many elements of the regulatory program, and thus are suitable for computational learning, the data pertains to promoters of most of the ribosomal protein genes (RP) of yeast (S....","","https://www.synapse.org/#!Synapse:syn2820426/wiki/71010","completed","intermediate","1","","2010-07-09","\N","2023-09-12 21:28:00","2023-10-19 23:32:10" -"211","dream-5-systems-genetics-challenge","DREAM 5 - Systems Genetics Challenge","Predict disease phenotypes and infer gene networks from systems genetics data","The central goal of systems biology is to gain a predictive, system-level understanding of biological networks. This can be done, for example, by inferring causal networks from observations on a perturbed biological system. An ideal experimental design for causal inference is randomized, multifactorial perturbation. The recognition that the genetic variation in a segregating population represents randomized, multifactorial perturbations (Jansen and Nap (2001), Jansen (2003)) gave rise to Systems Genetics (SG), where a segregating or genetically randomized population is genotyped for many DNA variants, and profiled for phenotypes of interest (e.g. disease phenotypes), gene expression, and potentially other ‘omics’ variables (protein expression, metabolomics, DNA methylation, etc.; Figure 1. Figure 1 was taken from Jansen and Nap (2001)). In this challenge we explore the use of Systems Genetics data for elucidating causal network models among genes, i.e. Gene Networks (DREAM5 SYSGEN...","","https://www.synapse.org/#!Synapse:syn2820440/wiki/","completed","intermediate","1","","2010-07-09","\N","2023-09-12 21:28:10","2023-10-12 17:54:42" -"212","dream-6-estimation-of-model-parameters-challenge","DREAM 6 - Estimation of Model Parameters Challenge","Challenge to estimate model parameters","Given the complete model structures (including expressions for the kinetic rate laws) for three gene regulatory networks, participants are asked to develop and/or apply optimization methods, including the selection of the most informative experiments, to accurately estimate parameters and predict outcomes of perturbations in Systems Biology models.","","https://www.synapse.org/#!Synapse:syn2841366/wiki/71372","completed","intermediate","1","","2011-06-01","2011-10-31","2023-09-12 21:28:12","2023-10-12 17:54:45" -"213","dream-6-flowcap2-molecular-classification-of-acute-myeloid-leukemia-challenge","DREAM 6 - FlowCAP2 Molecular Classification of Acute Myeloid Leukemia Challenge","Diagnose acute myeloid leukemia from patient data using flow cytometry","Flow cytometry (FCM) has been widely used by immunologists and cancer biologists for more than 30 years as a biomedical research tool to distinguish different cell types in mixed populations, based on the expression of cellular markers. It has also become a widely used diagnostic tool for clinicians to identify abnormal cell populations associated with disease. In the last decade, advances in instrumentation and reagent technologies have enabled simultaneous single-cell measurement of tens of surface and intracellular markers, as well as tens of signaling molecules, positioning FCM to play an even bigger role in medicine and systems biology [1,2]. However, the rapid expansion of FCM applications has outpaced the functionality of traditional analysis tools used to interpret FCM data such that scientists are faced with the daunting prospect of manually identifying interesting cell populations in 20 dimensional data from a collection of millions of cells. For these reasons a reliable...","","https://www.synapse.org/#!Synapse:syn2887788/wiki/72178","completed","intermediate","1","https://doi.org/10.1038/nmeth.2365","2011-06-01","2011-09-30","2023-09-12 21:28:19","2023-11-14 19:36:22" -"214","dream-6-alternative-splicing-challenge","DREAM 6 - Alternative Splicing Challenge","Compare mRNA-seq methods on primate and rhino transcripts","The goal of the mRNA-seq alternative splicing challenge is to assess the accuracy of the reconstruction of alternatively spliced mRNA transcripts from Illumina short-read mRNA-seq. Reconstructed transcripts will be scored against Pacific Biosciences long-read mRNA-seq. The ensuing analysis of the transcriptomes from mandrill and rhinoceros fibroblasts and their derived induced pluripotent stem cells (iPSC), as well as the transcriptome for human Embrionic Stem Cells (hESC) is an opportunity to discover novel biology as well as investigate species-bias of different methods.","","https://www.synapse.org/#!Synapse:syn2817724/wiki/","completed","intermediate","1","","2011-08-09","\N","2023-09-12 21:28:25","2023-10-12 17:54:50" -"215","causalbench-challenge","CausalBench Challenge","Gene network inference from single-cell perturbation data","Mapping gene-gene interactions in cellular systems is a fundamental step in early-stage drug discovery that helps generate hypotheses on what molecular mechanisms may effectively be targeted by potential future medicines. In the CausalBench Challenge, we invite the machine-learning community to advance the state-of-the-art in deriving gene-gene networks from large-scale real-world perturbational single-cell datasets to improve our ability to glean causal insights into disease-relevant biology.","","https://www.gsk.ai/causalbench-challenge/","completed","intermediate","15","https://doi.org/10.48550/arXiv.2308.15395","2023-03-01","2023-04-21","2023-09-12 21:28:25","2023-11-14 19:36:27" -"216","iclr-computational-geometry-and-topology-challenge-2022","ICLR Computational Geometry & Topology Challenge 2022","Advancing computational geometry and topology with python","The purpose of this challenge is to foster reproducible research in geometric (deep) learning, by crowdsourcing the open-source implementation of learning algorithms on manifolds. Participants are asked to contribute code for a published/unpublished algorithm, following Scikit-Learn/Geomstats' or pytorch's APIs and computational primitives, benchmark it, and demonstrate its use in real-world scenarios.","","https://github.com/geomstats/challenge-iclr-2022","completed","intermediate","\N","","\N","2022-04-04","2023-09-13 16:54:06","2023-10-19 23:28:44" -"217","iclr-computational-geometry-and-topology-challenge-2021","ICLR Computational Geometry & Topology Challenge 2021","Advancing computational geometry and topology with python","The purpose of this challenge is to push forward the fields of computational differential geometry and topology, by creating the best data analysis, computational method, or numerical experiment relying on state-of-the-art geometric and topological Python packages.","","https://github.com/geomstats/challenge-iclr-2021","completed","intermediate","\N","https://doi.org/10.48550/arXiv.2108.09810","\N","2021-05-02","2023-09-13 17:02:12","2023-10-19 23:28:44" -"218","genedisco-challenge","GeneDisco Challenge","Exploring experimental design with active learning for genetics","The GeneDisco challenge is a machine learning community challenge for evaluating batch active learning algorithms for exploring the vast experimental design space in genetic perturbation experiments. Genetic perturbation experiments, using for example CRISPR technologies to perturb the genome, are a vital component of early-stage drug discovery, including target discovery and target validation. The GeneDisco challenge is organized in conjunction with the Machine Learning for Drug Discovery workshop at ICLR-22.","","https://www.gsk.ai/genedisco-challenge/","completed","intermediate","15","https://doi.org/10.48550/arXiv.2110.11875","2022-01-31","2022-03-31","2023-09-13 17:20:30","2023-10-19 23:32:43" -"219","hidden-treasures-warm-up","Hidden Treasures: Warm Up","Assess genome sequencing software accuracy with unknown variants","In the context of human genome sequencing, software pipelines typically involve a wide range of processing elements, including aligning sequencing reads to a reference genome and subsequently identifying variants (differences). One way of assessing the performance of such pipelines is by using well-characterized datasets such as Genome in a Bottle’s NA12878. However, because the existing NGS reference datasets are very limited and have been widely used to train/develop software pipelines, benchmarking of pipeline performance would ideally be done on samples with unknown variants. This challenge will provide a unique opportunity for participants to investigate the accuracy of their pipelines by testing the ability to find in silico injected variants in FASTQ files from exome sequencing of reference cell lines. It will be a warm up for the community ahead of a more difficult in silico challenge to come in the fall. This challenge will provide users with a FASTQ file of a NA12878 se...","","https://precision.fda.gov/challenges/1","completed","intermediate","6","","2017-07-17","2017-09-13","2023-09-13 23:31:39","2023-10-12 17:55:23" -"220","data-management-and-graph-extraction-for-large-models-in-the-biomedical-space","Data management and graph extraction for large models in the biomedical space","Advancing biomedical knowledge graphs","This fall, CMU Libraries is hosting a hackathon in partnership with DNAnexus on the topic of data management and graph extraction for large models in the biomedical space. The hackathon will be held in person at CMU, October 19-21, 2023. The hackathon is a collaborative, rather than competitive, event, with each team working on a dedicated part of the problem. The teams will be focused on the following topics-1) Knowledge graph-based validation for variant (genomic) assertions; 2) Continuous monitoring for RLHF and flexible infrastructure for layering assertions with rollback; 3) Flexible tokenization of complex data types; 4) Assertion tracking in large models; 5) Column headers for data harmonization. The outputs are often published as preprints or on the F1000 hackathon channel. Contact Ben Busby (bbusby@dnanexus.com) with any questions about the hackathon or serving as a team lead.","","https://library.cmu.edu/about/news/2023-08/hackathon-2023","completed","intermediate","\N","","2023-10-19","2023-10-21","2023-09-13 23:32:59","2023-11-14 19:36:32" -"221","cagi2-asthma-twins","CAGI2: Asthma discordant monozygotic twins","Identify genetic differences between asthmatic and healthy twins","The dataset includes whole genomes of 8 pairs of discordant monozygotic twins (randomly numbered from 1 to 16) that is, in each pair identical twins one has asthma and one does not. In addition, RNA sequencing data for each individual is provided. One of the twins in each pair suffers from asthma while the other twin is healthy.","","https://genomeinterpretation.org/cagi2-asthma-twins.html","completed","intermediate","\N","","\N","2011-10-06","2023-09-28 18:19:48","2023-10-12 18:11:42" -"222","cagi4-bipolar","CAGI4: Bipolar disorder","Predicting bipolar disorder from exome data","Bipolar disorder (BD) is a serious mental illness characterized by recurrent episodes of manias and depression, which are syndromes of abnormal mood, thinking and behavior. It affects 1.0-4.5% of the population [1], and it is among the major causes of disability worldwide. This challenge involved the prediction of which of a set of individuals have been diagnosed with bipolar disorder, given exome data. 500 of the 1000 exome samples were provided for training.","","https://genomeinterpretation.org/cagi4-bipolar.html","completed","intermediate","\N","","\N","2016-04-04","2023-09-28 18:19:48","2023-09-28 18:25:17" -"223","cagi3-brca","CAGI3: BRCA1 & BRCA2","Assess hereditary cancer risk via BRCA gene analysis","In normal cells, the BRCA1 and BRCA2 genes are involved in homologous recombination for double strand break repair and ensure the stability of a cell's genetic material. Mutations in these genes have been linked to development of breast and ovarian cancer. Myriad Genetics created the BRACAnalysis test in order to assess a woman’s risk of developing hereditary breast or ovarian cancer based on detection of mutations in the BRCA1 and BRCA2 genes. This test has become the standard of care in identification of individuals with hereditary breast and ovarian cancer (HBOC) syndrome. It is based on proprietary methods.","","https://genomeinterpretation.org/cagi3-brca.html","completed","intermediate","\N","","\N","2013-04-25","2023-09-28 18:19:48","2023-10-19 23:32:48" -"224","cagi2-breast-cancer-pkg","CAGI2: Breast cancer pharmacogenomics","Exploring CHEK2 as a candidate gene for cancer susceptibility","Cell-cycle-checkpoint kinase 2 (CHEK2; OMIM #604373) is a protein that plays an important role in the maintenance of genome integrity and in the regulation of the G2/M cell cycle checkpoint. CHEK2 has been shown to interact with other proteins involved in DNA repair processes such as BRCA1 and TP53. These findings render CHEK2 an 23 attractive candidate susceptibility gene for a variety of cancers.","","https://genomeinterpretation.org/cagi2-breast-cancer-pkg.html","completed","intermediate","\N","","\N","2011-10-06","2023-09-28 18:19:48","2023-10-12 17:46:22" -"225","cagi4-2eqtl","CAGI4: eQTL causal SNPs","Identify regulatory variants causing gene expression differences","Identifying the causal alleles responsible for variation in expression of human genes has been particularly difficult. This is an important problem, as genome-wide association studies (GWAS) suggest that much of the variation underlying common traits and diseases maps within regions of the genome that do not encode protein. A massively parallel reporter assay (MPRA) has been applied to thousands of single nucleotide polymorphisms (SNPs) and small insertion/deletion polymorphisms in linkage disequilibrium (LD) with cis-expression quantitative trait loci (eQTLs). The results identify variants showing differential expression between alleles. The challenge is to identify the regulatory sequences and the expression-modulating variants (emVars) underlying each eQTL and estimate their effects in the assay.","","https://genomeinterpretation.org/cagi4-2eqtl.html","completed","intermediate","\N","","\N","2016-04-04","2023-09-28 18:19:48","2023-09-29 3-58-33" -"226","cagi1-cbs","CAGI1: CBS","Seeking to understand CBS enzyme function in cysteine production","CBS is a vitamin-dependent enzyme involved in cysteine biosynthesis. The human CBS requires two cofactors for function, vitamin B6 and heme. Homocystinuria due to CBS deficiency (OMIM #236200) is a recessive inborn error of sulfur amino acid metabolism.","","https://genomeinterpretation.org/cagi1-cbs.html","completed","intermediate","\N","","\N","2010-12-10","2023-09-28 18:19:48","2023-10-12 17:46:07" -"227","cagi2-cbs","CAGI2: CBS","Developing treatment for homocystinuria caused by cbs deficiency","CBS is a vitamin-dependent enzyme involved in cysteine biosynthesis. The human CBS requires two cofactors for function, vitamin B6 and heme. Homocystinuria due to CBS deficiency (OMIM #236200) is a recessive inborn error of sulfur amino acid metabolism.","","https://genomeinterpretation.org/cagi2-cbs.html","completed","intermediate","\N","","\N","2011-10-06","2023-09-28 18:19:48","2023-11-15 22:46:32" -"228","cagi1-chek2","CAGI1: CHEK2","Variants in the ATM & CHEK2 genes are associated with breast cancer","Predictors will be provided with 41 rare missense, nonsense, splicing, and indel variants in CHEK2.","","https://genomeinterpretation.org/cagi1-chek2.html","completed","intermediate","\N","","\N","2010-12-10","2023-09-28 18:19:48","2023-10-19 23:32:57" -"229","cagi3-fch","CAGI3: FCH","Seeking to understand genetic basis of common hyperlipidemia disorder","Familial combined hyperlipidemia (FCH; OMIM 14380) the most prevalent hyperlipidemia, is a complex metabolic disorder characterized by variable occurrence of elevated low-density lipoprotein cholesterol (LDL-C) level and high triglycerides (TG)—a condition that is commonly associated with coronary artery disease (CAD).","","https://genomeinterpretation.org/cagi3-fch.html","completed","intermediate","\N","","\N","2013-04-25","2023-09-28 18:19:48","2023-11-01 22:26:44" -"230","cagi3-ha","CAGI3: HA","Raising HDL levels to reduce heart disease risk","Hypoalphalipoproteinemia (HA; OMIM #604091) is characterized by severely decreased serum high-density lipoprotein cholesterol (HDL-C) levels and low apolipoprotein A1 (APOA1). Low HDL-C is a risk factor for coronary artery disease.","","https://genomeinterpretation.org/cagi3-ha.html","completed","intermediate","\N","","\N","2013-04-25","2023-09-28 18:19:48","2023-11-15 22:46:55" -"231","cagi2-croshn-s","CAGI2: Crohn's disease","Seeking genes linked to Crohn's, an inflammatory bowel disease","Crohn's disease (CD [MIM 266600]) a form of inflammatory bowel disease (IBD) is a complex genetic disorder characterized by chronic relapsing inflammation that can involve any part of the gastrointestinal tract.","","https://genomeinterpretation.org/cagi2-croshn-s.html","completed","intermediate","\N","","\N","2011-10-06","2023-09-28 18:19:48","2023-11-15 22:46:26" -"232","cagi3-crohn-s","CAGI3: Crohn's disease","Understanding the genetics behind Crohn's disease","Crohn's disease (CD [MIM 266600]) a form of inflammatory bowel disease (IBD) is a complex genetic disorder characterized by chronic relapsing inflammation that can involve any part of the gastrointestinal tract.","","https://genomeinterpretation.org/cagi3-crohn-s.html","completed","intermediate","\N","","\N","2013-04-25","2023-09-28 18:19:48","2023-11-15 22:46:27" -"233","cagi4-chron-s-exome","CAGI4: Crohn's exomes","Seeking to understand genetic basis of Crohn's bowel disease","Crohn's disease (CD [MIM 266600]) a form of inflammatory bowel disease (IBD) is a complex genetic disorder characterized by chronic relapsing inflammation that can involve any part of the gastrointestinal tract.","","https://genomeinterpretation.org/cagi4-chron-s-exome.html","completed","intermediate","\N","","\N","2016-04-04","2023-09-28 18:19:48","2023-11-15 22:46:23" -"234","cagi4-hopkins","CAGI4: Hopkins clinical panel","Exonic sequences of 83 genes linked to 14 diseases analyzed","The Johns Hopkins challenge, provided by the Johns Hopkins DNA Diagnostic Laboratory (http://www.hopkinsmedicine.org/dnadiagnostic), comprised of exonic sequence for 83 genes associated with one of 14 disease classes, including 5 decoys","","https://genomeinterpretation.org/cagi4-hopkins.html","completed","intermediate","\N","","\N","2016-04-04","2023-09-28 18:19:48","2023-10-12 17:45:27" -"235","cagi2-mouse-exomes","CAGI2: Mouse exomes","Predict causative variants from exome sequencing data","Predictors were given SNVs and indels found from exome sequencing. Causative variants had been identified for the L11Jus74 and Sofa phenotypes by the use of traditional breeding crosses,47 and the predictions were compared to these results, which were unpublished at the time of the CAGI submissions. The L11Jus74 phenotype is caused by two SNVs (chr11-102258914A> and chr11-77984176A>T), whereas a 15-nucleotide deletion in the Pfas gene is responsible for the Sofa phenotype. The predictions for Frg and Stn phenotypes could not be compared to experimental data, as the causative variants could not successfully be mapped by linkage","","https://genomeinterpretation.org/cagi2-mouse-exomes.html","completed","intermediate","\N","","\N","2011-10-06","2023-09-28 18:19:48","2023-10-12 17:45:19" -"236","cagi3-mrn-mre11","CAGI3: MRE11","Genomes are subject to constant threat by damaging agents that generate dna","Predict probability of pathogenicity (a number between 0 and 1) for individual rare variants of MRE11 and NBS1.","","https://genomeinterpretation.org/cagi3-mrn.html","completed","intermediate","\N","","\N","2013-04-25","2023-09-28 18:19:48","2023-11-15 22:47:19" -"237","cagi4-naglu","CAGI4: NAGLU","Predicting enzymatic activity of NAGLU mutants","NAGLU is a lysosomal glycohydrolyase. Deficiency of NAGLU causes the rare disorder Mucopolysaccharidosis IIIB or Sanfilippo B disease. Naturally occurring NAGLU mutants have been assayed for enzymatic activity in transfected cell lysates. The challenge is to predict the fractional activity of each mutant protein compared to the wild-type enzyme.","","https://genomeinterpretation.org/cagi4-naglu.html","completed","intermediate","\N","","\N","2016-04-04","2023-09-28 18:19:48","2023-11-15 22:47:24" -"238","cagi4-npm-alk","CAGI4: NPM: ALK","Predicting kinase activity of NPM-ALK fusion mutants","NPM-ALK is a fusion protein in which the ALK tyrosine kinase is constitutively activated, contributing to cancer. NPM-ALK constructs with mutations in the kinase domain have been assayed in extracts of transfected cells. The challenge is to predict the kinase activity and the Hsp90 binding affinity of the mutant proteins relative to the reference NPM-ALK fusion protein.","","https://genomeinterpretation.org/cagi4-npm-alk.html","completed","intermediate","\N","","\N","2016-04-04","2023-09-28 18:19:48","2023-11-15 22:47:32" -"239","cagi3-mrn-nbs1","CAGI3: NBS1","Predicting Pathogenicity of Rare MRE11 and NBS1 Variants","Predict probability of pathogenicity (a number between 0 and 1) for individual rare variants of MRE11 and NBS1.","","https://genomeinterpretation.org/cagi3-mrn.html","completed","intermediate","\N","","\N","2013-04-25","2023-09-28 18:19:48","2023-10-16 18:38:55" -"240","cagi3-p16","CAGI3: p16","Assessing p16 protein variants' effects on cell growth","Evaluate how different variants of p16 protein impact its ability to block cell proliferation.","","https://genomeinterpretation.org/cagi3-p16.html","completed","intermediate","\N","","\N","2013-04-25","2023-09-28 18:19:48","2023-10-20 23:28:57" -"241","cagi2-p53","CAGI2: p53 reactivation","Predictors are asked to submit predictions on the effect of the cancer rescue","The transcription factor p53 is a central tumor suppressor protein that controls DNA repair, cell cycle arrest, and apoptosis (programmed cell death). About half of human cancers have p53 mutations that inactivate p53. Over 250,000 US deaths yearly are due to tumors that express full-length p53 that has been inactivated by a single point mutation. For the past several years, the group of Rick Lathrop at University of California, Irvine, has been engaged in a complete functional census of p53 second-site suppressor (“cancer rescue”) mutations. These cancer rescue mutations are additional amino acids changes (to otherwise cancerous p53 mutations), which have been found to rescue p53 tumor suppressor function, reactivating otherwise inactive p53. These intragenic rescue mutations reactivate cancer mutant p53 in yeast and human cell assays by providing structural changes that compensate for the cancer mutation.","","https://genomeinterpretation.org/cagi2-p53.html","completed","intermediate","\N","","\N","2011-10-06","2023-09-28 18:19:48","2023-10-20 23:28:58" -"242","cagi1-pgp","CAGI1: PGP","CAGI challenges utilizing public genomic and phenotypic data resources","Participants in the project make their full sequence and phenotypic profile data publicly available. The four CAGI challenges were based on prerelease samples from this resource.","","https://genomeinterpretation.org/cagi1-pgp.html","completed","intermediate","\N","","\N","2010-12-10","2023-09-28 18:19:48","2023-09-27 21:05:22" -"243","cagi2-pgp","CAGI2: PGP","CAGI challenges utilizing public genomic and phenotypic data resources","Participants in the project make their full sequence and phenotypic profile data publicly available. The four CAGI challenges were based on prerelease samples from this resource.","","https://genomeinterpretation.org/cagi2-pgp.html","completed","intermediate","\N","","\N","2011-10-06","2023-09-28 18:19:48","2023-09-27 21:05:23" -"244","cagi3-pgp","CAGI3: PGP","CAGI challenges utilizing public genomic and phenotypic data resources","Participants in the project make their full sequence and phenotypic profile data publicly available. The four CAGI challenges were based on prerelease samples from this resource.","","https://genomeinterpretation.org/cagi3-pgp.html","completed","intermediate","\N","","\N","2013-04-25","2023-09-28 18:19:48","2023-09-27 21:05:23" -"245","cagi4-pgp","CAGI4: PGP","CAGI challenges utilizing public genomic and phenotypic data resources","Participants in the project make their full sequence and phenotypic profile data publicly available. The four CAGI challenges were based on prerelease samples from this resource.","","https://genomeinterpretation.org/cagi4-pgp.html","completed","intermediate","\N","","\N","2016-04-04","2023-09-28 18:19:48","2023-11-01 22:26:17" -"246","cagi4-pyruvate-kinase","CAGI4: Pyruvate kinase","Predicting mutation impacts on pyruvate kinase activity and regulation","Pyruvate kinase catalyzes the last step in glycolysis and is regulated by allosteric effectors. Variants in the gene encoding the isozymes expressed in red blood cells and liver, including missense variants mapping near the effector binding sites, cause PK deficiency. A large set of single amino acid mutations in the liver enzyme has been assayed in E. coli extracts for the effect on allosteric regulation of enzyme activity. The challenge is to predict the impacts of mutations on enzyme activity and allosteric regulation.","","https://genomeinterpretation.org/cagi4-pyruvate-kinase.html","completed","intermediate","\N","","\N","2015-01-11","2023-09-28 18:19:48","2023-11-01 22:26:25" -"247","cagi2-rad50","CAGI2: RAD50","Assessing RAD50 variants for breast cancer risk","RAD50 is a candidate intermediate-risk breast cancer susceptibility gene. The RAD50 data provided for CAGI challenge include a list of potentially interesting sequence variants observed from sequencing RAD50 gene in about 1,400 breast cancer cases and 1,200 ethnically matched controls. Variants in the list were observed between 1 and 20 times.","","https://genomeinterpretation.org/cagi2-rad50.html","completed","intermediate","\N","","\N","2011-10-06","2023-09-28 18:19:48","2023-11-15 22:47:40" -"248","cagi2-risksnps","CAGI2: riskSNPs","Exploring molecular mechanisms linking SNPs to disease risk","The goal of this experiment is to explore current understanding of the molecular level mechanisms underlying associations between SNPs and disease risk, incorporating expertise in each of the known mechanism areas, and as far as possible assigning possible mechanisms for each association locus. The correct mechanisms are unknown, so there can be no ranking of accuracy-that is not the point of the experiment. Rather, the goal is to ascertain which mechanisms appear most relevant, how confidently they can be assigned, and what fraction of loci can currently be assigned plausible mechanisms.","","https://genomeinterpretation.org/cagi2-risksnps.html","completed","intermediate","\N","","\N","2011-10-06","2023-09-28 18:19:48","2023-10-19 23:33:11" -"249","cagi3-risksnps","CAGI3: riskSNPs","Exploring molecular mechanisms linking SNPs to disease risk","The goal of this experiment is to explore current understanding of the molecular level mechanisms underlying associations between SNPs and disease risk, incorporating expertise in each of the known mechanism areas, and as far as possible assigning possible mechanisms for each association locus. The correct mechanisms are unknown, so there can be no ranking of accuracy-that is not the point of the experiment. Rather, the goal is to ascertain which mechanisms appear most relevant, how confidently they can be assigned, and what fraction of loci can currently be assigned plausible mechanisms.","","https://genomeinterpretation.org/cagi3-risksnps.html","completed","intermediate","\N","","\N","2013-04-25","2023-09-28 18:19:48","2023-10-19 23:33:13" -"250","cagi2-nav1-5","CAGI2: SCN5A","Predict the effect of SCN5A mutants in cardiac electrophysiology","The cardiac action potential (AP) is the sum of a number of distinct ionic currents. It can be divided into five phases (phase 0‐4). From pacemaker cells of the SA node the initial depolarizing wave front will spread throughout the cardiomyocytes via gap junctions. If the depolarization is sufficient voltage‐dependent sodium channels (Nav1.5) are activated and allow Na+ influx. This results in a further depolarization of the membrane which will lead to opening of even more Nav channels. This positive feedback mechanism is seen as the rapid upstroke in the initial phase (phase 0) of the action potential. Nav1.5 is encoded by SCN5A and mutations in this gene have been associated with various diseases such as Atrial fibrillation, Long QT syndrome, Cardiac Conduction Defect, Sick Sinus Disease, and Brugada Syndrome (BrS).","","https://genomeinterpretation.org/cagi2-nav1.5.html","completed","intermediate","\N","","\N","2011-10-06","2023-09-28 18:19:48","2023-11-14 19:36:54" -"251","cagi2-mr-1","CAGI2: Shewanella oneidensis strain MR-1","How MR-1 affect the fitness of that gene in a given condition","Predictors are asked to submit predictions on how insertions in the given gene of MR-1 affect the fitness of that gene in a given condition (stressor).","","https://genomeinterpretation.org/cagi2-mr-1.html","completed","intermediate","\N","","\N","2011-10-06","2023-09-28 18:19:55","2023-11-14 19:37:40" -"252","cagi3-mr-1","CAGI3: Shewanella oneidensis strain MR-1","How MR-1 affect the fitness of that gene in a given condition","Predictors are asked to submit predictions on how insertions in the given gene of MR-1 affect the fitness of that gene in a given condition (stressor).","","https://genomeinterpretation.org/cagi3-mr-1.html","completed","intermediate","\N","","\N","2013-04-25","2023-09-28 18:20:01","2023-11-14 19:37:47" -"253","cagi4-sickkids","CAGI4: SickKids","Match genome sequence to clinical descriptions","Realizing the promise of precision medicine will require developing methods for interpreting genome sequence data to infer individuals’ phenotypic traits and predispositions to disease. This challenge involves 25 children with suspected genetic disorders who were referred for clinical genome sequencing. Predictors are given their genome sequences and their clinical phenotypic descriptions, as provided to the diagnostic laboratory, and asked to predict which genome corresponds to which clinical description. Additionally, identify the diagnostic variants underlying the predictions. Optionally, identify predictive secondary variants conferring high risk of other diseases whose phenotypes are not reported in the clinical descriptions.","","https://genomeinterpretation.org/cagi4-sickkids.html","completed","intermediate","\N","","\N","2016-04-04","2023-09-28 18:19:48","2023-11-14 19:38:30" -"254","cagi4-sumo-ligase","CAGI4: SUMO ligase","Predict effect of the variants on SUMO ligase","SUMO ligase identifies target proteins and covalently attaches SUMO to them, thereby modulating the functions of hundreds of proteins including proteins implicated in cancer, neurodegeneration, and other diseases. A large library of missense mutations in human SUMO ligase has been assessed for competitive growth in a high-throughput yeast-based complementation assay. The challenge is to predict the effect of mutations on function, as measured by the change in fractional representation of each mutant SUMO ligase clone, relative to wild-type clones, in a competitive yeast growth assay.","","https://genomeinterpretation.org/cagi4-sumo-ligase.html","completed","intermediate","\N","","\N","2016-04-04","2023-09-28 18:19:48","2023-11-14 19:38:48" -"255","cagi3-splicing","CAGI3: TP53 splicing","Which TP53 mutations potentially contribute to cancer","The function of exonic splicing regulatory elements can be undermined by DNA sequence variation and in some cases can contribute to pathogenesis. Thousands of disease-causing mutations disrupt exonic splicing regulatory elements. These data suggest that >25 percent of missense mutations may impact pre-mRNA splicing rather than mRNA translation. Using minigene constructs derived from a fragment of the TP53 gene, we have experimentally determined if each mutation influences splicing fidelity in HEK293T cells. We hope that CAGI participants will be able to predict the outcome of our experiments. A long-term goal will be the computational prioritization of disease-causing mutations prior to experimental validation. This contribution is expected to have major impacts in understanding the pathogenic basis of disease-causing mutations.","","https://genomeinterpretation.org/cagi3-splicing.html","completed","intermediate","\N","","\N","2013-04-25","2023-09-28 18:19:48","2023-11-14 19:39:00" -"256","cagi4-warfarin","CAGI4: Warfarin exomes","Predict the therapeutic doses of warfarin","With over 33 million prescriptions in 2011, warfarin is the most commonly used anticoagulant for preventing thromboembolic events. Warfarin has a twenty-fold inter-individual dose variability and a narrow therapeutic index, and it is responsible for a third of adverse drug event hospitalizations in older Americans [2]. Alternatives to warfarin, such as direct thrombin inhibitors and factor Xa inhibitors, are now available. However, these are more expensive, irreversible, and may cause a higher rate of acute coronary events compared to warfarin [3,4]. Thus, warfarin remains a mainstay of anticoagulant therapy, and better methods of dosing warfarin will lead to fewer adverse events due to overcoagulation.","","https://genomeinterpretation.org/cagi4-warfarin.html","completed","intermediate","\N","","\N","2016-04-04","2023-09-28 18:19:48","2023-11-14 19:39:08" -"257","cagi6-calmodulin","CAGI6: Calmodulin","Predict competitive growth score of different Calmodulin variants","Calmodulin (CaM) is a ubiquitous calcium (Ca2+) sensor protein interacting with more than 200 molecular partners, thereby regulating a variety of biological processes. Missense point mutations in the genes encoding CaM have been associated with ventricular tachycardia and sudden cardiac death. A library encompassing up to 17 point mutations was assessed by far-UV circular dichroism (CD) by measuring melting temperature (Tm) and percentage of unfolding (%unfold) upon thermal denaturation at pH and salt concentration that mimic the physiological conditions. The challenge is to predict- the Tm and %unfold values for isolated CaM variants under Ca2+-saturating conditions (Ca2+-CaM) and in the Ca2+-free (apo) state; whether the point mutation stabilizes or destabilizes the protein (based on Tm and %unfold).","","https://genomeinterpretation.org/cagi6-cam.html","completed","intermediate","1","","\N","2021-12-31","2023-09-28 18:19:48","2023-11-15 22:47:52" -"258","cagi2-splicing","CAGI2: splicing","Compare exons to understand the mechanisms underlying pre-mRNA splicing errors","Accurate precursor mRNA (pre-mRNA) splicing is required for the expression of protein coding genes from the human genome. In this process, intervening sequences (introns) are removed from pre-mRNA and coding/regulatory sequences (exons) are ligated together generating a mature mRNA. A large ribonucleoprotein machine called the spliceosome assembles de novo upon every nascent intron and catalyzes the chemical steps of splicing.","","https://genomeinterpretation.org/cagi2-splicing.html","completed","intermediate","\N","","\N","2011-10-06","2023-09-28 18:19:48","2023-10-18 15:32:55" -"259","cagi6-lc-arsa","CAGI6: ARSA","Predict the effect of naturally occurring missense mutations","Metachromatic Leukodystrophy (MLD) is an autosomal recessive, lysosomal-storage disease caused by mutations in Arylsulfatase A (ARSA) and toxic accumulation of sulfatide substrate. Genome sequencing has revealed hundreds of protein-altering, ARSA missense variants, but the functional effect of most variants remains unknown. ARSA enzyme activity using a high-throughput cellular assay was measured for a large set of variants of known significance and variants of unknown significance. The challenge is to predict the fractional enzyme activity of each mutant protein compared to the wildtype protein.","","https://genomeinterpretation.org/cagi6-lc-arsa.html","completed","intermediate","1","","\N","2022-11-16","2023-09-28 18:20:23","2023-11-14 19:39:42" -"260","predict-hits-for-the-wdr-domain-of-lrrk2","CACHE1: Predict Hits for The WDR Domain of LRRK2","Finding ligands targeting the central cavity of the WDR domain of LRRK2","The first CACHE Challenge target is LRRK2, the most commonly mutated gene in familial Parkinson's Disease. Participants are asked to find hits for the WD40 repeat (WDR) domain of LRRK2. Read more under Details below.","","https://cache-challenge.org/challenges/predict-hits-for-the-wdr-domain-of-lrrk2","completed","intermediate","16","","2021-12-01","2022-01-31","2023-09-27 19:01:55","2023-11-14 19:39:53" -"261","finding-ligands-targeting-the-conserved-rna-binding-site-of-sars-cov-2-nsp13","CACHE2: Finding Ligands Targeting The Conserved RNA Binding Site of SARS-CoV-2 NSP13","Target the NSP13 helicase of SARS-CoV-2","Predicted compounds will be procured and tested at CACHE using both enzymatic and binding assays","","https://cache-challenge.org/challenges/finding-ligands-targeting-the-conserved-rna-binding-site-of-sars-cov-2-nsp13","completed","intermediate","16","","2022-06-22","2022-09-04","2023-09-27 19:02:43","2023-11-14 19:41:01" -"262","finding-ligands-targeting-the-macrodomain-of-sars-cov-2-nsp3","CACHE3: Finding ligands targeting the macrodomain of SARS-CoV-2 Nsp3","Study the macrodomain of SARS-CoV-2 Nsp3 for potential therapeutic applications","To predict ligands that bind to the ADPr site of SARS-CoV-2 Nsp3 macrodomain (Mac1).","","https://cache-challenge.org/challenges/finding-ligands-targeting-the-macrodomain-of-sars-cov-2-nsp3","completed","intermediate","16","","2022-11-02","2023-01-01","2023-09-27 19:03:13","2023-10-16 19:01:19" -"263","finding-ligands-targeting-the-tkb-domain-of-cblb","CACHE4: Finding ligands targeting the TKB domain of CBLB","Investigate the TKB domain of CBLB to discover novel compounds for treatment","Predict compounds that bind to the closed conformation of the CBLB TKB domain with novel chemical templates and KD below 30 micromolar.","","https://cache-challenge.org/challenges/finding-ligands-targeting-the-tkb-domain-of-cblb","completed","intermediate","16","","2023-03-09","2023-05-09","2023-09-27 19:03:14","2023-10-16 19:01:22" -"264","rare-disease-ai-hackathon","Rare Disease AI Hackathon","Advance rare disease diagnosis using artificial intelligence (AI) models","Bring AI and medical experts together to build open source models for rare diseases. Create zero-barrier access to rare disease expertise for patients, researchers and physicians. Use AI to Uncover novel links between rare diseases. Establish validation methods for medical AI models. Jumpstart an open source community for rare disease AI models. Launch models for Beta testing on Hypophosphatasia.ai and EhlersDanlos.ai.","","https://www.rarediseaseaihackathon.org/","active","intermediate","\N","","2023-09-30","2024-01-15","2023-09-27 19:10:40","2023-11-11 07:01:13" -"265","cometh-benchmark","COMETH Benchmark","Quantify tumor heterogeneity","Successful treatment of cancer is still a challenge and this is partly due to a wide heterogeneity of cancer composition across patient population. Unfortunately, accounting for such heterogeneity is very difficult. Clinical evaluation of tumor heterogeneity often requires the expertise of anatomical pathologists and radiologists.This benchmark is dedicated to the quantification of intra-tumor heterogeneity using appropriate statistical methods on cancer omics data.In particular, it focuses on estimating cell types and proportion in biological samples based on methylation and methylome data sets. The goal is to explore various statistical methods for source separation/deconvolution analysis (Non-negative Matrix Factorization, Surrogate Variable Analysis, Principal component Analysis, Latent Factor Models, ...) using both RNA-seq and methylome data.","","https://www.codabench.org/competitions/218/","completed","intermediate","10","","2020-06-14","2020-12-29","2023-09-28 23:25:52","2023-11-14 19:41:05" -"266","the-miccai-2014-machine-learning-challenge","The MICCAI 2014 Machine Learning Challenge","Predict binary and continuous phenotypes from Structural Brain MRI","Machine learning tools are increasingly applied to brain MRI scans for predicting individual-level clinical phenotypes. Despite methodological advancements, benchmark studies with standardized datasets are scarce, hindering tool validation and comparison. The MICCAI 2014 Machine Learning Challenge (MLC) addresses this gap, utilizing four large-scale (N > 70) brain MRI datasets with clinically relevant phenotypes. The aim is to showcase the current state of neuroimage-based prediction, drawing machine-learning practitioners to MICCAI and medical image computing. MICCAI 2014 MLC complements the main conference, the Machine Learning in Medical Imaging Workshop, and the CADDementia challenge focused on Alzheimer's diagnosis from brain MR scans.","","https://competitions.codalab.org/competitions/1471","completed","intermediate","9","","2014-04-16","2014-06-14","2023-09-28 23:36:12","2023-11-14 19:41:17" -"267","cagi6-annotate-all-missense","CAGI6: Annotate All Missense","Predict the functional effect of every coding SNV in the human genome","dbNSFP currently describes 81,782,923 possible protein-altering variants in the human genome. The challenge is to predict the functional effect of every such variant. For the vast majority of these missense and nonsense variants, the functional impact is not currently known, but experimental and clinical evidence is accruing rapidly. Rather than drawing upon a single discrete dataset as typical with CAGI, predictions will be assessed by comparing with experimental or clinical annotations made available after the prediction submission date, on an ongoing basis. If predictors assent, predictions will also be incorporated into dbNSFP.","","https://genomeinterpretation.org/cagi6-annotate-all-missense.html","completed","intermediate","1","","2021-06-01","2021-10-11","2023-06-23 00:00:00","2023-11-15 22:48:16" -"268","cagi6-hmbs","CAGI6: HMBS","Submit the fitness score for each of the variants in the HMBS gene","Hydroxymethylbilane synthase (HMBS), also known as porphobilinogen deaminase (PBGD) or uroporphyrinogen I synthase, is an enzyme involved in heme production. In humans, variants that affect HMBS function result in acute intermittent porphyria (AIP), an autosomal dominant genetic disorder caused by a build-up of porphobilinogen in the cytoplasm. A large library of HMBS missense variants was assessed with respect to their effects on protein function using a high-throughput yeast complementation assay. The challenge is to predict the functional effects of these variants.","","https://genomeinterpretation.org/cagi6-hmbs.html","completed","intermediate","1","","2021-06-08","2021-10-11","2023-06-23 00:00:00","2023-11-15 22:48:31" -"269","cagi6-id-panel","CAGI6: Intellectual Disability Panel","Analyze data of Intellectual Disability Panel to identify causative variants","The objective in this challenge is to predict a patient's clinical phenotype and the causal variant(s) based on their gene panel sequences. Sequence data for 74 genes from a cohort of 500 patients with a range of neurodevelopmental presentations (intellectual disability, autistic spectrum disorder, epilepsy, microcephaly, macrocephaly, hypotonia, ataxia) has been made available for this challenge. Additional data from 150 patients from the same clinical study is available for training and validation.","","https://genomeinterpretation.org/cagi6-id-panel.html","completed","intermediate","1","","2021-06-08","2021-10-11","2023-06-23 00:00:00","2023-11-14 19:43:25" -"270","cagi6-mapk1","CAGI6: MAPK1","Predict the ΔΔG(H2O) value for the MAPK1","MAPK1 (ERK2) is active as serine/threonine kinase in the Ras-Raf-MEK-ERK signal transduction cascade that regulates cell proliferation, transcription, differentiation, and cell cycle progression. MAPK1 is activated by phosphorylation which occurs with strict specificity by MEK1/2 on Thr185 and Tyr187, and may also act as a transcriptional repressor independent of its kinase activity. A library of eleven missense variants selected from the COSMIC database was assessed by near and far-UV circular dichroism and intrinsic fluorescence spectra to determine thermodynamic stability at different concentrations of denaturant. These data were used to calculate a ΔΔGH20 value; i.e., the difference in unfolding free energy ΔGH20 between each variant and the wildtype protein, both in phosphorylated and unphosphorylated forms. The challenge is to predict these two ΔΔGH20 values and the catalytic efficiency (kcat/km)mut/(kcat/km)wt, as determined by a fluorescence assay, of the phosphorylated fo...","","https://genomeinterpretation.org/cagi6-mapk1.html","completed","intermediate","1","","2021-07-08","2021-10-11","2023-06-23 00:00:00","2023-11-15 22:48:43" -"271","cagi6-mapk3","CAGI6: MAPK3","Predict the ΔΔG(H2O) value for the MAPK3","MAPK3 (ERK1) is active as serine/threonine kinase in the Ras-Raf-MEK-ERK signal transduction cascade that regulates cell proliferation, transcription, differentiation, and cell cycle progression. MAPK3 is activated by phosphorylation which occurs with strict specificity by MEK1/2 on Thr202 and Tyr204, and may also act as a transcriptional repressor independent of its kinase activity. A library of twelve missense variants selected from the COSMIC database was assessed by near and far-UV circular dichroism and intrinsic fluorescence spectra to determine thermodynamic stability at different concentrations of denaturant. These data were used to calculate a ΔΔGH20 value; i.e., the difference in unfolding free energy ΔGH20 between each variant and the wildtype protein, both in phosphorylated and unphosphorylated forms. The challenge is to predict these two ΔΔGH20 values and the catalytic efficiency (kcat/km)mut/(kcat/km)wt, as determined by a fluorescence assay, of the phosphorylated fo...","","https://genomeinterpretation.org/cagi6-mapk3.html","completed","intermediate","1","","2021-08-04","2021-10-11","2023-06-23 00:00:00","2023-11-15 22:48:47" -"272","cagi6-mthfr","CAGI6: MTHFR","Submit predictions for each missense variant in the MTHFR","Methylenetetrahydrofolate reductase (MTHFR) catalyzes the production of 5-methyltetrahydrofolate, which is needed for conversion of homocysteine to methionine. Humans with variants affecting MTHFR function present with a wide range of phenotypes, including homocystinuria, homocysteinemia, developmental delay, severe mental retardation, psychiatric disturbances, and late-onset neurodegenerative disorders. A further complication to interpretation of variants in this gene is a common variant, Ala222Val, carried by a large fraction of the human population. A large library of MTHFR missense variants was assessed with respect to their effects on protein function using a high-throughput yeast complementation assay. The challenge is to predict the functional effects of these variants in two different settings- for the wildtype protein, and for the protein with the common Ala222Val variant.","","https://genomeinterpretation.org/cagi6-mthfr.html","completed","intermediate","1","","2021-05-03","2021-06-30","2023-06-23 00:00:00","2023-11-15 22:48:59" -"273","cagi6-prs","CAGI6: Polygenic Risk Scores","Estimate polygenic risk scores (PRS) for complex diseases","Polygenic risk scores (PRS) have potential clinical utility for risk surveillance, prevention and personalized medicine. Participants will be provided with datasets of four real phenotypes (Type 2 Diabetes, Breast Cancer, Inflammatory Bowel Disease and Coronary Artery Disease) and of thirty simulated phenotypes representing a range of genetic architectures of common polygenic diseases. The challenge is to predict the disease outcomes of individuals in held-out validation cohorts.","","https://genomeinterpretation.org/cagi6-prs.html","completed","intermediate","1","","2021-06-08","2021-10-11","2023-06-23 00:00:00","2023-11-14 19:42:40" -"274","cagi6-rgp","CAGI6: Rare Genomes Project","Identify causative variants in rare disease genomes for diagnosis","The Rare Genomes Project (RGP) is a direct-to-participant research study on the utility of genome sequencing for rare disease diagnosis and gene discovery. The study is led by genomics experts and clinicians at the Broad Institute of MIT and Harvard. Research subjects are consented for genomic sequencing and the sharing of their sequence and phenotype information with researchers working to understand the molecular causes of rare disease. When a candidate disease variant believed to be related to the phenotype is identified, the variant is confirmed with Sanger sequencing in a clinical setting and returned to the participant via his or her local physician. In this challenge, whole genome sequence data and phenotype data from a subset of the solved and unsolved RGP families will be provided. Participants in the challenge will try to identify the causative variant(s) in each case. For the unsolved cases, prioritized variants from the participating teams will be examined to see if ad...","","https://genomeinterpretation.org/cagi6-rgp.html","completed","intermediate","1","","2021-06-08","2021-10-11","2023-06-23 00:00:00","2023-10-12 18:12:27" -"275","cagi6-invitae","CAGI6: Sherloc clinical classification","122,000 coding variants predicted for ClinVar","Invitae is a genetic testing company that publishes their variant interpretations to ClinVar. In this challenge, over 122,000 previously uncharacterized variants are provided, spanning the range of effects seen in the clinic. Following the close of this challenge, Invitae will submit their interpretations for these variants to ClinVar. Predictors are asked to interpret the pathogenicity of these variants, and the clinical utility of predictions will be assessed across multiple categories by Invitae.","","https://genomeinterpretation.org/cagi6-invitae.html","completed","intermediate","1","","2021-07-08","2021-12-01","2023-06-23 00:00:00","2023-11-16 17:44:21" -"276","cagi6-splicing-vus","CAGI6: Splicing VUS","Predict whether vus disrupt splicing and contribute to genetic disorders","Variants causing aberrant splicing have been implicated in a range of common and rare disorders, including retinitis pigmentosa, autism spectrum disorder, amyotrophic lateral sclerosis, and a variety of cancers. However, such variants are frequently overlooked by diagnostic sequencing pipelines, leading to missed diagnoses for patients. Clinically ascertained variants of unknown significance underwent whole-blood based RT-PCR to test for impact on splicing. The challenge is to predict which of the tested variants disrupt splicing.","","https://genomeinterpretation.org/cagi6-splicing-vus.html","completed","intermediate","1","","2021-06-08","2021-10-11","2023-06-23 00:00:00","2023-11-14 19:44:47" -"277","cagi6-stk11","CAGI6: STK11","Impact of variants in STK11 gene for Peutz-Jeghers syndrome","Serine/Threonine Kinase 11 (STK11) is considered a master kinase that functions as a tumor suppressor and nutrient sensor within a heterotrimeric complex with pseudo-kinase STRAD-alpha and structural protein MO25. Germline variants resulting in loss of STK11 define Peutz-Jaghers Syndrome, an autosomal dominant cancer predisposition syndrome marked by gastrointestinal hamartomas and freckling of the oral mucosa. Somatic loss of function variants, both nonsense and missense, occur in 15-30% of non-small cell lung adenocarcinomas, where they correlate clinically with insensitivity to anti-PD1 monoclonal antibody therapy. The challenge is to predict the impact on STK11 function for each missense variant in relation to wildtype STK11.","","https://genomeinterpretation.org/cagi6-stk11.html","completed","intermediate","1","","2021-06-08","2021-09-01","2023-06-23 00:00:00","2023-11-16 17:44:00" -"278","qbi-hackathon","QBI hackathon","The QBI hackathon","The QBI hackathon is a 48-hour event connecting the vibrant Bay Area developer community with the scientists from UCSF, UCB and UCSC, during which we work together on the cutting edge biomedical problems. Advances in computer vision, AI, and machine learning have enabled computers to pick out cat videos, recognize people’s faces from photos, play video games and drive cars. More recently, application of deep neural nets to protein structure prediction completely revolutionized the field. We look forward to seeing how far we can push science ahead when we apply these latest algorithms to biomedically relevant light microscopy, electron microscopy, and proteomics data. If you love FFTs, transformers, language models, topological data processing, or simply writing code, this is your chance to apply your skills to make an impact on global healthcare. Beyond the actual event, we hope to establish a better connection between talented developers and scientists in the Bay Area, so that we...","","https://www.eventbrite.com/e/qbi-hackathon-2023-tickets-633794304827?aff=oddtdtcreator","completed","intermediate","\N","","2023-11-04","2023-11-05","2023-10-06 21:22:51","2023-11-15 22:49:20" -"279","niddk-central-repository-data-centric-challenge","NIDDK Central Repository Data-Centric Challenge","Enhance NIDDK datasets for future Artificial Intelligence (AI) applications","The National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Central Repository (https://repository.niddk.nih.gov/home/) is conducting a Data Centric Challenge aimed at augmenting existing Repository data for future secondary research including data-driven discovery by artificial intelligence (AI) researchers. The NIDDK Central Repository (NIDDK-CR) program strives to increase the utilization and impact of the resources under its guardianship. However, lack of standardization and consistent metadata within and across studies limit the ability of secondary researchers to easily combine datasets from related studies to generate new insights using data science methods. In the fall of 2021, the NIDDK-CR began implementing approaches to augment data quality to improve AI-readiness by making research data FAIR (findable, accessible, interoperable, and reusable) via a small pilot project utilizing Natural Language Processing (NLP) to tag study variables. In 2022, the NIDD...","","https://www.challenge.gov/?challenge=niddk-central-repository-data-centric-challenge","completed","intermediate","\N","","2023-09-20","2023-11-03","2023-10-18 16:58:17","2023-11-15 22:49:26" -"280","stanford-ribonanza-rna-folding","Stanford Ribonanza RNA Folding","A path to programmable medicine and scientific breakthroughs","Ribonucleic acid (RNA) is essential for most biological functions. A better understanding of how to manipulate RNA could help usher in an age of programmable medicine, including first cures for pancreatic cancer and Alzheimer’s disease as well as much-needed antibiotics and new biotechnology approaches for climate change. But first, researchers must better understand each RNA molecule's structure, an ideal problem for data science.","","https://www.kaggle.com/competitions/stanford-ribonanza-rna-folding","completed","intermediate","8","","2023-08-23","2023-11-24","2023-10-23 20:58:06","2023-11-15 22:49:31" -"281","uls23","Universal Lesion Segmentation Challenge '23","Advancements, challenges, and a universal solution emerges","Significant advancements have been made in AI-based automatic segmentation models for tumours. Medical challenges focusing on e.g. Liver, kidney, or lung tumours have resulted in large performance improvements for segmenting these types of lesions. However, in clinical practice there is a need for versatile and robust models capable of quickly segmenting the many possible lesions types in the thorax-abdomen area. Developing a universal lesion segmentation (uls) model that can handle this diversity of lesions types requires a well-curated and varied dataset. Whilst there has been previous work on uls [6-8], most research in this field has made extensive use of a single partially annotated dataset [9], containing only the long- and short-axis diameters on a single axial slice. Furthermore, a test set containing 3d segmentation masks used during evaluation on this dataset by previous publications is not publicly available.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/747/ULS23_logo_aoB8tlx.png","https://uls23.grand-challenge.org/","active","intermediate","5","","2023-10-29","2024-03-17","2023-11-02 15:35:22","2023-11-17 21:29:35" -"282","vessel12","VESSEL12","Assess methods for blood vessels in lung CT images","The VESSEL12 challenge compares methods for automatic (and semi-automatic) segmentation of blood vessels in the lungs from CT images.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/1/logo.png","https://vessel12.grand-challenge.org/","completed","intermediate","5","https://doi.org/10.1016/j.media.2014.07.003","2011-11-25","2012-04-01","2023-11-08 00:42:00","2023-11-17 21:30:05" -"283","crass","CRASS","Invites participants to submit clavicle segmentation results","Crass stands for chest radiograph anatomical structure segmentation. The challenge currently invites participants to send in results for clavicle segmentation algorithms.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/5/logo.png","https://crass.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:09:56" -"284","anode09","ANODE09","Automatic pulmonary nodule detection systems in chest CT scans","ANODE09 is an initiative to compare systems that perform automatic detection of pulmonary nodules in chest CT scans on a single common database, with a single evaluation protocol.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/7/logo.png","https://anode09.grand-challenge.org/","completed","intermediate","5","https://doi.org/10.1016/j.media.2010.05.005","\N","\N","2023-11-08 00:42:00","2023-11-17 23:17:55" -"285","cause07","CAUSE07","Compares algorithms for caudate nucleus segmentation in brain MRI scans","The goal of CAUSE07 is to compare different algorithms to segment the caudate nucleaus from brain MRI scans.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/8/logo.png","https://cause07.grand-challenge.org/","completed","intermediate","5","","2007-10-26","\N","2023-11-08 00:42:00","2023-11-17 21:34:10" -"286","subsolidnodules","Subsolid Nodules","We present results of our segmentation method for subsolid lung nodules","We are presenting results of our segmentation method for subsolid lung nodules.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/10/logo.png","https://subsolidnodules.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-08 21:24:01" -"287","caddementia","CADDementia","Classification in AD, MCI, and healthy controls using MRI data","We seek algorithms that perform multi-class classification of patients with Alzheimer's disease (AD), patients with mild cognitive impairment (MCI) and healthy controls (CN) using multi-center structural MRI data.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/17/logo3_100.png","https://caddementia.grand-challenge.org/","completed","intermediate","5","https://doi.org/10.1016/j.neuroimage.2015.01.048","\N","\N","2023-11-08 00:42:00","2023-11-17 23:18:33" -"288","mitos-atypia-14","MITOS-ATYPIA-14","Mitosis detection and nuclear atypia on breast cancer H&E stained images","MITOS & ATYPIA 14 contest, hosted by conference ICPR 2014 - detection of mitosis and evaluation of nuclear atypia on breast cancer H&E stained images","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/20/logo_mitos_atypia.png","https://mitos-atypia-14.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:19:06" -"289","lola11","LOLA11","Segmentation of lungs and lobes in chest CT scans","The goal of LOLA11 (LObe and Lung Analysis 2011) is to compare methods for (semi-)automatic segmentation of the lungs and lobes from chest computed tomography scans. Any team, whether from academia or industry, can join.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/39/lola11_web_GVIrfhf.png","https://lola11.grand-challenge.org/","active","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:19:28" -"290","promise12","PROMISE12","Segmentation algorithms for MRI of the prostate","The goal of this challenge is to compare interactive and (semi)-automatic segmentation algorithms for MRI of the prostate.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/40/promise12.png","https://promise12.grand-challenge.org/","completed","intermediate","5","https://doi.org/10.1016/j.media.2013.12.002","\N","\N","2023-11-08 00:42:00","2023-11-14 19:48:34" -"291","camelyon16","CAMELYON16","Evaluating algorithms for automated cancer metastasis detection","The goal of this challenge is to evaluate new and existing algorithms for automated detection of cancer metastasis in digitized lymph node tissue sections. Two large datasets from both the radboud university medical center and the university medical center utrecht are provided.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/65/logo.png","https://camelyon16.grand-challenge.org/","completed","intermediate","5","https://doi.org/10.1001/jama.2017.14585","2015-11-25","2016-04-01","2023-11-08 00:42:00","2023-11-11 01:44:54" -"292","isbi-aida","ISBI-AIDA","The isbi challenge focuses on evaluating endoscopic image analysis methods","The aim of this challenge is to bring together the community of researchers working on the various types of optical endoscopy at its multiple scales and different needs, to provide reference databases and reference results both for the imaging community and those interested in the translation to the clinical practice.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/67/logo.png","https://isbi-aida.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:50:12" -"293","luna16","LUNA16","Nodule detection algorithms for chest CT in a large-scale setting","The LUNA16 challenge will focus on a large-scale evaluation of automatic nodule detection algorithms for chest CT.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/71/luna16_logo.png","https://luna16.grand-challenge.org/","completed","intermediate","5","https://doi.org/10.1016/j.media.2017.06.015","\N","\N","2023-11-08 00:42:00","2023-11-17 23:19:48" -"294","camelyon17","CAMELYON17","Automated detection and classification of breast cancer metastases","Automated detection and classification of breast cancer metastases in whole-slide images of histological lymph node sections. This task has high clinical relevance and would normally require extensive microscopic assessment by pathologists.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/80/camelyon17_logo.png","https://camelyon17.grand-challenge.org/","active","intermediate","5","https://doi.org/10.1109/tmi.2018.2867350","2016-11-16","\N","2023-11-08 00:42:00","2023-11-11 01:45:01" -"295","retouch","RETOUCH","Detecting retinal fluid in optical coherence tomography images","Retinal OCT fluid challenge (RETOUCH) compares automated algorithms that are able to detect and segment different types of retinal fluid in optical coherence tomography (OCT).","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/111/retouch-logo.png","https://retouch.grand-challenge.org/","completed","intermediate","5","https://doi.org/10.1109/tmi.2019.2901398","2017-04-03","\N","2023-11-08 00:42:00","2023-11-17 23:20:14" -"296","cataracts","CATARACTS","Image-based tool detection algorithms for cataract surgery","The challenge on automatic tool annotation for cataract surgery aims at evaluating image-based tool detection algorithms in the context of the most common surgical procedure in the world.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/130/logo.png","https://cataracts.grand-challenge.org/","completed","intermediate","5","https://doi.org/10.1016/j.media.2018.11.008","\N","\N","2023-11-08 00:42:00","2023-11-14 19:48:56" -"297","tadpole","TADPOLE","Assesses Alzheimer's disease prediction of longitudinal evolution","The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) challenge is brought to you by the europond consortium in collaboration with the Alzheimer's Disease Neuroimaging Initiative (ADNI).","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/141/logo_gC1i5c5.png","https://tadpole.grand-challenge.org/","completed","intermediate","5","https://arxiv.org/abs/2002.03419","\N","\N","2023-11-08 00:42:00","2023-11-17 23:21:11" -"298","coronare","CoronARe","Methods in coronary artery reconstruction using C-arm angiography","Coronare ranks state-of-the-art methods in symbolic and tomographic coronary artery reconstruction from interventional c-arm rotational angiography. Specifically, we will benchmark the performance of the methods using accurately pre-processed data, and study the effects of imperfect pre-processing conditions (segmentation and background subtraction errors). The evaluation will be performed in a controlled environment using digital phantom images.","","https://coronare.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-14 19:49:15" -"299","iciar2018-challenge","ICIAR 2018","Automatic detection of cancerous regions in breast cancer histology images","Can you develop a method for automatic detection of cancerous regions in breast cancer histology images?","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/176/logo_small.png","https://iciar2018-challenge.grand-challenge.org/","active","intermediate","5","https://doi.org/10.1016/j.media.2019.05.010","2023-01-09","\N","2023-11-08 00:42:00","2023-11-14 19:49:22" -"300","sliver07","SLIVER07","Liver segmentation in clinical 3D CT scans in this competition","The goal of this competition is to compare different algorithms to segment the liver from clinical 3d computed tomography (CT) scans.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/178/splash2.jpg","https://sliver07.grand-challenge.org/","completed","intermediate","5","https://doi.org/10.1109/tmi.2009.2013851","\N","\N","2023-11-08 00:42:00","2023-11-17 23:21:37" -"301","rocc","ROCC","DR disease in retina OCT volumes","Retinal OCT Classification Challenge (ROCC) is organized as a one day challenge in conjunction with MVIP2017. The goal of this challenge is to call different automated algorithms that are able to detect DR disease from normal retina on a common dataset of OCT volumes, acquired with topcon SD-OCT devices.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/180/logo.jpg","https://rocc.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:22:17" -"302","idrid","IDRiD","Retinal lesion segmentation, optic disc/fovea detection, and DR grading","This challenge evaluates automated techniques for analysis of fundus photographs. We target segmentation of retinal lesions like exudates, microaneurysms, and hemorrhages and detection of the optic disc and fovea. Also, we seek grading of fundus images according to the severity level of DR and DME.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/183/g2385.png","https://idrid.grand-challenge.org/","completed","intermediate","5","https://doi.org/10.1016/j.media.2019.101561","\N","\N","2023-11-08 00:42:00","2023-11-17 23:22:36" -"303","empire10","EMPIRE10","Chest CT images; assess the accuracy of algorithms","The EMPIRE10 challenge was launched in early 2010 with an initial set of 20 scan pairs to be registered by participants in their own facility. This was followed in September by a workshop at the MICCAI 2010 conference where participants registered a further 10 scan pairs live within a 3 hour timeframe. This process and the results obtained are described in detail in Murphy et al., ""Evaluation of registration methods on thoracic CT: the EMPIRE10 challenge."", IEEE Trans Med Imaging. 2011 Nov;30(11):1901-20. Please cite this publication if you wish to reference the EMPIRE10 challenge. From this point forward all participants will be judged based on the full set of 30 scan pairs. New participants and new submissions are always welcome - in this way we hope that the EMPIRE10 website will continue to reflect the state of the art in registration of pulmonary CT images.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/186/logo.png","https://empire10.grand-challenge.org/","completed","intermediate","5","https://doi.org/10.1109/tmi.2011.2158349","\N","\N","2023-11-08 00:42:00","2023-11-15 22:51:00" -"304","lumic","LUMIC","CT chest images using an anthropomorphic digital phantom","The LUMIC challenge tests the accuracy in registration between pre- and post-contrast CT chest images for algorithms, using an anthropomophic digital phantom.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/203/lumiclogo.png","https://lumic.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:22:52" -"305","continuousregistration","Continuous Registration","Submit your lung and brain registration method","Submit your method for lung and brain registration on https://github.com/superelastix/superelastix! Your method is easily accessible to end-users and automatically compiled, tested, and benchmarked weekly on several different data sets.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/207/logo.png","https://continuousregistration.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-14 19:50:44" -"306","drive","DRIVE","Develop a system to automatically segment vessels in human retina fundus images","The DRIVE database has been established to enable comparative studies on segmentation of blood vessels in retinal images. Retinal vessel segmentation and delineation of morphological attributes of retinal blood vessels, such as length, width, tortuosity, branching patterns and angles are utilized for the diagnosis, screening, treatment, and evaluation of various cardiovascular and ophthalmologic diseases such as diabetes, hypertension, arteriosclerosis and chorodial neovascularization. Automatic detection and analysis of the vasculature can assist in the implementation of screening programs for diabetic retinopathy, can aid research on the relationship between vessel tortuosity and hypertensive retinopathy, vessel diameter measurement in relation with diagnosis of hypertension, and computer-assisted laser surgery. Automatic generation of retinal maps and extraction of branch points have been used for temporal or multimodal image registration and retinal image mosaic synthesis. Mor...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/210/logo_drive.PNG","https://drive.grand-challenge.org/","active","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:51:30" -"307","curious2018","CuRIOUS 2018","MICCAI Challenge 2018 for brainshift correction with intra-operative ultrasound","Early brain tumor resection can effectively improve the patient’s survival rate. However, resection quality and safety can often be heavily affected by intra-operative brain tissue shift due to factors, such as gravity, drug administration, intracranial pressure change, and tissue removal. Such tissue shift can displace the surgical target and vital structures (e.g., blood vessels) shown in pre-operative images while these displacements may not be directly visible in the surgeon’s field of view. Intra-operative ultrasound (iUS) is a robust and relatively inexpensive technique to track intra-operative tissue shift and surgical tools, but to help update pre-surgical plans with this information, accurate and robust image registration algorithms are needed to relate pre-surgical MRI to iUS images. Despite the great progress so far, medical image registration techniques still have not made into the surgical room to directly benefit the patients with brain tumors. This challege/worksh...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/221/curious2018_logo.png","https://curious2018.grand-challenge.org/","completed","intermediate","5","https://doi.org/10.1109/tmi.2019.2935060","\N","\N","2023-11-08 00:42:00","2023-11-15 22:51:50" -"308","refuge","REFUGE","Algorithms for glaucoma detection and optic disc/cup segmentation","The goal of the REtinal FUndus Glaucoma Challenge (REFUGE) is to evaluate and compare automated algorithms for glaucoma detection and optic disc/cup segmentation on a common dataset of retinal fundus images.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/229/logo_refuge_200x200.png","https://refuge.grand-challenge.org/","active","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:23:34" -"309","monuseg","MoNuSeg","Segmenting nuclei from H&E stained histopathological images","This challenge will showcase the best nuclei segmentation techniques that will work on a diverse set of H&E stained histology images obtained from different hospitals spanning multiple patients and organs. This will enable the training and testing of readily usable (or generalized) nuclear segmentation softwares.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/238/monuseg_logo.png","https://monuseg.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:52:09" -"310","paves","PAVES","Mra images for lower limb arterial occlusive disease planning","Peripheral artery:vein enhanced segmentation (PAVES) is the challenge focussed on providing easily interpretable and relevant images that can be readily understood by clinicians (vascular interventional radiologists & vascular surgeons) from mra datasets where the venous and arterial vasculature may be equally enhanced. The setting is lower limb arterial occlusive disease where imaging of the below knee arterial vasculature is critical in planning limb salvage interventions. However, the competing demands of the high spatial resolution needed to image small vessels versus imaging time constraints where there is often a very short arteriovenous transit time for contrast passage form arterial to venous compartments makes imaging challenging. While dynamic mra techniques can usually allow arterial imaging without venous ‚äòcontamination‚äô these necessarily sacrifice spatial resolution.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/243/paveslogo.png","https://paves.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:23:47" -"311","prostatex","PROSTATEx","Clinical significance of prostate lesions using MRI data","This challenge is the live continuation of the offline PROSTATEx Challenge (""SPIE-AAPM-NCI Prostate MR Classification Challenge”) that was held in conjunction with the 2017 SPIE Medical Imaging Symposium. In this challenge, the task is to predict the clinical significance of prostate lesions found in MRI data.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/258/prostatex-logo.jpg","https://prostatex.grand-challenge.org/","completed","intermediate","5","","\N","2022-04-30","2023-11-08 00:42:00","2023-11-15 22:52:25" -"312","hc18","HC18","Measuring fetal head circumference using 2D ultrasound images","Automated measurement of fetal head circumference using 2D ultrasound images","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/265/HC18_LogoV1.png","https://hc18.grand-challenge.org/","active","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:23:58" -"313","anhir","ANHIR","Aligning multi-stained histology tissue samples","The challenge focuses on comparing the accuracy (using manually annotated landmarks) and the approximate speed of automatic non-linear registration methods for aligning microscopy images of multi-stained histology tissue samples.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/285/logo_sq_OdYGo3e.png","https://anhir.grand-challenge.org/","active","intermediate","5","https://doi.org/10.1109/tmi.2020.2986331","\N","\N","2023-11-08 00:42:00","2023-11-14 19:51:43" -"314","breastpathq","BreastPathQ: Cancer Cellularity Challenge 2019","Develop a method for analyzing histology patches","SPIE-AAPM-NCI BreastPathQ:Cancer Circularity Challenge 2019: Participants will be tasked to develop an automated method for analyzing histology patches extracted from whole slide images and assign a score reflecting cancer cellularity for tumor burden assessment in each.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/296/spie_with_overlays.png","https://breastpathq.grand-challenge.org/","active","intermediate","5","https://doi.org/10.1117/1.jmi.8.3.034501","\N","\N","2023-11-08 00:42:00","2023-11-17 23:27:13" -"315","chaos","CHAOS","Segment liver in CT data and liver, spleen, and kidneys in MRI data","In this challenge, you segment the liver in CT data, and segment liver, spleen, and kidneys in MRI data.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/298/logo_8sv4fA4_SWcTFEs.png","https://chaos.grand-challenge.org/","active","intermediate","5","https://doi.org/10.1016/j.media.2020.101950","\N","\N","2023-11-08 00:42:00","2023-11-17 21:31:53" -"316","ead2019","EAD2019","Address multi-class artefact detection, region segmentation, and detection","Endoscopic artefact detection (EAD) is a core problem and needed for realising robust computer-assisted tools. The EAD challenge has 3 tasks: 1) multi-class artefact detection, 2) region segmentation, 3) detection generalisation.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/302/1772_A_M62_00022_1.jpg","https://ead2019.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:25:06" -"317","acdc-lunghp","ACDC-LungHP","Methods for whole-slide lung histopathology images","Automatic cancer detection and classification in whole-slide lung histopathology","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/305/logo.png","https://acdc-lunghp.grand-challenge.org/","active","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-14 19:52:50" -"318","palm","PALM","Pathological Myopia diagnosis and fundus lesion segmentation in patients","The pathologic myopia challenge (PALM) focuses on the investigation and development of algorithms associated with the diagnosis of pathological myopia (PM) and segmentation of lesions in fundus photos from PM patients.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/307/palm-logo.jpg","https://palm.grand-challenge.org/","active","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:25:23" -"319","ichallenges","iChallenges","Eye image modalities, including REFUGE, PALM, RETOUCH, among others","We organized a serial of challenges on different eye image modalities, such as REFUGE, PALM, RETOUCH, etc.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/345/ichallenge.png","https://ichallenges.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:25:37" -"320","decathlon-10","Decathlon","Test machine learning algorithm generalizability across 10 different tasks","The medical segmentation decathlon challenge tests the generalisability of machine learning algorithms when applied to 10 different semantic segmentation task.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/350/background_dark_logo.png","https://decathlon-10.grand-challenge.org/","completed","intermediate","5","https://doi.org/10.1038/s41467-022-30695-9","2022-07-21","2023-08-20","2023-11-08 00:42:00","2023-11-14 19:53:19" -"321","lyon19","LYON19","Develop methods for automatic lymphocyte detection in IHC stained specimens","Automatic Lymphocyte detection in IHC stained specimens.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/355/ban2_kpuoTJg.png","https://lyon19.grand-challenge.org/","active","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:27:28" -"322","kits19","KiTS19","Participate in the segmentation challenge for kidneys and kidney tumors in 2019","2019 Kidney and Kidney Tumor Segmentation Challenge","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/360/Screenshot_from_2019-01-02_17-23-36.png","https://kits19.grand-challenge.org/","active","intermediate","5","https://arxiv.org/abs/1912.01054","\N","\N","2023-11-08 00:42:00","2023-11-17 23:27:36" -"323","paip2019","PAIP 2019","Address liver cancer segmentation and viable tumor burden estimation","PAIP2019: Liver Cancer Segmentation Task 1: Liver Cancer Segmentation Task 2: Viable Tumor Burden Estimation","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/370/Untitled_design.png","https://paip2019.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:27:53" -"324","orcascore","orCaScore","Coronary artery calcium scoring in cardiac CT scans","The purpose of the orCaScore challenge is to compare methods for automatic and semi-automatic coronary artery calcium scoring in cardiac CT scans. This evaluation framework was launched at the MICCAI 2014 workshops in Boston, USA, where we organized the Challenge on Automatic Coronary Calcium Scoring.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/378/00b670348bfdf4464e00c44310ec259f.jpg","https://orcascore.grand-challenge.org/","active","intermediate","5","https://doi.org/10.1118/1.4945696","\N","\N","2023-11-08 00:42:00","2023-11-17 23:28:02" -"325","curious2019","curious2019","MRI to intra-operative ultrasound (iUS) before and after tumor resection","MICCAI Challenge 2019 for Correction of Brainshift with Intra-Operative Ultrasound. Taks 1: Register pre-operative MRI to iUS before tumor resection;Taks 2: Register iUS after tumor resection to iUS before tumor resection","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/380/CuRIOUS.png","https://curious2019.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:28:13" -"326","patchcamelyon","PatchCamelyon","Detect breast cancer metastasis in lymph nodes","PatchCamelyon is a new and challenging image classification dataset of 327.680 color images (96 x 96px) extracted from histopathology images of the CAMELYON16 challenge. The goal is to detect breast cancer metastasis in lymph nodes.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/381/Screen_Shot_2019-05-05_at_21.43.25.png","https://patchcamelyon.grand-challenge.org/","active","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:28:22" -"327","endovissub2019-scared","Stereo Correspondence and Reconstruction of Endoscopic Data","Address stereo correspondence and reconstruction challenges in endoscopic data","Stereo correspondence and reconstruction of endoscopic data","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/385/c7714704.jpg","https://endovissub2019-scared.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-08 00:58:30" -"328","verse2019","VerSe`19","Vertebrae labelling and segmentation on 150 CT scans","Vertebrae labelling and segmentation on a spine dataset on an unprecedented 150 CT scans with voxel-level vertebral annotations.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/388/logo_border.png","https://verse2019.grand-challenge.org/","active","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 21:30:59" -"329","gleason2019","Gleason2019","Methods for prostate cancer from H&E-stained histopathology images","MICCAI 2019 automatic prostate gleason grading challenge: this challenge aims at the automatic gleason grading of prostate cancer from h&e-stained histopathology images. This task is of critical importance because gleason score is a strong prognostic predictor. On the other hand, it is very challenging because of the large degree of heterogeneity in the cellular and glandular patterns associated with each gleason grade, leading to significant inter-observer variability, even among expert pathologists.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/391/GLEASON2019.png","https://gleason2019.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-14 20:00:08" -"330","age","AGE","Assess automatic methods for angle closure glaucoma evaluation","Angle closure glaucoma evaluation challenge","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/394/icon.png","https://age.grand-challenge.org/","active","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-11 01:48:53" -"331","amd","iChallenge-AMD","Tackle challenges in age-related macular degeneration diagnosis and analysis","Age-related macular degeneration challenge","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/395/%E6%BC%94%E7%A4%BA%E6%96%87%E7%A8%BF1-2.png","https://amd.grand-challenge.org/","active","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-08 00:58:34" -"332","structseg2019","StructSeg2019","Automated structure segmentation for radiotherapy planning","Welcome to automatic structure segmentation for radiotherapy planning challenge 2019. This competition is part of the MICCAI 2019 challenge.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/398/logo_aAzg3xS.jpg","https://structseg2019.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-14 19:54:50" -"333","digestpath2019","DigestPath2019","Algorithms for signet ring cell detection and colonoscopy tissue screening","The challenge aims to evaluate algorithms for signet ring cell detection and colonoscopy tissue screening in digestive system pathological images. It introduces the first public dataset for these tasks, providing expert-level annotations to advance research on automatic pathological object detection and lesion segmentation.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/399/digestpath-logo2.png","https://digestpath2019.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 18:40:29" -"334","odir2019","ODIR-2019","Compete in recognizing ocular diseases using morphological features","Peking university international competition on ocular disease intelligent recognition","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/402/logo.jpg","https://odir2019.grand-challenge.org/","active","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-14 20:27:41" -"335","lysto","Lymphocyte Assessment Hackathon","Workshop for lymphocyte assessment in computational pathology","Lymphocyte assessment hackathon in conjunction with the MICCAI compay 2019 workshop on computational pathology","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/421/lysto_square.png","https://lysto.grand-challenge.org/","active","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-14 19:55:01" -"336","aasce19","AASCE","Develop accurate automated methods for estimating spinal curvature","Accurate automated spinal curvature estimation","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/424/logo.png","https://aasce19.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-08 00:58:39" -"337","ecdp2020","HEROHE","Identify HER2-positive from HER2-negative breast cancer specimens","Unlike previous challenges, this proposes to find an image analysis algorithm to identify her2-positive from her2-negative breast cancer specimens evaluating only the morphological features present on the he slide, without the staining patterns of ihc.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/433/ECDP2020_square.jpg","https://ecdp2020.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-14 19:55:07" -"338","monusac-2020","MoNuSAC 2020","Address segmentation and classification of nuclei in multi-organ images","Multi-organ nuclei segmentation and classification challenge","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/445/logo.PNG","https://monusac-2020.grand-challenge.org/","completed","intermediate","5","https://doi.org/10.13140/rg.2.2.12290.02244/1","\N","\N","2023-11-08 00:42:00","2023-11-08 00:58:42" -"339","endocv","EndoCV2020","Focus on artefact detection and disease detection in endoscopic images","Endoscopy computer vision challenge (endocv2020) introduces two core sub-themes in endoscopy: 1) artefact detection and segmentation (ead2020) and 2) disease detection and segmentation (edd2020).","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/462/endoLogo.png","https://endocv.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-14 19:55:17" -"340","lndb","LNDb Challenge","Determine nodule detection and characterization for lung cancer screening","Lung cancer screening and fleischner follow-up determination in chest CT through nodule detection, segmentation and characterization","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/470/thumbnail_lndb.png","https://lndb.grand-challenge.org/","active","intermediate","5","https://arxiv.org/abs/1911.08434","\N","\N","2023-11-08 00:42:00","2023-11-17 21:31:00" -"341","verse2020","VerSe'20","Label and segment vertebrae on a diverse CT dataset","Vertebrae labelling and segmentation on a multi-centre, multi-scanner, and anatomically-diverse CT dataset.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/473/logo_border.png","https://verse2020.grand-challenge.org/","active","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 21:31:02" -"342","paip2020","PAIP2020","Classify molecular subtypes in colorectal cancers, predict MSI","Built on the success of its predecessor, paip2020 is the second challenge organized by the pathology AI platform (paip) and the seoul national university hospital (snuh). Paip2020 will proceed to not only detect whole tumor areas in colorectal cancers but also to classify their molecular subtypes, which will lead to characterization of their heterogeneity with respect to prognoses and therapeutic responses. All participants should predict one of the molecular carcinogenesis pathways, i.e., microsatellite instability(msi) in colorectal cancer, by performing digital image analysis without clinical tests. This task has a high clinical relevance as the currently used procedure requires an extensive microscopic assessment by pathologists. Therefore, those automated algorithms would reduce the workload of pathologists as a diagnostic assistance.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/480/paip2020_thumb_640x640.jpg","https://paip2020.grand-challenge.org/","active","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 21:33:31" -"343","ribfrac","RibFrac","Benchmark rib fracture detection and classification on 660 CT scans","Rib fracture detection and classification challenge: a large-scale benchmark of 660 CT scans with ~5,000 rib fractures (around 80gb)","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/482/challenge-logo-white_b8a8xbr.jpg","https://ribfrac.grand-challenge.org/","active","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 21:31:05" -"344","tn-scui2020","Thyroid Nodule Segmentation and Classification","Develop algorithms for thyroid nodules using a diverse ultrasound dataset","The main topic of this tn-scui2020 challenge is finding automatic algorithms to accurately classify the thyroid nodules in ultrasound images. It will provide the biggest public dataset of thyroid nodule with over 4500 patient cases from different ages, genders, and were collected using different ultrasound machines. Each ultrasound image is provided with its ground truth class (benign or maglinant) and a detailed delineation of the nodule. This challenge will provide a unique opportunity for participants from different backgrounds (e.g. academia, industry, and government, etc.) To compare their algorithms in an impartial way.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/484/Capture8888.PNG","https://tn-scui2020.grand-challenge.org/","active","intermediate","5","","2022-01-20","\N","2023-11-08 00:42:00","2023-11-14 19:56:07" -"345","learn2reg","Learn2Reg","Address challenges in learning from small datasets","Challenge on medical image registration addressing: learning from small datasets; estimating large deformations; dealing with multi-modal scans; and learning from noisy annotations","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/486/logo_warped.png","https://learn2reg.grand-challenge.org/","active","intermediate","5","https://doi.org/10.1109/tmi.2022.3213983","\N","\N","2023-11-08 00:42:00","2023-11-14 19:56:18" -"346","asoca","Automated Segmentation Of Coronary Arteries","Develop automated methods for segmentation of coronary arteries","Automated segmentation of coronary arteries","","https://asoca.grand-challenge.org/","active","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-08 17:59:56" -"347","knoap2020","KNOAP2020","Compare methods MRI, X-ray, and clinical risk factors for knee osteoarthritis","Knee osteoarthritis causes a large economic burden on the society and reduces life quality of an individual. Therefore, methods that are able to identify subjects who will develop the disease in the future are important. Usually the methods are optimized for specific datasets and it is unclear how the different methods would perform on previously unseen data. Therefore, we are organizing a challenge to objectively compare methods that use mri, x-ray image data, and clinical risk factors for prediction of incident symptomatic radiographic knee osteoarthritis.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/492/KNOAP_logo_640x640.png","https://knoap2020.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-14 19:58:04" -"348","humanactivitiyclassificationwithradar","Human Activity Classification with Radar","Benchmark classification algorithms on a publicly available radar dataset","The radar challenge is a new event hosted at 2020 iet international radar conference that enables participants to test their classification algorithms on a common, publicly available database of radar data in order to benchmark performances. Dataset download link: http://researchdata.gla.ac.uk/848/","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/493/logo.png","https://humanactivitiyclassificationwithradar.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-11 01:59:47" -"349","saras-esad","SARAS-ESAD","AI-based surgical scene for robotic assistants in minimally invasive surgery","This challenge is part of medical imaging with deep learning conference, 2020. The conference is held between 6 ‚äë 8 july 2020 in montr√©al. The saras (smart autonomous robotic assistant surgeon) eu consortium, www.saras-project.eu, is working towards replacing the assistant surgeon in mis with two assistive robotic arms. To accomplish that, an artificial intelligence based system is required which not only can understand the complete surgical scene but also detect the actions being performed by the main surgeon. This information can later be used infer the response required from the autonomous assistant surgeon.","","https://saras-esad.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-28 00:29:54" -"350","surgvisdom","SurgVisDom","VR simulations to overcome data privacy concerns in context-aware models","Exploring visual domain adaptation using vr simulations to overcome data privacy concerns in context-aware models.","","https://surgvisdom.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-22 19:40:08" -"351","cada","CADA","Cerebral aneurysm image analysis challenge","Cerebral aneurysms are local dilations of arterial blood vessels caused by a weakness of the vessel wall. Subarachnoid hemorrhage (sah) caused by the rupture of a cerebral aneurysm is a life-threatening condition associated with high mortality and morbidity. The mortality rate is above 40%, and even in case of survival cognitive impairment can affect patients for a long time. Major goals in image analysis are the detection and risk assessment of aneurysms. We, therefore, subdivided the challenge into three categories. The first task is finding the aneurysm; the second task is the accurate segmentation to allow for a longitudinal assessment of the development of suspicious aneurysms. The third task is the estimation of the rupture risk of the aneurysm.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/531/data-first-row-2.png","https://cada.grand-challenge.org/","completed","intermediate","5","https://doi.org/10.1007/978-3-030-72862-5","\N","\N","2023-11-08 00:42:00","2023-11-11 01:54:15" -"352","dfu2020","Diabetic Foot Ulcer Challenge 2020","Diabetic foot ulcer challenge 2020","Diabetic foot ulcer challenge 2020","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/532/bb.png","https://dfu2020.grand-challenge.org/","active","intermediate","5","https://doi.org/10.1016/j.compbiomed.2021.104596","\N","\N","2023-11-08 00:42:00","2023-11-08 22:47:03" -"353","covid-ct","CT diagnosis of COVID-19","COVID-19 CT Image Diagnosis Competition","Coronavirus disease 2019 (COVID-19) has infected more than 1.3 million individuals all over the world and caused more than 106,000 deaths. One major hurdle in controlling the spreading of this disease is the inefficiency and shortage of medical tests. To mitigate the inefficiency and shortage of existing tests for COVID-19, we propose this competition to encourage the development of effective deep learning techniques to diagnose COVID-19 based on CT images. The problem we want to solve is to classify each CT image into positive COVID-19 (the image has clinical findings of COVID-19) or negative COVID-19 ( the image does not have clinical findings of COVID-19). It‚äôs a binary classification problem based on CT images.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/537/covid-CT2.png","https://covid-ct.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-14 20:25:11","2023-11-17 21:32:02" -"354","autoimplant","AutoImplant","MICCAI 2020 Cranial Implant Design","The MICCAI 2020 cranial implant design challenge","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/540/logos.PNG","https://autoimplant.grand-challenge.org/","completed","intermediate","5","https://arxiv.org/abs/2006.12449","\N","\N","2023-11-14 20:25:44","2023-11-08 00:59:03" -"355","cada-rre","CADA - Rupture Risk Estimation","Cerebral aneurysm challenge: detect, segment, and assess rupture risk","Cerebral aneurysms are local dilations of arterial blood vessels caused by a weakness of the vessel wall. Subarachnoid hemorrhage (sah) caused by the rupture of a cerebral aneurysm is a life-threatening condition associated with high mortality and morbidity. The mortality rate is above 40%, and even in case of survival cognitive impairment can affect patients for a long time. Major goals in image analysis are the detection and risk assessment of aneurysms. We, therefore, subdivided the challenge into three categories. The first task is finding the aneurysm; the second task is the accurate segmentation to allow for a longitudinal assessment of the development of suspicious aneurysms. The third task is the estimation of the rupture risk of the aneurysm.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/541/data-first-row-2.png","https://cada-rre.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-11 01:59:43" -"356","cada-as","CADA - Aneurysm Segmentation","Cerebral aneurysm image analysis: detect, segment, assess risk","Cerebral aneurysms are local dilations of arterial blood vessels caused by a weakness of the vessel wall. Subarachnoid hemorrhage (sah) caused by the rupture of a cerebral aneurysm is a life-threatening condition associated with high mortality and morbidity. The mortality rate is above 40%, and even in case of survival cognitive impairment can affect patients for a long time. Major goals in image analysis are the detection and risk assessment of aneurysms. We, therefore, subdivided the challenge into three categories. The first task is finding the aneurysm; the second task is the accurate segmentation to allow for a longitudinal assessment of the development of suspicious aneurysms. The third task is the estimation of the rupture risk of the aneurysm.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/543/data-first-row-2.png","https://cada-as.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-08 00:59:10" -"357","panda","The PANDA challenge","PANDA Challenge: prostate cancer grading","The panda challenge: prostate cancer grade assessment using the gleason grading system","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/544/panda_logo_notext.png","https://panda.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-08 00:59:10" -"358","pathvqachallenge","Pathology Visual Question Answering","Pathology visual question answering","Pathology visual question answering","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/548/grand_challenge3.jpg","https://pathvqachallenge.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-11 01:50:06" -"359","qubiq","QUBIQ","Biomedical image segmentation uncertainties","Quantification of uncertainties in biomedical image segmentation challenge","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/552/brain.png","https://qubiq.grand-challenge.org/","active","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-08 00:59:15" -"360","lodopab","LoDoPaB-CT","Low-dose CT reconstruction challenge","Low-dose CT reconstruction in the setting of the lodopab-ct dataset.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/555/logo_white_bg.png","https://lodopab.grand-challenge.org/","active","intermediate","5","https://doi.org/10.1038/s41597-021-00893-z","\N","\N","2023-11-08 00:42:00","2023-11-17 21:31:13" -"361","apples-ct","Apples-CT","Ct reconstruction for apple defect detection","High-throughput CT image reconstruction and defect detection for apples","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/557/logo.png","https://apples-ct.grand-challenge.org/","active","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-08 00:59:18" -"362","riadd","RIADD (ISBI-2021)","Retinal image analysis for disease detection","Retinal image analysis for multi-disease detection","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/562/Logo_ISBI_640_OO4Fuj9.png","https://riadd.grand-challenge.org/","active","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-08 00:59:20" -"363","mitoem","MitoEM","3D mitochondria segmentation benchmark","Large-scale 3d mitochondria instance segmentation benchmark","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/566/logo2.png","https://mitoem.grand-challenge.org/","active","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-08 00:59:22" -"364","a-afma","A-AFMA","Automated prenatal ultrasound measurement","Prenatal ultrasound (us) measurement of amniotic fluid is an important part of fetal surveillance as it provides a non-invasive way of assessing if there is oligohydramnios (insufficient amniotic fluid) and polyhydramnios (excess amniotic fluid), which are associated with numerous problems both during pregnancy and after birth. In this image analysis challenge, we aim to attract attention from the image analysis community to work on the problem of automated measurement of the mvp using the predefined ultrasound video clip based on a linear-sweep protocol [1]. We define two tasks. The first task is to automatically detect amniotic fluid and the maternal bladder. The second task is to identify the appropriate points for mvp measurement given the selected frame of the video clip, and calculate the length of the connected line between these points. The data was collected from women in the second trimester of pregnancy, as part of the pure study at the john radcliffe hospital in oxford, uk.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/567/Figure_3_MVP_example.png","https://a-afma.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-11 07:00:24" -"365","covid-segmentation","COVID-19 LUNG CT LESION SEGMENTATION CHALLENGE - 2020","SARS-CoV-2 lung lesion segmentation","This challenge will create the platform to evaluate emerging methods for the segmentation and quantification of lung lesions caused by SARS-CoV-2 infection from CT images.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/569/Challenge_Image.png","https://covid-segmentation.grand-challenge.org/","active","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:09:24" -"366","valdo","Where is VALDO?","Vascular lesion detection challenge 2021","This challenge aims at promoting the development of new solutions for the automated segmentation of such very sparse and small objects while leveraging weak and noisy labels. The central objective of this challenge is to facilitate quantification of CSVD in brain MRI scans.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/570/LogoVALDO.png","https://valdo.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:45:10" -"367","segpc-2021","SegPC-2021","Plasma cell cancer segmentation challenge","This challenge is positioned towards robust segmentation of cells which is the first stage to build such a tool for plasma cell cancer, namely, multiple myeloma (mm), which is a type of blood cancer.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/574/logo_fRPkhwS.png","https://segpc-2021.grand-challenge.org/","active","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-08 00:59:29" -"368","endocv2021","EndoCV2021","Endoscopy Computer Vision Challenge 2021","Computer-aided detection, localization, and segmentation methods can help improve colonoscopy procedures. Even though many methods have been built to tackle automatic detection and segmentation of polyps, benchmarking and development of computer vision methods remains an open problem. This is mostly due to the lack of datasets or challenges that incorporate highly heterogeneous dataset appealing participants to test for generalisation abilities of the methods. We aim to build a comprehensive, well-curated, and defined dataset from 6 different centres worldwide and provide 5 datasets types that include: i) multi-centre train-test split from 5 centres ii) polyp size-based split (participants should do this by themselves if of interest), iii) data centre wise split, iv) modality split (only test) and v) one hidden centre test. Participants will be evaluated on all types to address strength and weaknesses of each participants’ method. Both detection bounding boxes and pixel-wise segme...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/575/endoLogo-2021_AdZmuvg.jpg","https://endocv2021.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:38:42" -"369","fusc","Foot Ulcer Segmentation Challenge","Foot ulcer segmentation challenge","The goal of this challenge is to segment the wound area from natural images photographed during clinical visits. In the dataset provided, over 1000 images are collected over 2 years from hundreds of patients. All images are completely de-identified by removing personal identifiers defined by hipaa.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/579/Logo.png","https://fusc.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:38:28" -"370","nucmm","NucMM","Millimeter-scale nucleus 3D segmentation","Segmenting 3D cell nuclei from microscopy image volumes is critical for biological and clinical analysis, enabling the study of cellular expression patterns and cell lineages. We pushed the task forward to the sub-cubic millimeter scale and curated the NucMM dataset with two fully annotated volumes: one 0.1 mm^3 electron microscopy (EM) volume containing nearly the entire zebrafish brain with around 170,000 nuclei; and one 0.25 mm^3 micro-CT (uCT) volume containing part of a mouse visual cortex with about 7,000 nuclei.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/580/NucMM_logo.png","https://nucmm.grand-challenge.org/","completed","intermediate","5","https://doi.org/10.1007/978-3-030-87193-2_16","\N","\N","2023-11-08 00:42:00","2023-11-15 22:45:22" -"371","vessel-wall-segmentation","Carotid Artery Vessel Wall Segmentation Challenge","Carotid artery vessel wall segmentation","In this challenge, the task is to segment the vessel wall from 3D-MERGE image with high accuracy and robustness. While the challenges of segmentation in different body regions are different, all vessel wall segmentation requires the basic steps of identifying the artery (localization) and lumen and outer wall segmentation. Then the wall thickness (difference between the lumen and outer wall contours) can be measured. Other clinically usable measurements such as lumen area or percent stenosis can also be derived from the vessel wall segmentation. Therefore, this challenge focuses on the important first step of vessel wall segmentation.","","https://vessel-wall-segmentation.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:38:02" -"372","crossmoda","Cross-Modality Domain Adaptation Image Segmentation - 2021","Cross-modality domain adaptation 2021","This challenge proposes the first medical imaging benchmark of unsupervised cross-modality Domain Adaptation approaches (from contrast-enhanced T1 to high-resolution T2).","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/592/crossmoda_logo_black.png","https://crossmoda.grand-challenge.org/","active","intermediate","5","https://doi.org/10.1016/j.media.2022.102628","\N","\N","2023-11-08 00:42:00","2023-11-15 22:37:49" -"373","brainptm-2021","BrainPTM 2021","Brain pre-surgical tractography mapping","In this challenge we ask the participants to perform direct white matter tracts mapping in clinical brain MRI scans we provide. The data that is provided consists of 75 cases (patients referred for brain tumor removal) that were acquired at Sheba Medical Center at Tel HaShomer, Israel [2]. Patient pathologies include oligodendrogliomas , astrocytomas, glioblastomas and cavernomas, on first occurrence or in a post-surgical recurrence. According to the neuro-radiologist's estimation, the tumor volumes ranged from 4 (cavernoma) to 60 [cm^3] (glioblastoma multiforme). Also, different levels of edema are present around the dataset tumors, from inexistent to very significant. Along with each case both T1 Structural and Diffusion Weighted modalities are provided. For 60 cases (training) semi-manual white matters tracts mapping is provided in the form of binary segmentation maps. For the rest 15 cases (test) no tracts annotations are provided as these will be used for participants algori...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/595/logo_square.jpg","https://brainptm-2021.grand-challenge.org/","active","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-16 17:40:36" -"374","cholectriplet2021","CholecTriplet 2021","EndoVis sub-challenge for surgical action","This sub-challenge focuses on exploiting machine learning methods for the online automatic recognition of surgical actions as a series of triplets. Participants will develop and compete with algorithms to recognize action triplets directly from the provided surgical videos. This novel challenge investigates the state-of-the-art on surgical fine-grained activity recognition and will establish a new promising research direction in computer-assisted surgery.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/596/logo-challenge.png","https://cholectriplet2021.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:37:21" -"375","paip2021","PAIP2021","PAIP 2021 challenge: perineural invasion","PAIP 2021 challenge aims to promote the development of a common algorithm for automatic detection of perineural invasion in resected specimens of multi-organ cancers. PAIP 2021 challenge will have a technical impact in the following fields: detection of composite targets (nerve and tumor) and common modeling for target images in multiple backgrounds. This challenge will provide a good opportunity to overcome the limitations of current disease-organ-specific modeling and develop a technological approach to the universality of histology in multiple organs.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/598/640-640.png","https://paip2021.grand-challenge.org/","active","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:37:00" -"376","flare","FLARE21","Abdominal organ segmentation challenge","Abdominal organ segmentation plays an important role in clinical practice, and to some extent, it seems to be a solved problem because the state-of-the-art methods have achieved inter-observer performance in several benchmark datasets. However, most of the existing abdominal datasets only contain single-center, single-phase, single-vendor, or single-disease cases, and it is unclear whether the excellent performance can be generalized on more diverse datasets. Moreover, many SOTA methods use model ensembles to boost performance, but these solutions usually have a large model size and cost extensive computational resources, which are impractical to be deployed in clinical practice. To address these limitations, we organize the Fast and Low GPU Memory Abdominal Organ Segmentation challenge that has two main features: (1) the dataset is large and diverse, includes 511 cases from 11 medical centers. (2) we not only focus on segmentation accuracy but also segmentation efficiency, whi...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/599/logo_hDqJ8uG.gif","https://flare.grand-challenge.org/","active","intermediate","5","https://doi.org/10.1016/j.media.2022.102616","\N","\N","2023-11-08 00:42:00","2023-11-15 22:36:39" -"377","nucls","NuCLS","Triple-negative breast cancer nuclei challenge","Classification, Localization and Segmentation of nuclei in scanned FFPE H&E stained slides of triple-negative breast cancer from The Cancer Genome Atlas. See: Amgad et al. 2021. arXiv:2102.09099 [cs.CV].","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/601/TCGA-AR-A0U4-DX1_id-5ea40a88ddda5f8398990ccf_left-42405_top-70784_bo_PgpXdUu.png","https://nucls.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:29:28" -"378","bcsegmentation","Breast Cancer Segmentation","Triple-negative breast cancer segmentation","Semantic segmentation of histologic regions in scanned FFPE H&E stained slides of triple-negative breast cancer from The Cancer Genome Atlas. See: Amgad M, Elfandy H, ..., Gutman DA, Cooper LAD. Structured crowdsourcing enables convolutional segmentation of histology images. Bioinformatics. 2019. doi: 10.1093/bioinformatics/btz083","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/602/BCSegmentationLogo.png","https://bcsegmentation.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:29:37" -"379","feta","FeTA - Fetal Tissue Annotation Challenge","Fetal tissue annotation challenge","The Fetal Tissue Annotation and Segmentation Challenge (FeTA) is a multi-class, multi-institution image segmentation challenge part of MICCAI 2022. The goal of FeTA is to develop generalizable automatic multi-class segmentation methods for the segmentation of developing human brain tissues that will work with data acquired at different hospitals. The challenge provides manually annotated, super-resolution reconstructed MRI data of human fetal brains which will be used for training and testing automated multi-class image segmentation algorithms. In FeTA 2021, we used the first publicly available dataset of fetal brain MRI to encourage teams to develop automatic brain tissue segmentation algorithms. This year, FeTA 2022 takes it to the next level by launching a multi-center challenge for the development of image segmentation algorithms that will be generalizable to different hospitals with unseen data. We will include data from two institutions in the training dataset, and there wi...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/604/FeTA_logo_640.png","https://feta.grand-challenge.org/","upcoming","intermediate","5","","2024-03-21","2024-04-26","2023-11-08 00:42:00","2023-11-15 22:36:15" -"380","fastpet-ld","fastPET-LD","PET scan ""hot spots"" detection challenge","In this challenge, we provide 2 training datasets of 68 cases each: the first one was acquired at Sheba medical center (Israel) nuclear medicine department with a very-short exposure of 30s pbp, while the second is the same data followed by a denoising step implemented by a fully convolutional Dnn architecture trained under perceptual loss [1,2]. The purpose of this challenge is the detection of “hot spots”, that is locations that have an elevated standard uptake value (SUV) and potential clinical significance. Corresponding CT scans are also provided. The ground truth, common to both datasets, was generated by Dr. Liran Domachevsky, chair of nuclear medicine at Sheba medical center. It consists of a 3-D segmentation map of the hot spots as well as an Excel file containing the position and size of a 3D cuboid bounding box for each hot spot.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/605/IMG_19052021_144815_600_x_600_pixel.jpg","https://fastpet-ld.grand-challenge.org/","active","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:35:52" -"381","autoimplant2021","AutoImplant 2021","Automatic cranial implant design challenge","Please see our AutoImplant 2020 website for an overview of the cranial implant design topic. Our 2nd AutoImplant Challenge (referred to as AutoImplant 2021) sees the (not limited to) following three major improvements compared to the prior edition, besides a stronger team: Real craniotomy defective skulls will be provided in the evaluation phase. Task specific metrics (e.g., boundary Dice Score) that are optimally in agreement with the clinical criteria of cranial implant design will be implemented and used. Besides a metric-based scoring and ranking system, neurosurgeons will be invited to verify, score and rank the participants-submitted cranial implants based their clinical usability (for the real cases in Task 2).","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/607/AutoImplant_2021_Logo.png","https://autoimplant2021.grand-challenge.org/","completed","intermediate","5","https://doi.org/10.1109/tmi.2021.3077047","\N","\N","2023-11-08 00:42:00","2023-11-16 17:41:01" -"382","dfu-2021","DFUC2021","Diabetic foot ulcer challenge 2021","We have received approval from the UK National Health Service (NHS) Re-search Ethics Committee (REC) to use these images for the purpose of research. The NHS REC reference number is 15/NW/0539. Foot images with DFU were collected from the Lancashire Teaching Hospital over the past few years. Three cameras were used for capturing the foot images, Kodak DX4530, Nikon D3300and Nikon COOLPIX P100. The images were acquired with close-ups of the full foot at a distance of around 30–40 cm with the parallel orientation to the plane of an ulcer. The use of flash as the primary light source was avoided, and instead, adequate room lights were used to get the consistent colours in images. Images were acquired by a podiatrist and a consultant physician with specialization in the diabetic foot, both with more than 5 years professional experience. As a pre-processing stage, we have discarded photographs with out of focus and blurry artefacts. The DFUC2021 consists of 15,683 DFU patche...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/608/footsnap_logo.png","https://dfu-2021.grand-challenge.org/","active","intermediate","5","https://doi.org/10.1007/978-3-030-94907-5_7","\N","\N","2023-11-08 00:42:00","2023-11-16 17:41:08" -"383","saras-mesad","SARAS-MESAD","MICCAI 2021 multi-domain surgeon action detection","This challenge is organized under MICCAI 2021, the 24th International Conference on Medical Image Computing and Computer Assisted Intervention. The event will be held from September 27th to October 1st 2021 in Strasbourg, France. The challenge focuses on multi-domain surgeon action detection.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/609/Screenshot_3.png","https://saras-mesad.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:30:14" -"384","node21","NODE21","NODE21: nodule generation and detection","Among both men and women, lung cancer causes the greatest number of cancer deaths worldwide. Symptoms of lung cancer typically occur at an advanced stage of the disease, when treatment has a reduced chance of success. Early detection is therefore a key factor in reducing mortality rates from lung cancer. Pulmonary nodules, detected through imaging, are the initial manifestation of lung cancer, visible well before clinical symptoms or signs emerge. They can be visible on a chest radiograph (CXR), and chest radiography is by far the most common radiological exam in the world. Thus, CXR plays a critical role in the accurate identification of nodules in the drive towards early detection of lung cancer. Pulmonary nodules are frequently encountered as incidental findings in patients undergoing routine examination or CXR imaging for issues unrelated to lung cancer.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/612/node21logo.jpg","https://node21.grand-challenge.org/","active","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:34:20" -"385","wsss4luad","WSSS4LUAD","WSSS4LUAD semantic segmentation challenge","The WSSS4LUAD dataset contains over 10,000 patches of lung adenocarcinoma from whole slide images from Guangdong Provincial People's Hospital and TCGA with image-level annotations. The goal of this challenge is to perform semantic segmentation for differentiating three important types of tissues in the WSIs of lung adenocarcinoma, including cancerous epithelial region, cancerous stroma region and normal region. Paticipants have to use image-level annotations to give pixel-level prediction.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/621/%E6%88%AA%E5%B1%8F2021-07-05_%E4%B8%8A%E5%8D%8810.17.09.png","https://wsss4luad.grand-challenge.org/","active","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:30:23" -"386","ski10","SKI10","SKI10 cartilage and bone segmentation challenge","Welcome to the SKI10 website. The goal of SKI10 was to compare different algorithms for cartilage and bone segmentation from knee MRI data. Knee cartilage segmentation is a clinically relevant segmentation problem that has gained considerable importance in recent years. Among others, it is used to quantify cartilage deterioration for the diagnosis of Osteoarthritis and to optimize surgical planning of knee implants. See the SKI10 paper in the SKI10 Zenodo repository for further details. SKI10 started out as one of the three competitions of the Grand Challenge Workshop 2010, organized in conjunction with the MICCAI 2010 conference.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/624/ski10sq-big.png","https://ski10.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:31:16" -"387","emsig","EMSIG","EMSIG hackathon: radar-based activity recognition","Welcome to the EMSIG Hackathon 2021, organised by EMSIG (www.emsig.org.uk/), the University of Glasgow, Edinburgh Napier University, UCL, DSTL and BAE Systems plc. The goal of the challenge is to evaluate and compare algorithms for human activity recognition based on radar data. We invite the UK radar community to participate by developing and testing existing and novel automated classification methods.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/628/EMSIGgroup_nYL722C.png","https://emsig.grand-challenge.org/","active","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:30:58" -"388","qubiq21","QUBIQ2021","Quantification of uncertainties challenge 2021","The QUBIQ challenge deals with benchmarking algorithms that quantify uncertainties in biomedical image segmentation. Participants will work on binary segmentation tasks, all of which with multiple annotations from domain experts. To be segmented are various pathologies and anatomical structures, such as brain, kidney, or prostate, in MR or CT image data. A successful algorithm will segment these structures and reproduce the distribution of the experts’ annotations.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/629/brain.png","https://qubiq21.grand-challenge.org/","active","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:30:44" -"389","midog2021","MIDOG Challenge 2021","Mitosis domain generalization challenge 2021","Motivation: Mitosis detection is a key component of tumor prognostication for various tumors, including breast cancer. Scanning microscopy slides with different scanners leads to a significant visual difference, resulting in a domain shift. This domain shift prevents most deep learning models from generalizing to other scanners, leading to strongly reduced performance.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/633/midog_logo.png","https://midog2021.grand-challenge.org/","completed","intermediate","5","https://doi.org/10.5281/zenodo.4573978","\N","\N","2023-11-08 00:42:00","2023-11-15 22:26:47" -"390","tiger","TIGER","Tumor infiltrating lymphocytes assessment","TIGER is the first challenge on fully automated assessment of tumor-infiltrating lymphocytes (TILs) in H&E breast cancer slides. It is organized by the Diagnostic Image Analysis Group (DIAG) of the Radboud University Medical Center (Radboudumc) in Nijmegen (The Netherlands), in close collaboration with the International Immuno-Oncology Biomarker working Group (www.tilsinbreastcancer.org). The goal of this challenge is to evaluate new computer algorithms for the automated assessment of tumor-infiltrating lymphocytes (TILs) in Her2 positive and Triple Negative breast cancer (BC) histopathology slides. In recent years, several studies have shown the predictive and prognostic value of visually scored TILs in BC as well as in other cancer types, making TILs a powerful biomarker that can potentially be used in the clinic. With TIGER, we aim at developing computer algorithms that can automatically generate a ""TIL score"" with a high prognostic value.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/636/tiger-logo_qr7B8JU.png","https://tiger.grand-challenge.org/","active","intermediate","5","","2022-02-03","\N","2023-11-08 00:42:00","2023-11-15 22:26:17" -"391","stoic2021","STOIC2021 - COVID-19 AI Challenge","COVID-19 AI challenge: CT diagnosis and prognosis","We are launching an artificial intelligence challenge aimed at predicting the severe outcome of COVID-19, based on the largest dataset of Computed Tomography (CT) images of COVID-19 suspects and patients collected to date. Participants will have access to data from the STOIC project, recently published in Radiology. The STOIC project collected CT images of 10,735 individuals suspected of being infected with SARS-COV-2 during the first wave of the pandemic in France, from March to April 2020. The focus of the challenge is the prediction of severe COVID-19, defined as intubation or death within one month from the acquisition of the CT scan (AUC, primary metric). COVID19 positivity will be assessed as a secondary metric in the leaderboard.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/637/stoic2021logo_B3b4JM9.png","https://stoic2021.grand-challenge.org/","active","intermediate","5","","2021-12-23","2028-01-01","2023-11-08 00:42:00","2023-11-15 22:24:32" -"392","cxr-covid19","Chest XR COVID-19 detection","AI models for COVID-19 detection in chest x-rays","The Coronavirus Disease 2019 (COVID-19) has spread globally and caused unprecedented damages worldwide. Technology, in particular AI, can play an important role in helping fight against this pandemic. In addition, lessons learned can be helpful in fighting and preventing future pandemics. Multiple hospitals and health professionals have shared COVID-19 images coming from multiple modalities to help advance the research in the field. This challenge aims to develop a multiclass classification algorithm capable of detecting COVID-19 in Chest X-ray images. The dataset contains 3 image classes: COVID-19, Pneumonia and Normal (healthy) (See example images below). With 20,000+ images, the participants can train their algorithms to solve this challenge. A test set will be released and will be used to benchmark the obtained results. This Challenge is part of the ‘Ethics and Explainability for Responsible Data Science (EE-RDS) conference’ which will be held virtually and in Johannesburg (So...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/638/CovidChallenge.png","https://cxr-covid19.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:13:57" -"393","pi-cai","The PI-CAI Challenge","AI and radiologists: prostate cancer detection","Prostate cancer (PCa) is one of the most prevalent cancers in men. One million men receive a diagnosis and 300,000 die from clinically significant PCa (csPCa) (defined as ISUP ≥ 2 cancer) each year, worldwide. Multiparametric magnetic resonance imaging (mpMRI) is playing an increasingly important role in the early diagnosis of prostate cancer, and has been recommended by the 2019 European Association of Urology (EAU) guidelines and the 2019 UK National Institute for Health and Care Excellence (NICE) guidelines, prior to biopsies (Mottet et al., 2021). However, current guidelines for reading prostate mpMRI (i.e. PI-RADS v2.1) follow a semi-quantitative assessment, mandating substantial expertise for proper usage. Moreover, prostate cancer can exhibit a broad range of clinical behavior and highly heterogeneous morphology in MRI. As such, assessments are susceptible to low inter-reader agreement (<50%), sub-optimal interpretation and overdiagnosis (Rosenkrantz et al., 2016, Westphale...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/642/square_logo_we441sa.jpg","https://pi-cai.grand-challenge.org/","active","intermediate","5","https://doi.org/10.5281/zenodo.6667655","2022-06-12","\N","2023-11-08 00:42:00","2023-11-15 22:10:32" -"394","ultra-low-dose-pet","Ultra-low Dose PET Imaging Challenge","Low-dose PET scanner imaging recovery challenge","This challenge aims to develop computational algorithms capable of recovering high-quality imaging from low statistics corresponding to low dose scans, with the hope of reducing the radiation exposure to be equivalent to transatlantic flight.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/643/Ultra-low_Dose_PET-01.jpg","https://ultra-low-dose-pet.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:09:48" -"395","airogs","AIROGS","AI for robust glaucoma screening challenge","Early detection of glaucoma can avoid visual impairment, which could be facilitated through screening. Artificial intelligence (AI) could increase the cost-effectiveness of glaucoma screening, by reducing the need for manual labor. AI approaches for glaucoma detection from color fundus photography (CFP) have been proposed and promising at-the-lab performances have been reported. However, large performance drops often occur when AI solutions are applied in real-world settings. Unexpected out-of-distribution data and bad quality images are major causes for this performance drop. Aim: The development of solutions for glaucoma screening from CFP that are robust to real-world scenarios.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/644/logo2-01-logo.png","https://airogs.grand-challenge.org/","active","intermediate","5","","2021-12-01","\N","2023-11-08 00:42:00","2023-11-15 22:03:44" -"396","conic-challenge","CoNIC 2022","Colon nuclei identification and counting 2022","The CoNIC challenge starts with the discovery phase where we share the training data, challenge goals, and the evaluation code. Participants should start experimenting with the dataset and train/validate their model on it. All challenge submissions are in the form of a docker container, which means that participants should submit their method to be evaluated on the test sets. In other words, only the training set will be released during the challenge and participants will not have access to any part of the test set. The test will be done in two phases. The first phase, the preliminary test, will give participants a chance to work on their submissions for two weeks, get familiar with the submission workflow, improve their code if needed, and make sure their method works fine in the challenge evaluation pipeline. We will release a template docker structure and tutorials on how participants should package their code using the template and submit it to the challenge website. During ...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/648/conic_logo_YbqWBDc.png","https://conic-challenge.grand-challenge.org/","active","intermediate","5","https://arxiv.org/abs/2111.14485","2022-02-13","\N","2023-11-08 00:42:00","2023-11-15 22:03:23" -"397","cholectriplet2022","CholecTriplet2022: Surgical Action Triplet Detection","Dounding box localization of the regions of action triplets","Formalizing surgical activities as triplets of the used instruments, actions performed, and target anatomies acted upon provides a better, comprehensive and fine-grained modeling of surgical activities. Automatic recognition of these triplet activities directly from surgical videos would facilitate the development of intra-operative decision support systems that are more helpful, especially for safety, in the operating room (OR). Our previous EndoVIS challenge, CholecTriplet2021 (MICCAI 2021), and existing works on surgical action triplet recognition tackles this as a multi-label classification of all possible combinations. For better clinical utility, real-time modeling of tool-tissue interaction will go beyond determining the presence of these action triplets, to also include estimating their locations in each video frame. Hence, this challenge extends our previous challenge on action triplet recognition to also include bounding box localization of the...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/649/t50-logo-2022_kz11kSp.png","https://cholectriplet2022.grand-challenge.org/","completed","intermediate","5","https://doi.org/10.1007/978-3-030-59716-0_35","\N","\N","2023-11-08 00:42:00","2023-11-27 20:45:26" -"398","endocv2022","EndoCV2022","Endoscopic video sequence detection and segmentation","Accurate detection of artefacts is a core challenge in a wide-range of endoscopic applications addressing multiple different disease areas. The importance of precise detection of these artefacts is essential for high-quality endoscopic video acquisition crucial for realising reliable computer assisted endoscopy tools for improved patient care. In particular, colonoscopy requires colon preparation and cleaning to obtain improved adenoma detection rate. Computer aided systems can help to guide both expert and trainee endoscopists to obtain consistent high quality surveillance and detect, localize and segment widely known cancer precursor lesion, “polyps”. While deep learning has been successfully applied in the medical imaging, generalization is still an open problem. Generalizability issue of deep learning models need to be clearly defined and tackled to build more reliable technology for clinical translation. Inspired by the enthusiasm of participants on our previous challenges, t...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/650/EndoCV2022-logo-v2.jpg","https://endocv2022.grand-challenge.org/","completed","intermediate","5","https://doi.org/10.1016/j.media.2021.102002","2022-02-20","\N","2023-11-08 00:42:00","2023-11-15 21:56:32" -"399","mela","MELA2022","MICCAI 2022 MELA challenge: ct scan benchmark","The mediastinum is the common site of various lesions, including hyperplasia, cysts, tumors, and lymph nodes transferred from the lungs, which might cause serious problems due to their location. Therefore, the detection of mediastinal lesions has important indications for the early screening and diagnosis of related diseases. Computer-aided diagnosis methods have been developed to assist doctors in interpreting massive computed tomography (CT) scans. However, few prior studies investigate deep learning methods on this labor-intensive task. This challenge establishes a large-scale benchmark dataset to automatically detect mediastinal lesions from 1100 CT scans, consisting of 770 CTs for training, 110 CTs for validation, and 220 CTs for testing. Each annotation file includes coordinates of the bounding box of each mediastinal lesion region per CT scan for serving the task of detection. We hope this challenge could facilitate the research and application of automatic mediastinal lesi...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/651/LOGO-%E8%93%9D-900.png","https://mela.grand-challenge.org/","completed","intermediate","5","","2022-07-02","2022-07-17","2023-11-08 00:42:00","2023-11-15 21:56:16" -"400","kipa22","KiPA22 (Regular Challenge)","Kidney and artery segmentation challenge","The challenge is aimed to segment kidney, renal tumors, arteries, and veins from computed tomography angiography (CTA) images in one inference.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/654/logo3_%E5%89%AF%E6%9C%AC.png","https://kipa22.grand-challenge.org/","active","intermediate","5","https://doi.org/10.1016/j.media.2021.102055","2022-07-01","\N","2023-11-08 00:42:00","2023-11-17 23:31:41" -"401","parse2022","Parse2022","Pulmonary artery segmentation challenge 2022","It is of significant clinical interest to study pulmonary artery structures in the field of medical image analysis. One prerequisite step is to segment pulmonary artery structures from CT with high accuracy and low time-consuming. The segmentation of pulmonary artery structures benefits the quantification of its morphological changes for diagnosis of pulmonary hypertension and thoracic surgery. However, due to the complexity of pulmonary artery topology, automated segmentation of pulmonary artery topology is a challenging task. Besides, the open accessible large-scale CT data with well labeled pulmonary artery are scarce (The large variations of the topological structures from different patients make the annotation an extremely challenging process). The lack of well labeled pulmonary artery hinders the development of automatic pulmonary artery segmentation algorithm. Hence, we try to host the first Pulmonary ARtery SEgmentation challenge in MICCAI 2022 (Named Parse2022) to start a...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/658/logo.jpg","https://parse2022.grand-challenge.org/","active","intermediate","5","","2023-06-30","\N","2023-11-08 00:42:00","2023-11-17 23:31:47" -"402","tdsc-abus2023","TDSC-ABUS2023","Automated 3D breast ultrasound tumor challenge","Tumor Detection, Segmentation And Classification Challenge On Automated 3D Breast Ultrasound","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/662/logo.png","https://tdsc-abus2023.grand-challenge.org/","completed","intermediate","5","","2023-07-15","2023-08-20","2023-11-08 00:42:00","2023-11-08 01:00:36" -"403","instance","INSTANCE2022","Intracranial hemorrhage segmentation challenge 2022","Participants are required to segment Intracranial Hemorrhage region in Non-Contrast head CT (NCCT).","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/667/Logo_%E9%A1%B5%E9%9D%A2_2.png","https://instance.grand-challenge.org/","active","intermediate","5","https://doi.org/10.1109/jbhi.2021.3103850","2022-07-14","\N","2023-11-08 00:42:00","2023-11-15 21:55:33" -"404","bcnb","BCNB","Early breast cancer core-needle biopsy dataset","Breast cancer (BC) has become the greatest threat to women’s health worldwide. Clinically, identification of axillary lymph node (ALN) metastasis and other tumor clinical characteristics such as ER, PR, and so on, are important for evaluating the prognosis and guiding the treatment for BC patients. Several studies intended to predict the ALN status and other tumor clinical characteristics by clinicopathological data and genetic testing score. However, due to the relatively poor predictive values and high genetic testing costs, these methods are often limited. Recently, deep learning (DL) has enabled rapid advances in computational pathology, DL can perform high-throughput feature extraction on medical images and analyze the correlation between primary tumor features and above status. So far, there is no relevant research on preoperatively predicting ALN metastasis and other tumor clinical characteristics based on WSIs of primary BC samples.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/668/BCNB-logo_CUGMa0V.png","https://bcnb.grand-challenge.org/","completed","intermediate","5","https://doi.org/10.3389/fonc.2021.759007","\N","\N","2023-11-08 00:42:00","2023-11-16 17:41:33" -"405","ravir","RAVIR","Retinal arteries and veins segmentation dataset","The retinal vasculature provides important clues in the diagnosis and monitoring of systemic diseases including hypertension and diabetes. The microvascular system is of primary involvement in such conditions, and the retina is the only anatomical site where the microvasculature can be directly observed. The objective assessment of retinal vessels has long been considered a surrogate biomarker for systemic vascular diseases, and with recent advancements in retinal imaging and computer vision technologies, this topic has become the subject of renewed attention. In this paper, we present a novel dataset, dubbed RAVIR, for the semantic segmentation of Retinal Arteries and Veins in Infrared Reflectance (IR) imaging. It enables the creation of deep learning-based models that distinguish extracted vessel type without extensive post-processing.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/673/IR_Case_022.png","https://ravir.grand-challenge.org/","active","intermediate","5","https://doi.org/10.1109/jbhi.2022.3163352","2022-07-18","\N","2023-11-08 00:42:00","2023-11-16 17:41:34" -"406","dfuc2022","DFUC 2022","Diabetic foot ulcer (DFU) segmentation challenge","Diabetes is a global epidemic affecting around 425 million people and expected to rise to 629 million by 2045. Diabetic Foot Ulcer (DFU) is a severe condition that can result from the disease. The rise of the condition over the last decades is a challenge for healthcare systems. Cases of DFU usually lead to severe conditions that greatly prolongs treatment and result in limb amputation or death. Recent research focuses on creating detection algorithms to monitor their condition to improve patient care and reduce strain on healthcare systems. Work between Manchester Metropolitan University, Lancashire Teaching Hospitals and Manchester University NHS Foundation Trust has created an international repository of up to 11,000 DFU images. Analysis of ulcer regions is a key for DFU management. Delineation of ulcers is time-consuming. With effort from the lead scientists of the UK, US, India and New Zealand, this challenge promotes novel work in DFU segmentation and promote interdisciplina...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/674/footsnap_logo.png","https://dfuc2022.grand-challenge.org/","active","intermediate","5","https://arxiv.org/abs/2204.11618","2022-06-20","\N","2023-11-08 00:42:00","2023-11-17 23:32:01" -"407","atlas","ATLAS R2.0 - Stroke Lesion Segmentation","Anatomical tracings of lesions after stroke","Accurate lesion segmentation is critical in stroke rehabilitation research for the quantification of lesion burden and accurate image processing. Current automated lesion segmentation methods for T1-weighted (T1w) MRIs, commonly used in rehabilitation research, lack accuracy and reliability. Manual segmentation remains the gold standard, but it is time-consuming, subjective, and requires significant neuroanatomical expertise. However, many methods developed with ATLAS v1.2 report low accuracy, are not publicly accessible or are improperly validated, limiting their utility to the field. Here we present ATLAS v2.0 (N=1271), a larger dataset of T1w stroke MRIs and manually segmented lesion masks that includes training (public. n=655), test (masks hidden, n=300), and generalizability (completely hidden, n=316) data. Algorithm development using this larger sample should lead to more robust solutions, and the hidden test and generalizability datasets allow for unbiased performance eval...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/676/ATLAS_Logo_square.png","https://atlas.grand-challenge.org/","active","intermediate","5","https://doi.org/10.1101/2021.12.09.21267554","2022-09-18","\N","2023-11-08 00:42:00","2023-11-15 21:54:33" -"408","3dteethseg","3D Teeth Scan Segmentation and Labeling Challenge MICCAI2022","Teeth segmentation in orthodontic CAD systems","Computer-aided design (CAD) tools have become increasingly popular in modern dentistry for highly accurate treatment planning. In particular, in orthodontic CAD systems, advanced intraoral scanners (IOSs) are now widely used as they provide precise digital surface models of the dentition. Such models can dramatically help dentists simulate teeth extraction, move, deletion, and rearrangement and therefore ease the prediction of treatment outcomes. Although IOSs are becoming widespread in clinical dental practice, there are only few contributions on teeth segmentation/labeling available in the literature and no publicly available database. A fundamental issue that appears with IOS data is the ability to reliably segment and identify teeth in scanned observations. Teeth segmentation and labelling is difficult as a result of the inherent similarities between teeth shapes as well as their ambiguous positions on jaws.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/680/Grand-Challenge-Logo_2.jpg","https://3dteethseg.grand-challenge.org/","completed","intermediate","5","","2022-07-01","2022-08-15","2023-11-08 00:42:00","2023-11-17 23:32:08" -"409","flare22","MICCAI FLARE 2022","Fast and low-resource abdominal organ segmentation","We extend the FLARE 2021 Challenge from fully supervised settings to a semi-supervised setting that focuses on how to use unlabeled data. Specifically, we provide a small number of labeled cases (50) and a large number of unlabeled cases (2000) in the training set, 50 visible cases for validation, and 200 hidden cases for testing. The segmentation targets include 13 organs: liver, spleen, pancreas, right kidney, left kidney, stomach, gallbladder, esophagus, aorta, inferior vena cava, right adrenal gland, left adrenal gland, and duodenum. In addition to the typical Dice Similarity Coefficient (DSC) and Normalized Surface Dice (NSD), our evaluation metrics also focus on the inference speed and resources (GPU, CPU) consumption. Compare to the FLARE 2021 challenge, the dataset is 4x larger and the segmentations targets are increased to 13 organs. Moreover, the resource-related metrics are changed to the area under GPU memory-time curve and the area under CPU utilization-time curve rat...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/683/challenge-logo_xJtvQKE.png","https://flare22.grand-challenge.org/","active","intermediate","5","https://doi.org/10.1109/tpami.2021.3100536","2023-01-01","\N","2023-11-08 00:42:00","2023-11-15 21:54:18" -"410","aggc22","AGGC22","Segment the Circle of Willis vessel components for both CTA and MRA","Driving innovation in computational pathology for prostate cancer diagnosis. Develop algorithms to identify Gleason Patterns in H&E-stained whole slide images.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/684/logo_yEwrCqI.PNG","https://aggc22.grand-challenge.org/","active","intermediate","5","","2022-06-29","\N","2023-11-08 00:42:00","2023-11-17 23:32:15" -"411","autopet","autoPET","Whole-body FDG-PET/CT lesion segmentation","Automatic tumor lesion segmentation in whole-body FDG-PET/CT on large-scale database of 1014 studies of 900 patients (training database) acquired on a single site: accurate and fast lesion segmentation avoidance of false positives (brain, bladder, etc.) Testing will be performed on 200 150 studies (held-out test database) with 100 studies originating from the same hospital as the training database and 100 50 are drawn from a different hospital with similar acquisition protocol to assess algorithm robustness and generalizabilit","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/686/autopet-5.png","https://autopet.grand-challenge.org/","completed","intermediate","5","","2022-05-02","2022-09-04","2023-11-08 00:42:00","2023-11-15 21:53:42" -"412","acrobat","ACROBAT 2023","Acrobat challenge: WSI registration in breast cancer","The ACROBAT challenge aims to advance the development of WSI registration algorithms that can align WSIs of IHC-stained breast cancer tissue sections to corresponding tissue regions that were stained with H&E. All WSIs originate from routine diagnostic workflows.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/687/final_logo_1280x1280_qgi9ILO.png","https://acrobat.grand-challenge.org/","active","intermediate","5","","2022-06-15","\N","2023-11-08 00:42:00","2023-11-17 23:32:30" -"413","surgt","SurgT: Surgical Tracking","Surgical video tracking for trajectory estimation","This challenge consists of surgical videos with a target bounding box and the participants are expected to develop visual tracking algorithms to estimate the trajectory of the bounding box throughout the video-sequence.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/688/Screenshot_from_2022-06-27_09-41-30.png","https://surgt.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:32:36" -"414","slcn","Surface Learning for Clinical Neuroimaging","Developmental phenotypes prediction from cortical imaging","The goal of this challenge will therefore be to elicit submissions of novel methods for registration-free or registration-robust cortical phenotype regression, with emphasis on interpretable or explainable machine learning methods which deliver biomarkers predictive of risk for neurodevelopmental impairment. These will be benchmarked on the tasks of regression of gestational age at birth (seen as a correlate of prematurity) on both registered and native space cortical surface data.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/689/SLCN_Logo.png","https://slcn.grand-challenge.org/","completed","intermediate","5","https://doi.org/10.1016/j.neuroimage.2018.01.054","2022-04-24","2022-07-15","2023-11-08 00:42:00","2023-11-15 21:53:02" -"415","p2ilf","Preoperative to Intraoperative Laparoscopy Fusion","Preoperative to intraoperative laparoscopy fusion","Augmented reality (AR) in laparoscopic liver surgery needs key landmark detection in intraoperative 2D laparoscopic images and its registration with the preoperative 3D model from CT/MRI data. Such AR techniques are vital to surgeons as they enable precise tumor localisation for surgical removal. A full resection of targeted tumor minimises the risk of recurrence. However, the task of automatic anatomical curve segmentation (considered as landmarks), and its registration to 3D models is a non-trivial and complex task. Most developed methods in this domain are built around traditional methodologies in computer vision. This challenge is designed to challenge participants to deploy machine learning methods for two tasks - Task I: segmentation of five key anatomical curves from laparoscopic video images and 3D model, including ridge (L, R), ligament, silhouettes, liver boundary; Task 2: matching these segmented curves to the 3D liver model from volumetric data (CT/MR).","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/690/logo_V3.png","https://p2ilf.grand-challenge.org/","completed","intermediate","5","","2022-09-02","2022-09-14","2023-11-08 00:42:00","2023-11-15 21:52:39" -"416","hecktor","MICCAI HECKTOR 2022","Head and neck tumor segmentation in PET/CT","Following the success of the first two editions of the HECKTOR challenge in 2020 and 2021, this challenge will be presented at the 25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2022. Two tasks are proposed this year (participants can choose to participate in either or both tasks): Task 1: The automatic segmentation of Head and Neck (H&N) primary tumors and lymph nodes (new!) in FDG-PET/CT images; Task 2: The prediction of patient outcomes, namely Recurrence-Free Survival (RFS) from the FDG-PET/CT images and available clinical data.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/691/grandchallenge_logo_d8JNqKz.png","https://hecktor.grand-challenge.org/","active","intermediate","5","https://doi.org/10.1007/978-3-030-98253-9","2022-08-26","2024-05-01","2023-11-08 00:42:00","2023-11-15 21:52:24" -"417","k2s","K2S: from undersampled K-space To automatic Segmentation","K2s: undersampled k-space to segmentation","Magnetic resonance imaging (MRI) is the modality of choice for evaluating knee joint degeneration, but it can be susceptible to long acquisition times, tedious post processing, and lack of standardization. One of the most compelling applications of deep learning, therefore, is accelerated analysis of knee MRI. In addition to faster MRI acquisition, deep learning has enhanced image post-processing applications such as tissue segmentation. While fast, undersampled MRI acquisition may not have qualitative, visual acuity that comes from fully-sampled data, the underlying embedding space may be adequate for some applications. The implications for down-stream tasks such as tissue segmentation using convolutional neural networks are not well-characterized. Efficient segmentation of key anatomical structures from undersampled data is an open question that has clinical relevance, e.g., patient triage. The goal of this challenge, therefore, is to train segmentation models from 8x undersamp...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/692/K2S_gradient_5AE5wa5.png","https://k2s.grand-challenge.org/","completed","intermediate","5","https://doi.org/10.1148/ryai.2021200165","2022-05-16","2022-06-16","2023-11-08 00:42:00","2023-11-15 21:51:47" -"418","drac22","Diabetic Retinopathy Analysis Challenge MICCAI2022","DR lesions segmentation in UW-OCTA-M images","Diabetic retinopathy is one of the leading causes of blindness and affects approximately 78% people, with a history of diabetes of 15 years or longer [1]. DR often causes gradual changes in vasculature structure and resulting abnormalities. DR is diagnosed by visually inspecting retinal fundus images for the presence of retinal lesions, such as microaneurysms (MAs), intraretinal microvascular abnormalities (IRMAs), nonperfusion areas and neovascularization. The detection of these lesions is critical to the diagnosis of DR. There have been some works using fundus images for DR diagnosis [2]. With rising popularity, OCT angiography (OCTA) has the capability of visualizing the retinal and choroidal vasculature at a microvascular level in great detail [3]. Specially, swept-source (SS)-OCTA allows additionally the individual assessment of the choroidal vasculature. There are already some works using SS-OCTA to grade for qualitative features of diabetic retinopathy [4-6]. Further, ultra...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/694/logo_kT1YYna.png","https://drac22.grand-challenge.org/","active","intermediate","5","","2022-08-07","\N","2023-11-08 00:42:00","2023-11-15 21:50:58" -"419","amos22","Multi-Modality Abdominal Multi-Organ Segmentation Challenge 2022","Multi-modality abdominal multi-organ segmentation","Abdominal multi-organ segmentation is one of the most attractive topics in the field of medical image analysis, which plays an important role in supporting clinical workflows such as disease diagnosis and treatment planning. The recent success of deep learning methods applied for abdominal multi-organ segmentation exposes the lack of large-scale comprehensive benchmarks for developing and comparing such methods. While several benchmark datasets for abdominal organ segmentation are available, the limited number of organs of interest and training samples still limits the power of modern deep models and makes it difficult to provide a fully comprehensive and fair estimate of different methods. And, most research in medical image analysis today focuses on building bespoke systems to handle stereotypical inputs and outputs associated with a single task, the complexity of systems like this can grow dramatically as the inputs or outputs grow more diverse. If a single algorithm could h...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/695/AMOS_2022.png","https://amos22.grand-challenge.org/","active","intermediate","5","","2022-10-09","2060-12-31","2023-11-08 00:42:00","2023-11-15 21:50:34" -"420","surgtoolloc","Surgical Tool Localization in endoscopic videos","Surgical tool localization in endoscopic videos","The ability to automatically detect and track surgical instruments in endoscopic video will enable many transformational interventions. Assessing surgical performance and efficiency, identifying skilled tool use and choreography, and planning operational and logistical aspects of OR resources are just some of the applications that would benefit. Unfortunately obtaining the annotations needed to train machine learning models to identify and localize surgical tools is a difficult task. Annotating bounding boxes frame-by-frame in video is tedious and time consuming, yet a wide variety of surgical tools and surgeries must be captured for robust training. Moreover, ongoing annotator training is needed to stay up to date with surgical instrument innovation. In robot-assisted surgery however, potentially informative data like timestamps of instrument installation and removal can be programmatically harvested. The ability to use only tool presence labels to localize tools would significan...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/698/grand-challenge_logo.png","https://surgtoolloc.grand-challenge.org/","completed","intermediate","5","","2022-08-29","2022-09-08","2023-11-08 00:42:00","2023-11-15 21:50:20" -"421","curious2022","Brain shift with Intraoperative Ultrasound - Segmentation tasks","Brain shift with intraoperative ultrasound segmentation","Early brain tumor resection can effectively improve the patient’s survival rate. However, resection quality and safety can often be heavily affected by intra-operative brain tissue shift due to factors, such as gravity, drug administration, intracranial pressure change, and tissue removal. Such tissue shift can displace the surgical target and vital structures (e.g., blood vessels) shown in pre-operative images while these displacements may not be directly visible in the surgeon’s field of view. Intra-operative ultrasound (iUS) is a robust and relatively inexpensive technique to track intra-operative tissue shift and surgical tools. Automatic algorithms for brain tissue segmentation in iUS, especially brain tumors and resection cavity can greatly facilitate the robustness and accuracy of brain shift correction through image registration, and allow easy interpretation of the iUS. This has the potential to improve surgical outcomes and patient survival rate. The challenge is an ex...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/699/CuRIOUS_logo.png","https://curious2022.grand-challenge.org/","completed","intermediate","5","","2022-08-15","2022-09-13","2023-11-08 00:42:00","2023-11-15 21:50:06" -"422","vessel-wall-segmentation-2022","Carotid Vessel Wall Segmentation and Atherosclerosis Diagnosis","Carotid vessel wall segmentation and diagnosis","In this challenge, the task is to segment the vessel wall from 3D-VISTA images and diagnose the atherosclerotic lesions with high accuracy and robustness. And then the clinical usable measurements such as wall thickness (difference between the lumen and outer wall contours), lumen area or stenosis percent can be derived from the vessel wall segmentation. In addition, the identification of the lumen and outer wall boundary of the vessel wall is also critical for the diagnosis of lesions. In summary, this challenge focuses on carotid vessel wall segmentation and atherosclerotic lesion diagnosis.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/700/%E5%9B%BE%E7%89%871.png","https://vessel-wall-segmentation-2022.grand-challenge.org/","completed","intermediate","5","","2022-07-08","2022-08-01","2023-11-08 00:42:00","2023-11-16 17:41:55" -"423","crossmoda2022","Cross-Modality Domain Adaptation: Segmentation & Classification","CrossMoDA 2022: unsupervised domain adaptation","The CrossMoDA 2022 challenge is the second edition of the first large and multi-class medical dataset for unsupervised cross-modality Domain Adaptation.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/701/squarelogo_2022.png","https://crossmoda2022.grand-challenge.org/","active","intermediate","5","","2022-05-11","\N","2023-11-08 00:42:00","2023-11-17 23:32:53" -"424","atm22","Multi-site, Multi-Domain Airway Tree Modeling (ATM'22)","Airway segmentation in x-ray CT for pulmonary diseases","Airway segmentation is a crucial step for the analysis of pulmonary diseases including asthma, bronchiectasis, and emphysema. The accurate segmentation based on X-Ray computed tomography (CT) enables the quantitative measurements of airway dimensions and wall thickness, which can reveal the abnormality of patients with chronic obstructive pulmonary disease (COPD). Besides, the extraction of patient-specific airway models from CT images is required for navigatiisted surgery.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/702/logo_xqf7twK.png","https://atm22.grand-challenge.org/","active","intermediate","5","https://doi.org/10.1007/978-3-031-16431-6_48","2022-08-17","\N","2023-11-08 00:42:00","2023-11-21 17:16:40" -"425","ps-fh-aop-2023","FH-PS-AOP challenge","Fetal head and pubic symphysis segmentation","The task of the FH-PS-AOP grand challenge is to automatically segment 700 FH-PSs from transperineal ultrasound images in the devised Set 2 (test set), given the availability of Set 1, consisting of 401 images. Set 2 is held private and therefore not released to the potential participants to prevent algorithm tuning, but instead the algorithms have to be submitted in the form of Docker containers that will be run by organizers on Set 2. The challenge is organized by taking into account the current guidelines for biomedical image analysis competitions, in particular the recommendations of the Biomedical Image Analysis Challenges (BIAS) initiative for transparent challenge reporting.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/703/F2_WDBTbsq.tif","https://ps-fh-aop-2023.grand-challenge.org/","completed","intermediate","5","https://doi.org/10.1007/s11517-022-02747-1","2023-03-27","2023-09-20","2023-11-08 00:42:00","2023-11-16 17:41:56" -"426","shifts","Shifts Challenge 2022","Shifts challenge 2022: distributional shift and uncertainty","The goal of the Shifts Challenge 2022 is to raise awareness among the research community about the problems of distributional shift, robustness, and uncertainty estimation, and to identify new solutions to address them. The competition will consist of two new tracks: White Matter Multiple Sclerosis (MS) lesion segmentation in 3D Magnetic Resonance Imaging (MRI) of the brain and Marine cargo vessel power estimation.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/704/logo_1200.png","https://shifts.grand-challenge.org/","active","intermediate","5","https://arxiv.org/abs/2206.15407","2022-09-15","2024-04-08","2023-11-08 00:42:00","2023-11-17 23:33:07" -"427","megc2022","ACMMM MEGC2022: Facial Micro-Expression Grand Challenge","Facial macro- and micro-expressions spotting","The unseen testing set (MEGC2022-testSet) contains 10 long video, including 5 long videos from SAMM (SAMM Challenge dataset) and 5 clips cropped from different videos in CAS(ME)3. The frame rate for SAMM Challenge dataset is 200fps and the frame rate for CAS(ME)3 is 30 fps. The participants should test on this unseen dataset.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/705/acmmm2022_logo.png","https://megc2022.grand-challenge.org/","active","intermediate","5","https://doi.org/10.1109/fg47880.2020.00029","2022-05-23","\N","2023-11-08 00:42:00","2023-11-16 17:39:17" -"428","midog2022","MItosis DOmain Generalization Challenge 2022","Mitosis domain generalization challenge 2022","Motivation: Mitosis detection is a key component of tumor prognostication for various tumors. Modern deep learning architectures provide detection accuracies for mitosis that are on the level of human experts. Mitosis is known to be relevant for many tumor types, yet, when trained on one tumor / tissue type, the performance will typically drop significantly on another. Scope: Detect mitotic figures (cells undergoing cell division) from histopathology images (object detection). You will be provided with images from 6 different tumor types, 5 out of which are labeled. In total the set consists of 405 cases and includes 9501 mitotic figure annotations in the training set. Evaluation will be done on ten different tumor types with the F1 score as main metric.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/706/midog_compact.png","https://midog2022.grand-challenge.org/","completed","intermediate","5","https://doi.org/10.5281/zenodo.6362337","2022-08-04","2022-08-30","2023-11-08 00:42:00","2023-11-16 17:39:11" -"429","isles22","Ischemic Stroke Lesion Segmentation Challenge","Ischemic stroke lesion segmentation challenge","The goal of this challenge is to evaluate automated methods of stroke lesion segmentation in MR images. Participants are tasked with automatically generating lesion segmentation masks from DWI, ADC and FLAIR MR modalities. The task consist on a single phase of algorithms evaluation. Participants will submit their segmentation model (""algorithm"") via a Docker container which will then be used to generate predictions on a hidden dataset.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/707/Slide1_N1qHO1K.png","https://isles22.grand-challenge.org/","active","intermediate","5","","2022-07-15","2030-12-06","2023-11-08 00:42:00","2023-11-15 21:48:03" -"430","neurips22-cellseg","Cell Segmentation in Multi-modality Microscopy Images","Weakly supervised cell segmentation in high-res microscopy","Cell segmentation is usually the first step for downstream single-cell analysis in microscopy image-based biology and biomedical research. Deep learning has been widely used for image segmentation, but it is hard to collect a large number of labeled cell images to train models because manually annotating cells is extremely time-consuming and costly. Furthermore, datasets used are often limited to one modality and lacking in diversity, leading to poor generalization of trained models. This competition aims to benchmark cell segmentation methods that could be applied to various microscopy images across multiple imaging platforms and tissue types. We frame the cell segmentation problem as a weakly supervised learning task to encourage models that use limited labeled and many unlabeled images for cell segmentation as unlabeled images are relatively easy to obtain in practice.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/708/logo_EOVfhip.PNG","https://neurips22-cellseg.grand-challenge.org/","active","intermediate","5","","2023-08-01","\N","2023-11-08 00:42:00","2023-11-16 17:39:21" -"431","bci","Breast Cancer Immunohistochemical Image Generation Challenge","Breast cancer immunohistochemical image generation","This is an image-to-image translation task that builds a mapping between two domains (HE and IHC). Given an HE image, the algorithm should predict the corresponding IHC image.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/711/logo.png","https://bci.grand-challenge.org/","active","intermediate","5","","2022-08-24","\N","2023-11-08 00:42:00","2023-11-16 17:39:23" -"432","auto-rtp","Fully Automated Radiotherapy Treatment Planning Challenge","Automated radiotherapy treatment planning in prostate cancer","Participants will be provided with simulation CTs for ten prostate cancer patients, together with a treatment intent/prescription (in a machine readable format). The cases will be a mix of prostate only and prostate + nodes. Participants are asked to generate a treatment plan in an as-automated-as-possible way, including contouring and plan generation. No manual intervention on contouring or planning should be performed, but manual steps to transfer data between systems are permitted if required. Freedom is given to participants with respect to the ""treatment machine"" the plan is designed for. However, it is expected that all participants produce a plan that is deliverable in clinically reasonable time frame.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/713/AUTO-RTP_Logo.png","https://auto-rtp.grand-challenge.org/","active","intermediate","5","","2023-06-05","\N","2023-11-08 00:42:00","2023-11-16 17:39:25" -"433","2023paip","PAIP 2023: TC prediction in pancreatic and colon cancer","Tumor cellularity prediction in pancreatic and colon cancer","Tumor cellularity (TC) is used to compute the residual tumor burden in several organs, such as the breast and colon. The TC is measured based on semantic cell segmentation, which accurately classifies and delineates individual cells. However, manual analysis of TC is impractical in clinics because of the large volumes of pathological images and is unreliable owing to inconsistent TC values among pathologists. Essentially, tumor cellularity should be calculated by individual cell counting; however, manual counting is impossible, and human pathologists cannot avoid individual differences in diagnostic performance. Automatic image analysis is the ideal method for solving this problem, and it can efficiently reduce the workload of pathologists.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/716/PAIP2023-640.png","https://2023paip.grand-challenge.org/","active","intermediate","5","","2023-02-15","\N","2023-11-08 00:42:00","2023-11-16 17:39:26" -"434","snemi3d","SNEMI3D: 3D Segmentation of neurites in EM images","IEEE ISBI 2013 challenge: multimodal segmentation","In this challenge, a full stack of electron microscopy (EM) slices will be used to train machine-learning algorithms for the purpose of automatic segmentation of neurites in 3D. This imaging technique visualizes the resulting volumes in a highly anisotropic way, i.e., the x- and y-directions have a high resolution, whereas the z-direction has a low resolution, primarily dependent on the precision of serial cutting. EM produces the images as a projection of the whole section, so some of the neural membranes that are not orthogonal to a cutting plane can appear very blurred. None of these problems led to major difficulties in the manual labeling of each neurite in the image stack by an expert human neuro-anatomist.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/717/logo.png","https://snemi3d.grand-challenge.org/","active","intermediate","5","","2013-01-15","\N","2023-11-08 00:42:00","2023-11-16 17:39:27" -"435","han-seg2023","The Head and Neck Organ-at-Risk CT & MR Segmentation Challenge","Endometrial carcinoma prediction on whole-slide images","Cancer in the region of the head and neck (HaN) is one of the most prominent cancers, for which radiotherapy represents an important treatment modality that aims to deliver a high radiation dose to the targeted cancerous cells while sparing the nearby healthy organs-at-risk (OARs). A precise three-dimensional spatial description, i.e. segmentation, of the target volumes as well as OARs is required for optimal radiation dose distribution calculation, which is primarily performed using computed tomography (CT) images. However, the HaN region contains many OARs that are poorly visible in CT, but better visible in magnetic resonance (MR) images. Although attempts have been made towards the segmentation of OARs from MR images, so far there has been no evaluation of the impact the combined analysis of CT and MR images has on the segmentation of OARs in the HaN region. The Head and Neck Organ-at-Risk Multi-Modal Segmentation Challenge aims to promote the development of new and applicatio...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/718/logo.jpg","https://han-seg2023.grand-challenge.org/","active","intermediate","5","","2023-03-26","2023-12-15","2023-11-08 00:42:00","2023-11-16 17:39:30" -"436","endo-aid","Endometrial Carcinoma Detection in Pipelle biopsies","Non-rigid registration challenge for expansion microscopy","Evaluation platform as reference benchmark for algorithms that can predict endometrial carcinoma on whole-slide images of Pipelle sampled endometrial slides stained in H&E, based on the test data set used in our project.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/719/logo-challenge.png","https://endo-aid.grand-challenge.org/","active","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:33:27" -"437","rnr-exm","Robust Non-rigid Registration Challenge for Expansion Microscopy","Xray projectomic reconstruction with skeleton segmentation","Despite the wide adoption of ExM, there are few public benchmarks to evaluate the registration pipeline, which limits the development of robust methods for real-world deployment. To address this issue, we have launched RnR-ExM, a challenge that releases 24 pairs of 3D image volumes from three different species. Participants are asked to align these pairs and submit dense deformation fields for assessment. Half of the volume pairs (the validation and test set) have annotated cell structures (nuclei, blood vessels) as registration landmarks.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/720/RnR-ExM_Logo.png","https://rnr-exm.grand-challenge.org/","active","intermediate","5","","2023-02-17","2028-03-16","2023-11-08 00:42:00","2023-11-16 17:39:32" -"438","xpress","Xray Projectomic Reconstruction Extracting Segment with Skeleton","Automated lesion segmentation in PET/CT - domain generalization","In this task, we provide volumetric XNH images of cortical white matter axons from the mouse brain at 100 nm per voxel isotropic resolution. Additionally, we provide ground truth annotations for axon trajectories. Manual voxel-wise annotation of ground truth is a time-consuming bottleneck for training segmentation networks. On the other hand, skeleton-based ground truth is much faster to annotate, and sufficient to determine connectivity. Therefore, we encourage participants to develop methods to leverage skeleton-based training. To this end, we provide two types of training (validation) sets: a small volume of voxel-wise annotations and a larger volume with skeleton-based annotations. The participants will have the flexibility to use either or both of the provided annotations to train their models, and are challenged to submit an accurate voxel-wise prediction on the test volume. Entries will be evaluated on how accurately the submitted segmentations agree with the ground-truth s...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/721/XPRESS_logo_sq2-01.png","https://xpress.grand-challenge.org/","active","intermediate","5","","2023-02-06","\N","2023-11-08 00:42:00","2023-11-16 17:39:34" -"439","autopet-ii","autoPET-II","Automated lesion segmentation in PET/CT - domain generalization challenge","Positron Emission Tomography / Computed Tomography (PET/CT) is an integral part of the diagnostic workup for various malignant solid tumor entities. Due to its wide applicability, Fluorodeoxyglucose (FDG) is the most widely used PET tracer in an oncological setting reflecting glucose consumption of tissues, e.g. typically increased glucose consumption of tumor lesions. As part of the clinical routine analysis, PET/CT is mostly analyzed in a qualitative way by experienced medical imaging experts. Additional quantitative evaluation of PET information would potentially allow for more precise and individualized diagnostic decisions. A crucial initial processing step for quantitative PET/CT analysis is segmentation of tumor lesions enabling accurate feature extraction, tumor characterization, oncologic staging and image-based therapy response assessment. Manual lesion segmentation is however associated with enormous effort and cost and is thus infeasible in clinical routine. Automatio...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/722/autopet-5.png","https://autopet-ii.grand-challenge.org/","completed","intermediate","5","","2023-02-28","2023-09-24","2023-11-08 00:42:00","2023-11-15 21:45:49" -"440","toothfairy","ToothFairy: Cone-Beam Computed Tomography Segmentation Challenge","Toothfairy challenge: inferior alveolar canal segmentation","This is the first edition of the ToothFairy challenge organized by the University of Modena and Reggio Emilia with the collaboration of Raudboud University. This challenge aims at pushing the development of deep learning frameworks to segment the Inferior Alveolar Canal (IAC) by incrementally extending the amount of publicly available 3D-annotated Cone Beam Computed Tomography (CBCT) scans. CBCT modality is becoming increasingly important for treatment planning and diagnosis in implant dentistry and maxillofacial surgery. The three-dimensional information acquired with CBCT can be crucial to plan a vast number of surgical interventions with the aim of preserving noble anatomical structures such as the Inferior Alveolar Canal (IAC), which contains the homonymous nerve (Inferior Alveolar Nerve, IAN). Deep learning models can support medical personnel in surgical planning procedures by providing a voxel-level segmentation of the IAN automatically extracted from CBCT scans.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/723/logo.jpg","https://toothfairy.grand-challenge.org/","active","intermediate","5","","2023-06-30","\N","2023-11-08 00:42:00","2023-11-17 23:33:47" -"441","spider","SPIDER","Lumbar SPIDER challenge: MRI segmentation of spinal structures","The Lumbar SPIDER Challenge focuses on the segmentation of three anatomical structures in lumbar spine MRI: vertebrae, intervertebral discs (IVDs), and spinal canal. The segmentation task requires participants to produce separate masks for each vertebra, IVD, and the spinal canal in the lumbar spine MRI volume. The numbering of the vertebrae and IVDs is not specific and may vary across different cases.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/724/SPIDER_logo_square_jsl2NDu.png","https://spider.grand-challenge.org/","active","intermediate","5","","2023-07-26","2024-04-30","2023-11-08 00:42:00","2023-11-17 23:34:08" -"442","lnq2023","LNQ2023","3D lymph node segmentation for comprehensive disease evaluation","Accurate lymph node size estimation is critical for staging cancer patients, initial therapeutic management, and in longitudinal scans, assessing response to therapy. Current standard practice for quantifying lymph node size is based on a variety of criteria that use unidirectional or bidirectional measurements on just one or a few nodes, typically on just one axial slice. But humans have hundreds of lymph nodes, any number of which may be enlarged to various degrees due to disease or immune response. While a normal lymph node may be approximately 5mm in diameter, a diseased lymph node may be several cm in diameter. The mediastinum, the anatomical area between the lungs and around the heart, may contain ten or more lymph nodes, often with three or more enlarged greater than 1cm. Accurate segmentation in 3D would provide more information to evaluate lymph node disease.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/725/LNQ-square.png","https://lnq2023.grand-challenge.org/","completed","intermediate","5","","2023-05-01","2023-09-30","2023-11-08 00:42:00","2023-11-17 23:34:13" -"443","arcade","ARCADE-MICCAI2023","ARCADE 2023: automatic region-based coronary artery disease diagnostics","Coronary artery disease (CAD) is a condition that affects blood supply of heart, due to buildup of atherosclerotic plaque in the coronary arteries. CAD is one of the leading death causes around the world. The most common diagnosis procedure for CAD is coronary angiography, which uses contrast material and X-rays for observation of lesions in arteries, this type of procedure showing blood flow in coronary arteries in real time what allows precise detection of stenosis and control of intraventricular interventions and stent insertions. Coronary angiography is useful diagnostic method for planning necessary revascularization procedures based on calculated occlusion and affected segment of coronary arteries. The development of automated analytical tool for lesion detection and localization is a promising strategy for increasing effectiveness of detection and treatment strategies for CAD.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/726/aRCADE__1.jpg","https://arcade.grand-challenge.org/","completed","intermediate","5","","2023-06-07","2023-09-20","2023-11-08 00:42:00","2023-11-15 21:45:02" -"444","ultrasoundenhance2023","Ultrasound Image Enhancement challenge 2023","Ultrasound image enhancement challenge 2023","Ultrasound imaging is commonly used for aiding disease diagnosis and treatment, with advantages in noninvasive. Lately, medical ultrasound shows prospects revolving from expensive big-size machines in hospitals to economical hand-held devices in wider use. The barrier is that ultrasound examination with a handheld device has the drawback of low imaging quality due to hardware limitations. Toward this, ultrasound image enhancement provides a potential low-cost solution. Restoring high-quality images from low-quality ones using computer algorithms would exempt requirements for hardware improvements and promote ultrasound device revolutions and wider applications. We propose to hold the challenge of enhancement for ultrasound images in conjunction with MICCAI 2023. We will provide various ultrasound data of five organs, including the thyroid, carotid artery, liver, breast, and kidney. The challenging task is reconstructing high-quality ultrasound images from low-quality ones. A tota...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/727/logo.png","https://ultrasoundenhance2023.grand-challenge.org/","completed","intermediate","5","","2023-07-10","2023-08-31","2023-11-08 00:42:00","2023-11-15 21:44:45" -"445","multicenteraorta","SEG.A. - Segmentation of the Aorta","Aortic vessel tree segmentation challenge in CT images","Segmentation, modeling and visualization of the arterial tree are still a challenge in medical image analysis. The main track of this challenge deals with the fully automatic segmentation of the aortic vessel tree in computed tomography images. Optionally, teams can submit tailored solutions for meshing and visualization of the vessel tree.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/729/logo_final_miccai.jpg","https://multicenteraorta.grand-challenge.org/","completed","intermediate","5","https://arxiv.org/abs/2108.02998","2023-06-15","2023-08-15","2023-11-08 00:42:00","2023-11-17 23:34:24" -"446","sppin","Surgical Planning in Pediatric Neuroblastoma","Pediatric neuroblastoma surgical planning challenge","Neuroblastoma: Neuroblastoma is one of the most common cancers in children, accounting for 15% of pediatric cancer related deaths. This tumor originates from the symphatic nervous system, and is often located in the abdomen. Treatment of neuroblastoma includes surgical resection of the tumor, but complete resection of the tumor is often challenging. Surgical planning in Neuroblastoma: Surgical procedures can be complicated due to the neuroblastoma often being in proximity or even encasing organs and vessels in the affected area. These structures can include abdominal organs such as kidneys, liver, pancreas and spleen or big abdominal vessels such as the aorta and renal veins. During surgical planning it is essential to have a clear understanding of the neuroblastoma in relation to the relevant anatomy. Currently, magnetic resonance imaging (MRI) is used as pre-operative imaging. Studying 3D models of the tumor and relevant structures guides surgeons in the pre-operative understan...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/730/SPINN_Logo_SB_2023_03_11-09_TnwZJgK.png","https://sppin.grand-challenge.org/","completed","intermediate","5","","2023-08-10","2023-09-01","2023-11-08 00:42:00","2023-11-11 01:52:06" -"447","medfm2023","Foundation Model Prompting for Medical Image Classification","Model adaptation for medical image classification challenge","In the past few years, deep learning foundation models have been trendy, especially in computer vision and natural language processing. As a result, many milestone works have been proposed, such as Vision Transformers (ViT), Generative Pretrained Transformer (GPT), and Contrastive Language-Image Pretraining (CLIP). They aim to solve many downstream tasks by utilizing the robust representation learning and generalization abilities of foundation models.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/731/logo640.png","https://medfm2023.grand-challenge.org/","active","intermediate","5","","2023-07-14","2033-10-15","2023-11-08 00:42:00","2023-11-16 17:39:48" -"448","dentex","DENTEX - MICCAI23","Dental enumeration and diagnosis on panoramic x-rays","Panoramic X-rays are widely used in dental practice to provide a comprehensive view of the oral cavity and aid in treatment planning for various dental conditions. However, interpreting these images can be a time-consuming process that can distract clinicians from essential clinical activities. Moreover, misdiagnosis is a significant concern, as general practitioners may lack specialized training in radiology, and communication errors can occur due to work exhaustion.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/732/logo_diseased.png","https://dentex.grand-challenge.org/","completed","intermediate","5","https://arxiv.org/abs/2303.06500","2023-04-30","2023-09-01","2023-11-08 00:42:00","2023-11-16 17:39:45" -"449","segrap2023","SegRap 2023","Multi-modal CT image segmentation challenge with 45 OARs","Radiotherapy is one of the most important cancer treatments for killing cancer cells with external beam radiation. Treatment planning is vital for radiotherapy, which sets up the radiation dose distribution for tumors and ordinary organs. The goal of planning is to ensure the cancer cells receive enough radiation and to prevent normal cells in organs-at-risk (OARs) from being damaged too much. For instance, optical nerves and chiasma in the head cannot receive too much radiation. Otherwise, the patient risks losing his/her vision. Gross Target Volume (GTV) is the position and extent of gross tumor imaged by CT scans, i.e., what can be seen. A critical step in radiation treatment planning is to delineate the boundaries of GTV and tens of OARs. However, manual delineation slice-by-slice in CT scans is tedious and time-consuming for radiation oncologists. Automatic delineation of GTV and OARs would substantially reduce the treatment planning time and therefore improve the efficiency ...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/734/segrap-logo_cLCSrpZ.png","https://segrap2023.grand-challenge.org/","completed","intermediate","5","","2023-07-09","2023-09-13","2023-11-08 00:42:00","2023-11-16 17:39:47" -"450","ldctiqac2023","Low-dose Computed Tomography Perceptual Image Quality Assessment","Low-dose CT perceptual image quality assessment challenge","Image quality assessment (IQA) is extremely important in computed tomography (CT) imaging, since it facilitates the optimization of radiation dose and the development of novel algorithms in medical imaging, such as restoration. In addition, since an excessive dose of radiation can cause harmful effects in patients, generating high-quality images from low-dose images is a popular topic in the medical domain. However, even though peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) are the most widely used evaluation metrics for these algorithms, their correlation with radiologists’ opinion of the image quality has been proven to be insufficient in previous studies, since they calculate the image score based on numeric pixel values (1-3). In addition, the need for pristine reference images to calculate these metrics makes them ineffective in real clinical environments, considering that pristine, high-quality images are often impossible to obtain due to th...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/735/IQA_logo_3io1BcW.png","https://ldctiqac2023.grand-challenge.org/","completed","intermediate","5","","2023-04-19","2023-07-28","2023-11-08 00:42:00","2023-11-16 17:39:58" -"451","cl-detection2023","CL-Detection 2023","Cephalometric landmark detection in lateral x-ray images","We invite you to participate in the CL-Detection 2023 cephalometric landmark detection challenge, which is held with 2023 MICCAI conference. Prof Wang is also hosting another challenge in MICCAI 2023. If you are seeking more publication opportunities, feel free to check the challenge website (Automated prediction of treatment effectiveness in ovarian cancer using histopathological images)","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/737/logo.png","https://cl-detection2023.grand-challenge.org/","completed","intermediate","5","https://doi.org/10.1109/tmi.2015.2412951","2023-05-31","2023-08-15","2023-11-08 00:42:00","2023-11-16 17:39:52" -"452","surgtoolloc23","Endoscopic surgical tool localization using tool presence labels","Endoscopic surgical tool localization challenge","The ability to automatically detect and track surgical instruments in endoscopic video will enable many transformational interventions. Assessing surgical performance and efficiency, identifying skilled tool use and choreography, and planning operational and logistical aspects of OR resources are just some of the applications that would benefit. The annotations needed to train machine learning models to robustly identify and localize surgical tools, however, are difficult to obtain. Annotating bounding boxes frame-by-frame in video is tedious and time consuming, yet a wide variety of surgical tools and surgeries must be captured for robust training. Moreover, ongoing annotator training is needed to stay up to date with surgical instrument innovation. In robot-assisted surgery, potentially informative data like timestamps of instrument installation and removal, can be programmatically harvested. The ability to use only tool presence labels to localize tools would significantly redu...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/738/grand-challenge_logo_2023.png","https://surgtoolloc23.grand-challenge.org/","completed","intermediate","5","","2023-06-29","2023-09-20","2023-11-08 00:42:00","2023-11-16 17:39:53" -"453","ocelot2023","OCELOT 2023: Cell Detection from Cell-Tissue Interaction","Cell detection from cell-tissue interaction","Cell detection in histology images is one of the most important tasks in computational pathology. Recently, the OCELOT dataset was released in [1] which provides overlapping cell and tissue annotations on images acquired from multiple organs stained with H&E. [1] showed that understanding the relationship between the surrounding tissue structures and individual cells can boost cell detection performance.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/739/gc_loco_XeBK92j.png","https://ocelot2023.grand-challenge.org/","completed","intermediate","5","https://arxiv.org/abs/2303.13110","2023-06-04","2023-08-04","2023-11-08 00:42:00","2023-11-16 17:39:56" -"454","thompson-challenge","The Trauma THOMPSON Challenge","Trauma thompson challenge: trauma image analysis","The primary goal of The Trauma THOMPSON Challenge is to find the best algorithms for automatic action recognition and prediction using computer vision from first-person view in the medical domain (refer to egocentric datasets of medical procedures). We offer the first egocentric view dataset of life-saving intervention (LSI) procedures with detailed annotations by medical professionals. We have collected over 200 procedure videos with environment, simulator, and type variability. Based on this dataset, the challenge we propose involves multiple tasks to encourage participants across the globe to design impactful algorithms with applications to medicine. The envisioned algorithms include action recognition, action anticipation, procedure recognition, and visual question answering (VQA).","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/742/ttlog_black_-_Copy.png","https://thompson-challenge.grand-challenge.org/","active","intermediate","5","","2023-09-01","\N","2023-11-08 00:42:00","2023-11-16 17:39:57" -"455","bonbid-hie2023","Hypoxic Ischemic Encephalopathy Lesion Segmentation Challenge","Hypoxic ischemic encephalopathy lesion segmentation","Hypoxic ischemic encephalopathy (HIE) is a brain injury that occurs in 1 ~ 5/1000 term-born neonates. HIE affects around 200,000 term-born neonates every year worldwide, costing about $2 billion/year in the US alone, let alone family burdens. Although therapeutic hypothermia can reduce mortality and morbidity, yet around 60% of patients still die or develop neurocognitive deficits by 2 years of age. HIE lesion segmentation is a crucial step in clinical care of HIE. It will lead to a more accurate estimation of prognosis, a better understanding of neurological symptoms, and a timely prediction of response to therapy.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/743/hie.png","https://bonbid-hie2023.grand-challenge.org/","completed","intermediate","5","","2023-07-01","2023-09-21","2023-11-08 00:42:00","2023-11-16 17:40:00" -"456","panorama","PANORAMA","AI and radiologists at pancreatic cancer diagnosis","The PANORAMA (Pancreatic cancer diagnosis: Radiologists meet AI) study is a new prospectively designed multi-center study with over 1500 cases, established in conjunction with an international, multi-disciplinary scientific advisory board (11 experts in pancreas radiology, AI and pancreatic cancer survivor representative) ⁠—to unify and standardize present-day guidelines and to ensure meaningful validation of pancreas-AI towards clinical translation (Reinke et al., 2022).","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/746/panorama_logo_square.png","https://panorama.grand-challenge.org/","completed","intermediate","5","","\N","\N","2023-11-08 00:42:00","2023-11-16 17:40:02" -"457","cameo-3d","CAMEO-3D","Protein structure prediction quality assessment","Cameo Continuously Applies Quality Assessment Criteria Established By The Protein Structure Prediction Community. Since The Accuracy Requirements For Different Scientific Applications Vary, There Is No ""One Fits All"" Score. Cameo Therefore Offers A Variety Of Scores - Assessing Different Aspects Of A Prediction (Coverage, Local Accuracy, Completeness, Etc.) To Reflect These Requirements.","","https://www.cameo3d.org/modeling/3-months/","active","intermediate","17","","2023-11-04","\N","2023-11-11 01:29:20","2023-11-16 22:41:57" -"458","cameo-qe-model-quality-estimation","CAMEO-QE: Model Quality Estimation","Protein structure prediction quality assessment","Cameo Continuously Applies Quality Assessment Criteria Established By The Protein Structure Prediction Community. Since The Accuracy Requirements For Different Scientific Applications Vary, There Is No ""One Fits All"" Score. Cameo Therefore Offers A Variety Of Scores - Assessing Different Aspects Of A Prediction (Coverage, Local Accuracy, Completeness, Etc.) To Reflect These Requirements.","","https://www.cameo3d.org/quality-estimation/","active","intermediate","17","","2023-11-04","\N","2023-11-11 01:29:20","2023-11-16 22:41:57" -"459","cameo-3d-modeling-of-structures-and-complexes-beta","CAMEO-3D: Modeling of Structures & Complexes - BETA","Protein structure prediction quality assessment","Cameo Continuously Applies Quality Assessment Criteria Established By The Protein Structure Prediction Community. Since The Accuracy Requirements For Different Scientific Applications Vary, There Is No ""One Fits All"" Score. Cameo Therefore Offers A Variety Of Scores - Assessing Different Aspects Of A Prediction (Coverage, Local Accuracy, Completeness, Etc.) To Reflect These Requirements.","","https://beta.cameo3d.org/complete-modeling/","active","intermediate","17","","2023-11-04","\N","2023-11-11 01:29:20","2023-11-16 22:41:58" -"460","pegs-dream-challenge","PEGS DREAM Challenge","","","","https://www.synapse.org/pegs","upcoming","intermediate","1","","\N","\N","2023-11-13 22:48:02","2023-11-16 16:20:18" -"461","fda-data-centric-challenge","FDA Data-Centric Challenge","","","","https://www.synapse.org/fda_data_centric","upcoming","intermediate","1","","\N","\N","2023-11-13 22:49:41","2023-11-16 16:18:38" -"462","ai-institute-for-dynamic-systems","AI Institute for Dynamic Systems","","","","https://www.synapse.org/#!Synapse:syn52052735","upcoming","intermediate","1","","\N","\N","2023-11-13 22:51:53","2023-11-17 0:13:33" -"463","competition-nih-alzheimers-adrd-1","PREPARE Phase 1 - Find IT!","Help NIH break new ground in early Alzheimer's prediction and related dementias","The goal of the PREPARE Challenge (Pioneering Research for Early Prediction of Alzheimer's and Related Dementias EUREKA Challenge) is to inform novel approaches to early detection that might ultimately lead to more accurate tests, tools, and methodologies for clinical and research purposes. Advances in artificial intelligence (AI), machine learning (ML), and computing ecosystems increase possibilities of intelligent data collection and analysis, including better algorithms and methods that could be leveraged for the prediction of biological, psychological (cognitive), socio-behavioral, functional, and clinical changes related to AD/ADRD. This first phase, Find IT!: Data for Early Prediction, is focused on finding, curating, or contributing data to create representative and open datasets that can be used for the early prediction of AD/ADRD.","","https://www.drivendata.org/competitions/253/competition-nih-alzheimers-adrd-1/","active","intermediate","18","","2023-09-01","2024-01-31","2023-11-16 21:57:03","2023-12-06 7:15:18" -"464","prepare-phase-2-build-it","PREPARE Phase 2 - Build IT!","Help NIH break new ground in early Alzheimer's prediction and related dementias","The goal of the PREPARE Challenge (Pioneering Research for Early Prediction of Alzheimer's and Related Dementias EUREKA Challenge) is to inform novel approaches to early detection that might ultimately lead to more accurate tests, tools, and methodologies for clinical and research purposes. Advances in artificial intelligence (AI), machine learning (ML), and computing ecosystems increase possibilities of intelligent data collection and analysis, including better algorithms and methods that could be leveraged for the prediction of biological, psychological (cognitive), socio-behavioral, functional, and clinical changes related to AD/ADRD. This second phase, Build IT!: Algorithms and Approaches, is focused on advancing algorithms and analytic approaches for early prediction of AD/ADRD, with an emphasis on explainability of predictions.","","","upcoming","intermediate","18","","2024-09-01","\N","2023-11-17 00:09:25","2023-12-06 7:18:18" -"465","prepare-phase-3-put-it-all-together","PREPARE Phase 3 - Put IT All Together!","Help NIH break new ground in early Alzheimer's prediction and related dementias","The goal of the PREPARE Challenge (Pioneering Research for Early Prediction of Alzheimer's and Related Dementias EUREKA Challenge) is to inform novel approaches to early detection that might ultimately lead to more accurate tests, tools, and methodologies for clinical and research purposes. Advances in artificial intelligence (AI), machine learning (ML), and computing ecosystems increase possibilities of intelligent data collection and analysis, including better algorithms and methods that could be leveraged for the prediction of biological, psychological (cognitive), socio-behavioral, functional, and clinical changes related to AD/ADRD. This third phase, Put IT All Together!: Proof of Principle Demonstration, is for the top solvers from Phase 2 demonstrate algorithmic approaches on diverse datasets and share their results at an innovation event.","","","upcoming","intermediate","18","","2025-03-01","\N","2023-11-17 00:09:26","2023-12-06 7:18:08" -"466","cdc-fall-narratives","Unsupervised Wisdom: Explore Medical Narratives on Older Adult Falls","Extract insights about older adult falls from emergency department narratives","Falls among adults 65 and older is the leading cause of injury-related deaths. Falls can also result in serious injuries to the head and/or broken bones. Some risk factors associated with falls can be reduced through appropriate interventions like treating vision problems, exercising for strength and balance, and removing tripping hazards in your home. Medical record narratives are a rich yet under-explored source of potential insights about how, when, and why people fall. However, narrative data sources can be difficult to work with, often requiring carefully designed, time-intensive manual coding procedures. Modern machine learning approaches to working with narrative data have the potential to effectively extract insights about older adult falls from narrative medical record data at scale. The goal in this challenge is to identify effective methods of using unsupervised machine learning to extract insights about older adult falls from emergency department narratives. Insights...","https://drivendata-public-assets.s3.amazonaws.com/cdc-banner-hands.png","https://www.drivendata.org/competitions/217/cdc-fall-narratives/","completed","intermediate","18","","\N","2023-10-06","2023-12-06 06:56:06","2023-12-06 7:21:14" -"467","visiomel-melanoma","VisioMel Challenge: Predicting Melanoma Relapse","Use digitized microscopic slides to predict the likelihood of melanoma relapse","Melanoma is a cancer of the skin which develops from cells responsible for skin pigmentation. In 2020, over 325,000 people were diagnosed with skin melanoma, with 57,000 deaths in the same year.1 Melanomas represent 10% of all skin cancers and are the most dangerous due to high likelihood of metastasizing (spreading). Patients are initially diagnosed with melanoma after a pathologist examines a portion of the cancerous tissue under a microscope. At this stage, the pathologist assesses the risk of relapse—a return of cancerous cells after the melanoma has been treated—based on information such as the thickness of the tumor and the presence of an ulceration. Combined with factors such as age, sex, and medical history of the patient, these microscopic observations can help a dermatologist assess the severity of the disease and determine appropriate surgical and medical treatment. Preventative treatments can be administered to patients with high likelihood for relapse. However, these...","https://drivendata-public-assets.s3.amazonaws.com/visiomel_banner_img.jpeg","https://www.drivendata.org/competitions/1481/visiomel-melanoma/","completed","intermediate","18","","\N","2023-05-11","2023-12-06 07:35:00","2023-12-06 7:52:55" -"468","competition-cervical-biopsy","TissueNet: Detect Lesions in Cervical Biopsies","Detect the most severe epithelial lesions of the uterine cervix","A biopsy is a sample of tissue examined at a microscopic level to diagnose cancer or signs of pre-cancer. While most diagnoses are still made with photonic microscopes, digital pathology has developed considerably over the past decade as it has become possible to digitize slides into ""virtual slides"" or ""whole slide images"" (WSIs). These heavy image files contain all the information required to diagnose lesions as malignant or benign. Making this diagnosis is no easy task. It requires specialized training and careful examination of microscopic tissue. Approaches in machine learning are already able to help analyze WSIs by measuring or counting areas of the image under a pathologist's supervision. In addition, computer vision has shown some potential to classify tumor subtypes, and in time may offer a powerful tool to aid pathologists in making the most accurate diagnoses. This challenge focuses on epithelial lesions of the uterine cervix, and features a unique collection of thou...","https://s3.amazonaws.com/drivendata-public-assets/sfp_comp_image.jpg","https://www.drivendata.org/competitions/67/competition-cervical-biopsy/","completed","intermediate","18","","\N","2020-10-29","2023-12-06 07:52:34","2023-12-06 7:58:21" -"469","clog-loss-alzheimers-research","Clog Loss: Advance Alzheimer’s Research with Stall Catchers","Automatically classify which blood vessels are flowing and which are stalled","5.8 million Americans live with Alzheimer’s dementia, including 10% of all seniors 65 and older. Scientists at Cornell have discovered links between “stalls,” or clogged blood vessels in the brain, and Alzheimer’s. Stalls can reduce overall blood flow in the brain by 30%. The ability to prevent or remove stalls may transform how Alzheimer’s disease is treated. Stall Catchers is a citizen science project that crowdsources the analysis of Alzheimer’s disease research data provided by Cornell University’s Department of Biomedical Engineering. It resolves a pressing analytic bottleneck: for each hour of data collection it would take an entire week to analyze the results in the lab, which means an entire experimental dataset would take 6-12 months to analyze. Today, the Stall Catchers players are collectively analyzing data 5x faster than the lab while exceeding data quality requirements. The research team has realized there are aspects of this task that are best suited to uniquely h...","","https://www.drivendata.org/competitions/65/clog-loss-alzheimers-research/","completed","intermediate","18","","\N","2020-08-03","2023-12-06 08:04:52","2023-12-06 8:07:15" -"470","flu-shot-learning","Flu Shot Learning: Predict H1N1 and Seasonal Flu Vaccines","Predict whether people got H1N1 and flu vaccines using information they shared","In this challenge, we will take a look at vaccination, a key public health measure used to fight infectious diseases. Vaccines provide immunization for individuals, and enough immunization in a community can further reduce the spread of diseases through ""herd immunity."" As of the launch of this competition, vaccines for the COVID-19 virus are still under development and not yet available. The competition will instead revisit the public health response to a different recent major respiratory disease pandemic. Beginning in spring 2009, a pandemic caused by the H1N1 influenza virus, colloquially named ""swine flu,"" swept across the world. Researchers estimate that in the first year, it was responsible for between 151,000 to 575,000 deaths globally. A vaccine for the H1N1 flu virus became publicly available in October 2009. In late 2009 and early 2010, the United States conducted the National 2009 H1N1 Flu Survey. This phone survey asked respondents whether they had received the H1N1...","https://drivendata-public-assets.s3.amazonaws.com/flu-vaccine.jpg","https://www.drivendata.org/competitions/66/flu-shot-learning/","active","intermediate","18","","\N","2024-07-30","2023-12-06 08:10:49","2023-12-06 8:14:49" -"471","machine-learning-with-a-heart","Warm Up: Machine Learning with a Heart","Predict the presence or absence of heart disease in patients","We've all got to start somewhere. This is one of the smallest datasets on DrivenData. That makes it a great place to dive into the world of data science competitions. Get your heart thumping and try your hand at predicting heart disease.","","https://www.drivendata.org/competitions/54/machine-learning-with-a-heart/","completed","intermediate","18","","\N","2019-10-30","2023-12-06 08:19:47","2023-12-06 8:21:53" -"472","dengai-predicting-disease-spread","DengAI: Predicting Disease Spread","Predict the number of dengue fever cases reported each week in 2 regions","Using environmental data collected by various U.S. Federal Government agencies—from the Centers for Disease Control and Prevention to the National Oceanic and Atmospheric Administration in the U.S. Department of Commerce—can you predict the number of dengue fever cases reported each week in San Juan, Puerto Rico and Iquitos, Peru? This is an intermediate-level practice competition. Your task is to predict the number of dengue cases each week (in each location) based on environmental variables describing changes in temperature, precipitation, vegetation, and more. An understanding of the relationship between climate and dengue dynamics can improve research initiatives and resource allocation to help fight life-threatening pandemics.","","https://www.drivendata.org/competitions/44/dengai-predicting-disease-spread/","active","intermediate","18","","\N","2024-10-05","2023-12-06 08:28:42","2023-12-06 8:30:39" -"473","senior-data-science-safe-aging-with-sphere","Senior Data Science: Safe Aging with SPHERE","Predict actual activity from sensor data in seniors","This challenge is part of a large research project which centers around using sensors and algorithms to help older people live safely at home while maintaining their privacy and independence. Using passive, automated monitoring, the ultimate goal is to look out for a person's well-being without being burdensome or intrusive. To gather data, researchers in the SPHERE Inter-disciplinary Research Collaboration (IRC) equipped volunteers with accelerometers similar to those found in cell phones or fitness wearables, and then had the subjects go about normal activities of daily living in a home-like environment that was also equipped with motion detectors. After gathering a robust set of sensor data, they had multiple annotators use camera footage to establish the ground truth, labeling chunks of sensor data as one of twenty specifically chosen activities (e.g. walk, sit, stand-to-bend, ascend stairs, descend stairs, etc). Your challenge: help push forward the state of the art by pred...","","https://www.drivendata.org/competitions/42/senior-data-science-safe-aging-with-sphere/","completed","intermediate","18","","\N","2016-07-31","2023-12-06 08:35:31","2023-12-06 8:44:36" -"474","countable-care-modeling-womens-health-care-decisions","Countable Care: Modeling Women's Health Care Decisions","Predict what drives women’s health care decisions in America","Recent literature suggests that the demand for women’s health care will grow over 6% by 2020. Given how rapidly the health landscape has been changing over the last 15 years, it’s increasingly important that we understand how these changes affect what care people receive, where they go for it, and how they pay. Through the National Survey of Family Growth, the CDC provides one of the few nationally representative datasets that dives deep into the questions that women face when thinking about their health. Can you predict what drives women’s health care decisions in America?","","https://www.drivendata.org/competitions/6/countable-care-modeling-womens-health-care-decisions/","completed","intermediate","18","","\N","2015-04-14","2023-12-06 08:45:12","2023-12-06 8:46:00" -"475","warm-up-predict-blood-donations","Warm Up: Predict Blood Donations","Predict whether a donor will return to donate blood given their donation history","We've all got to start somewhere. This is the smallest, least complex dataset on DrivenData. That makes it a great place to dive into the world of data science competitions. Get your blood pumping and try your hand at predicting donations.","","https://www.drivendata.org/competitions/2/warm-up-predict-blood-donations/","completed","intermediate","18","","\N","2019-03-21","2023-12-06 08:52:21","2023-12-06 8:53:13" -"476","genetic-engineering-attribution","Genetic Engineering Attribution Challenge","Identify the lab-of-origin for genetically engineered DNA","our goal is to create an algorithm that identifies the most likely lab-of-origin for genetically engineered DNA. Applications for genetic engineering are rapidly diversifying. Researchers across the world are using powerful new techniques in synthetic biology to solve some of the world’s most pressing challenges in medicine, agriculture, manufacturing and more. At the same time, increasingly powerful genetically engineered systems could yield unintended consequences for people, food crops, livestock, and industry. These incredible advances in capability demand tools that support accountable innovation. Genetic engineering attribution is the process of identifying the source of a genetically engineered piece of DNA. This ability ensures that scientists who have spent countless hours developing breakthrough technology get their due credit, intellectual property is protected, and responsible innovation is promoted. By connecting a genetically engineered system with its designers, s...","https://s3.amazonaws.com/drivendata-public-assets/al-green-homepage.jpg","https://www.drivendata.org/competitions/63/genetic-engineering-attribution/","completed","intermediate","18","","\N","2020-10-19","2023-12-06 08:54:24","2023-12-06 8:56:29" +"id","slug","name","headline","description","avatar_url","website_url","status","platform","doi","start_date","end_date","created_at","updated_at" +"1","network-topology-and-parameter-inference","Network Topology and Parameter Inference","Optimize methods to estimate biology model parameters","Participants are asked to develop and/or apply optimization methods, including the selection of the most informative experiments, to accurately estimate parameters and predict outcomes of perturbations in Systems Biology models.","","https://www.synapse.org/#!Synapse:syn2821735","completed","1","","2012-06-01","2012-10-01","2023-11-15 22:40:15","2023-11-16 18:31:42" +"2","breast-cancer-prognosis","Breast Cancer Prognosis","Predict breast cancer survival from clinical and genomic data","The goal of the breast cancer prognosis Challenge is to assess the accuracy of computational models designed to predict breast cancer survival, based on clinical information about the patient's tumor as well as genome-wide molecular profiling data including gene expression and copy number profiles.","","https://www.synapse.org/#!Synapse:syn2813426","completed","1","","2012-07-12","2012-10-15","2023-11-14 20:36:32","2023-11-14 20:17:33" +"3","phil-bowen-als-prediction-prize4life","Phil Bowen ALS Prediction Prize4Life","Seeking treatment to halt ALS's fatal loss of motor function","Amyotrophic Lateral Sclerosis (ALS), or Lou Gehrig's disease, is a fatal neurological condition causing the death of nerve cells in the brain and spinal cord, resulting in a progressive loss of motor function while cognitive functions persist. Typically emerging around age 50, it affects about five in 100,000 people worldwide, with familial hereditary forms as the only known risk factors (5-10% of cases). There is currently no cure for ALS. The FDA-approved drug Riluzole extends life by a few months. ALS patients, on average, have a life expectancy of 2-5 years, with 10% experiencing slower disease progression. Astrophysicist Stephen Hawking, living with ALS for 49 years, is an exceptional case. The DREAM-Phil Bowen ALS Prediction Prize4Life, or ""ALS Prediction Prize,"" utilizes the PRO-ACT database with clinical data from over 7,500 ALS patients. This collaboration with DREAM aims to expedite ALS treatment discovery. Prize4Life, a non-profit, collaborates with NEALS and ALS Ther...","","https://www.synapse.org/#!Synapse:syn2826267","completed","1","","2012-06-01","2012-10-01","2023-11-01 22:09:02","2023-11-13 17:16:16" +"4","drug-sensitivity-and-drug-synergy-prediction","Drug Sensitivity and Drug Synergy Prediction","Predicting drug sensitivity in human cell lines","Development of new cancer therapeutics currently requires a long and protracted process of experimentation and testing. Human cancer cell lines represent a good model to help identify associations between molecular subtypes, pathways, and drug response. In recent years there have been several efforts to generate genomic profiles of collections of cell lines and to determine their response to panels of candidate therapeutic compounds. These data provide the basis for the development of in silico models of sensitivity based either on the unperturbed genetic potential of a cancer cell, or by using perturbation data to incorporate knowledge of actual cell response. Making predictions from either of these data profiles will be beneficial in identifying single and combinatorial chemotherapeutic response in patients. To that end, the present challenge seeks computational methods, derived from the molecular profiling of cell lines both in a static state and in response to perturbation of ...","","https://www.synapse.org/#!Synapse:syn2785778","completed","1","","2012-06-01","2012-10-01","2023-11-01 22:08:36","2023-11-16 17:58:39" +"5","niehs-ncats-unc-toxicogenetics","NIEHS-NCATS-UNC Toxicogenetics","Predicting cytotoxicity from genomic and chemical data","This challenge is designed to build predictive models of cytotoxicity as mediated by exposure to environmental toxicants and drugs. To approach this question, we will provide a dataset containing cytotoxicity estimates as measured in lymphoblastoid cell lines derived from 884 individuals following in vitro exposure to 156 chemical compounds. In subchallenge 1, participants will be asked to model interindividual variability in cytotoxicity based on genomic profiles in order to predict cytotoxicity in unknown individuals. In subchallenge 2, participants will be asked to predict population-level parameters of cytotoxicity across chemicals based on structural attributes of compounds in order to predict median cytotoxicity and mean variance in toxicity for unknown compounds.","","https://www.synapse.org/#!Synapse:syn1761567","completed","1","","2013-06-10","2013-09-15","2023-11-01 22:08:45","2023-11-01 22:06:01" +"6","whole-cell-parameter-estimation","Whole-Cell Parameter Estimation","Seeking innovative parameter estimation methods for large models","The goal of this challenge is to explore and compare innovative approaches to parameter estimation of large, heterogeneous computational models. Participants are encouraged to develop and/or apply optimization methods, including the selection of the most informative experiments. The organizers encourage participants to form teams to collaboratively solve the challenge.","","https://www.synapse.org/#!Synapse:syn1876068","completed","1","","2013-06-10","2013-09-23","2023-06-23 00:00:00","2023-11-01 22:06:23" +"7","hpn-dream-breast-cancer-network-inference","HPN-DREAM Breast Cancer Network Inference","Inferring causal signaling networks in breast cancer","The overall goal of the Heritage-DREAM breast cancer network inference challenge is to quickly and effectively advance our ability to infer causal signaling networks and predict protein phosphorylation dynamics in cancer. We provide extensive training data from experiments on four breast cancer cell lines stimulated with various ligands. The data comprise protein abundance time-courses under inhibitor perturbations.","","https://www.synapse.org/#!Synapse:syn1720047","completed","1","","2013-06-10","2013-09-16","2023-06-23 00:00:00","2023-11-13 17:15:59" +"8","rheumatoid-arthritis-responder","Rheumatoid Arthritis Responder","Unlocking Anti-TNF response predictors in RA therapy","The goal of this project is to use a crowd-based competition framework to develop a validated molecular predictor of anti-TNF response in RA. There is an increasing need for predictors of response to therapy in inflammatory disease driven by the observation that most clinically defined diseases show variable response and the growing availability of alternative therapies. Anti-TNF drugs in Rheumatoid Arthritis represent a prototypical example of this opportunity. A number of studies have tried, over the past decade, to develop a robust predictor of response. We believe the time is right to try a different approach to developing such a biomarker with a crowd-sourced collaborative competition. This is based on DREAM and Sage Bionetworks' experience with running competitions and the availability of new unpublished large-scale data relating to RA treatment response.THIS CHALLENGE RAN FROM FEBRUARY TO OCTOBER 2014 AND IS NOW CLOSED.","","https://www.synapse.org/#!Synapse:syn1734172","completed","1","","2014-02-10","2014-06-04","2023-06-23 00:00:00","2023-11-15 22:42:17" +"9","icgc-tcga-dream-mutation-calling","ICGC-TCGA DREAM Mutation Calling","Crowdsourcing challenge to improve cancer mutation detection","The ICGC-TCGA DREAM Genomic Mutation Calling Challenge (herein, The Challenge) is an international effort to improve standard methods for identifying cancer-associated mutations and rearrangements in whole-genome sequencing (WGS) data. Leaders of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) cancer genomics projects are joining with Sage Bionetworks and IBM-DREAM to initiate this innovative open crowd-sourced Challenge [1-3].","","https://www.synapse.org/#!Synapse:syn312572","completed","1","","2013-12-14","2016-04-22","2023-06-23 00:00:00","2023-10-14 05:38:15" +"10","acute-myeloid-leukemia-outcome-prediction","Acute Myeloid Leukemia Outcome Prediction","Uncover drivers of AML using clinical and proteomic data","The AML Outcome Prediction Challenge provides a unique opportunity to access and interpret a rich dataset for AML patients that includes clinical covariates, select gene mutation status and proteomic data. Capitalizing on a unique AML reverse phase protein array (RPPA) dataset obtained at M.D. Anderson Cancer Center that captures 271 measurements for each patient, participants of the DREAM 9 Challenge will help uncover what drives AML. Outcomes of this Challenge have the potential to be used immediately to tailor therapies for newly diagnosed leukemia patients and to accelerate the development of new drugs for leukemia.","","https://www.synapse.org/#!Synapse:syn2455683","completed","1","","2014-06-02","2014-09-15","2023-06-23 00:00:00","2023-10-14 05:38:16" +"11","broad-dream-gene-essentiality-prediction","Broad-DREAM Gene Essentiality Prediction","Crowdsourcing models to predict cancer cell gene dependencies","The goal of this project is to use a crowd-based competition to develop predictive models that can infer gene dependency scores in cancer cells (genes that are essential to cancer cell viability when suppressed) using features of those cell lines. An additional goal is to find a small set of biomarkers (gene expression, copy number, and mutation features) that can best predict a single gene or set of genes.","","https://www.synapse.org/#!Synapse:syn2384331","completed","1","","2014-06-02","2014-09-29","2023-06-23 00:00:00","2023-10-14 05:38:16" +"12","alzheimers-disease-big-data","Alzheimer's Disease Big Data","Seeking accurate predictive biomarkers","The goal of the Alzheimer's Disease Big Data DREAM Challenge #1 (AD#1) was to apply an open science approach to rapidly identify accurate predictive AD biomarkers that can be used by the scientific, industrial and regulatory communities to improve AD diagnosis and treatment. AD#1 will be the first in a series of AD Data Challenges to leverage genetics and brain imaging in combination with cognitive assessments, biomarkers and demographic information from cohorts ranging from cognitively normal to mild cognitively impaired to individuals with AD.","","https://www.synapse.org/#!Synapse:syn2290704","completed","1","","2014-06-02","2014-10-17","2023-06-23 00:00:00","2023-10-14 05:38:17" +"13","olfaction-prediction","Olfaction Prediction","Predicting smell from molecule features","The goal of the DREAM Olfaction Prediction Challenge is to find models that can predict how a molecule smells from its physical and chemical features. A model that allows us to predict a smell from a molecule will provide fundamental insights into how odor chemicals are transformed into a smell percept in the brain. Further, being able to predict how a chemical smells will greatly accelerate the design of new molecules to be used as fragrances. Currently, fragrance chemists synthesize many molecules to obtain a new ingredient, but most of these will not have the desired qualities.","","https://www.synapse.org/#!Synapse:syn2811262","completed","1","","2015-01-15","2015-05-01","2023-11-01 22:11:08","2023-10-14 05:38:17" +"14","prostate-cancer","Prostate Cancer","Predict survival of docetaxel treatment in mCRPC patients","This challenge will attempt to improve the prediction of survival and toxicity of docetaxel treatment in patients with metastatic castration-resistant prostate cancer (mCRPC). The primary benefit of this Challenge will be to establish new quantitative benchmarks for prognostic modeling in mCRPC, with a potential impact for clinical decision making and ultimately understanding the mechanism of disease progression. Participating teams will be asked to submit predictive models based on clinical variables from the comparator arms of four phase III clinical trials with over 2,000 mCRPC patients treated with first-line docetaxel. The comparator arm of a clinical trial represents the patients that receive a treatment that is considered to be effective. This arm of the clinical trial is used to evaluate the effectiveness of the new therapy being tested.","","https://www.synapse.org/#!Synapse:syn2813558","completed","1","","2015-03-16","2015-07-27","2023-06-23 00:00:00","2023-10-14 05:38:18" +"15","als-stratification-prize4life","ALS Stratification Prize4Life","Predicting ALS progression and survival with data","As illustrated by the overview figure below, (a) Challenge Data includes data from ALS clinical trials and ALS registries. ALS clinical trials consist of patients from clinical trials available open access on the PRO-ACT database and patients from 6 clinical trials not yet added into the database. Data from ALS registries was collected from patients in national ALS registries. (b) Data is divided into three subsets-training data provided to solvers in full, leaderboard, and validation data that is available only to the organizers and is reserved for the scoring of the challenge. (c) The goal of this challenge is then to predict the Clinical Targets, i.e. the disease progression as ALSFRS slope as well as survival. (d) For Building the Models, participants create two algorithms-one that selects features and one that predicts outcomes. To perform predictions, data from a given patient is fed into the selector . The selector selects 6 features and a cluster/model ID (3), e.g. from a...","","https://www.synapse.org/#!Synapse:syn2873386","completed","1","","2015-06-22","2015-10-04","2023-06-23 00:00:00","2023-10-14 05:38:19" +"16","astrazeneca-sanger-drug-combination-prediction","AstraZeneca-Sanger Drug Combination Prediction","Predict effective drug combinations using genomic data","To accelerate the understanding of drug synergy, AstraZeneca has partnered with the European Bioinformatic Institute, the Sanger Institute, Sage Bionetworks, and the distributed DREAM community to launch the AstraZeneca-Sanger Drug Combination Prediction DREAM Challenge. This Challenge is designed to explore fundamental traits that underlie effective combination treatments and synergistic drug behavior using baseline genomic data, i.e. data collected pretreatment. As the basis of the Challenge, AstraZeneca is releasing ~11.5k experimentally tested drug combinations measuring cell viability over 118 drugs and 85 cancer cell lines (primarily colon, lung, and breast), and monotherapy drug response data for each drug and cell line. Moreover, in coordination with the Genomics of Drug Sensitivity in Cancer and COSMIC teams at the Sanger Institute, genomic data including gene expression, mutations (whole exome), copy-number alterations, and methylation data will be released into the publ...","","https://www.synapse.org/#!Synapse:syn4231880","completed","1","","2015-09-03","2016-03-14","2023-06-23 00:00:00","2023-10-14 05:38:19" +"17","smc-dna-meta","SMC-DNA Meta","Seeking most accurate somatic mutation detection pipeline","The goal of this Challenge is to identify the most accurate meta-pipeline for somatic mutation detection, and establish the state-of-the-art. The algorithms in this Challenge must use as input mutations predicted by one or more variant callers and output mutation calls associated with cancer. An additional goal is to highlight the complementarity of the calling algorithms and help understand their individual advantages/deficiencies.","","https://www.synapse.org/#!Synapse:syn4588939","completed","1","","2015-08-17","2016-04-10","2023-06-23 00:00:00","2023-10-14 05:38:20" +"18","smc-het","SMC-Het","Crowdsourcing challenge to improve tumor subclonal reconstruction","The ICGC-TCGA DREAM Somatic Mutation Calling-Tumour Heterogeneity Challenge (SMC-Het) is an international effort to improve standard methods for subclonal reconstruction-to quantify and genotype each individual cell population present within a tumor. Leaders of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) cancer genomics projects are joining with Sage Bionetworks and IBM-DREAM to initiate this innovative open crowd-sourced Challenge [1-3].","","https://www.synapse.org/#!Synapse:syn2813581","completed","1","","2015-11-16","2016-06-30","2023-11-01 22:21:29","2023-10-14 05:38:21" +"19","respiratory-viral","Respiratory Viral","Early predictors of respiratory infection and contagiousness","Respiratory viruses are highly infectious and cause acute illness in millions of people every year. However, there is wide variation in the physiologic response to exposure at the individual level. Some people that are exposed to virus are able to completely avoid infection. Others contract virus but are able to fight it off without exhibiting any symptoms of illness such as coughing, sneezing, sore throat or fever. It is not well understood what characteristics may protect individuals from respiratory viral infection. These individual responses are likely influenced by multiple processes including both the basal state of the human host upon exposure and the dynamics of host immune response in the early hours immediately following exposure. Many of these processes play out in the peripheral blood through activation and recruitment of circulating immune cells. Global gene expression patterns measured in peripheral blood at the time of symptom onset-several days after viral exposure...","","https://www.synapse.org/#!Synapse:syn5647810","completed","1","","2016-05-16","2016-09-28","2023-06-23 00:00:00","2023-11-14 20:16:42" +"20","disease-module-identification","Disease Module Identification","Crowdsourcing challenge to find disease modules in genomic networks","The Disease Module Identification DREAM Challenge is an open community effort to systematically assess module identification methods on a panel of state-of-the-art genomic networks and leverage the “wisdom of crowds” to discover novel modules and pathways underlying complex diseases.","","https://www.synapse.org/#!Synapse:syn6156761","completed","1","https://doi.org/10.1038/s41592-019-0509-5","2016-06-24","2016-10-01","2023-11-01 22:21:32","2023-10-16 21:17:48" +"21","encode","ENCODE","Predict transcription factor binding sites from limited data","Transcription factors (TFs) are regulatory proteins that bind specific DNA sequence patterns (motifs) in the genome and affect transcription rates of target genes. Binding sites of TFs differ across cell types and experimental conditions. Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is an experimental method that is commonly used to obtain the genome-wide binding profile of a TF of interest in a specific cell type/condition. However, profiling the binding landscape of every TF in every cell type/condition is infeasible due to constraints on cost, material and effort. Hence, accurate computational prediction of in vivo TF binding sites is critical to complement experimental results.","","https://www.synapse.org/#!Synapse:syn6131484","completed","1","","2016-07-07","2017-01-11","2023-11-01 22:21:32","2023-10-14 05:38:26" +"22","idea","Idea","Fostering collaborative solutions in health: the DREAM IDEA challenge","The DREAM Idea Challenge is designed to collaboratively shape and enable the solution of a question fundamental to improving human health. In the process, all proposals and their evaluation will be made publicly available for the explicit purpose of connecting modelers and experimentalists who want to address the same question. This Wall of Models will enable new collaborations, and help turn every good modeling idea into a success story. It will further serve as a basis for new DREAM challenges.","","https://www.synapse.org/#!Synapse:syn5659209","completed","1","","2016-06-15","2017-04-30","2023-06-23 00:00:00","2023-11-20 20:18:36" +"23","smc-rna","SMC-RNA","Crowdsourcing challenge to improve cancer mutation detection from rna data","The ICGC-TCGA DREAM Somatic Mutation Calling-RNA Challenge (SMC-RNA) is an international effort to improve standard methods for identifying cancer-associated rearrangements in RNA sequencing (RNA-seq) data. Leaders of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) cancer genomics projects are joining with Sage Bionetworks and IBM-DREAM to initiate this innovative open crowd-sourced Challenge [1-3].","","https://www.synapse.org/#!Synapse:syn2813589","completed","1","","2016-06-29","2017-05-02","2023-06-23 00:00:00","2023-10-14 05:38:29" +"24","digital-mammography-dream-challenge","Digital Mammography DREAM Challenge","Improve mammography prediction to detect breast cancer early","The Digital Mammography DREAM Challenge will attempt to improve the predictive accuracy of digital mammography for the early detection of breast cancer. The primary benefit of this Challenge will be to establish new quantitative tools-machine learning, deep learning or other-that can help decrease the recall rate of screening mammography, with a potential impact on shifting the balance of routine breast cancer screening towards more benefit and less harm. Participating teams will be asked to submit predictive models based on over 640,000 de-identified digital mammography images from over 86000 subjects, with corresponding clinical variables.","","https://www.synapse.org/#!Synapse:syn4224222","completed","1","https://doi.org/10.1001/jamanetworkopen.2020.0265","2016-11-18","2017-05-16","2023-06-23 00:00:00","2023-10-14 05:38:29" +"25","multiple-myeloma","Multiple Myeloma","Develop precise risk model for myeloma patients","Multiple myeloma (MM) is a cancer of the plasma cells in the bone marrow, with about 25,000 newly diagnosed patients per year in the United States alone. The disease's clinical course depends on a complex interplay of clinical traits and molecular characteristics of the plasma cells.1 Since risk-adapted therapy is becoming standard of care, there is an urgent need for a precise risk stratification model to assist in therapeutic decision-making and research. While progress has been made, there remains a significant opportunity to improve patient stratification to optimize treatment and to develop new therapies for high-risk patients. A DREAM Challenge represents a chance not only to integrate available data and analytical approaches to tackle this important problem, but also provides the ability to benchmark potential methods to identify those with the greatest potential to yield patient care benefits in the future.","","https://www.synapse.org/#!Synapse:syn6187098","completed","1","","2017-06-30","2017-11-08","2023-06-23 00:00:00","2023-10-14 05:38:31" +"26","ga4gh-dream-workflow-execution","GA4GH-DREAM Workflow Execution","Develop technologies to enable distributed genomic data analysis","The highly distributed and disparate nature of genomic and clinical data generated around the world presents an enormous challenge for those scientists who wish to integrate and analyze these data. The sheer volume of data often exceeds the capacity for storage at any one site and prohibits the efficient transfer between sites. To address this challenge, researchers must bring their computation to the data. Numerous groups are now developing technologies and best practice methodologies for running portable and reproducible genomic analysis pipelines as well as tools and APIs for discovering genomic analysis resources. Software development, deployment, and sharing efforts in these groups commonly rely on the use of modular workflow pipelines and virtualization based on Docker containers and related tools.","","https://www.synapse.org/#!Synapse:syn8507133","completed","1","","2017-07-21","2017-12-31","2023-06-23 00:00:00","2023-10-14 05:38:31" +"27","parkinsons-disease-digital-biomarker","Parkinson's Disease Digital Biomarker","Develop Parkinson's digital signatures from sensor data for Parkinson's disease","The Parkinson's Disease Digital Biomarker DREAM Challenge is a first of it's kind challenge, designed to benchmark methods for the processing of sensor data for development of digital signatures reflective of Parkinson's Disease. Participants will be provided with raw sensor (accelerometer, gyroscope, and magnetometer) time series data recorded during the performance of pre-specified motor tasks, and will be asked to extract data features which are predictive of PD pathology. In contrast to traditional DREAM challenges, this one will focus on feature extraction rather than predictive modeling, and submissions will be evaluated based on their ability to predict disease phenotype using an array of standard machine learning algorithms.","","https://www.synapse.org/#!Synapse:syn8717496","completed","1","","2017-07-06","2017-11-10","2023-06-23 00:00:00","2023-11-14 19:10:32" +"28","nci-cptac-proteogenomics","NCI-CPTAC Proteogenomics","Develop tools to extract insights from cancer proteomics data","Cancer is driven by aberrations in the genome [1,2], and these alterations manifest themselves largely in the changes in the structure and abundance of proteins, the main functional gene products. Hence, characterization and analyses of alterations in the proteome has the promise to shed light into cancer development and may improve development of both biomarkers and therapeutics. Measuring the proteome is very challenging, but recent rapid technology developments in mass spectrometry are enabling deep proteomics analysis [3]. Multiple initiatives have been launched to take advantage of this development to characterize the proteome of tumours, such as the Clinical Proteomic Tumor Analysis Consortium (CPTAC). These efforts hold the promise to revolutionize cancer research, but this will only be possible if the community develops computational tools powerful enough to extract the most information from the proteome, and to understand the association between genome, transcriptome and ...","","https://www.synapse.org/#!Synapse:syn8228304","completed","1","","2017-06-26","2017-11-20","2023-11-01 22:21:37","2023-10-14 05:38:33" +"29","multi-targeting-drug","Multi-Targeting Drug","Seeking generalizable methods to predict multi-target compound binding","The objective of this challenge is to incentivize development of methods for predicting compounds that bind to multiple targets. In particular, methods that are generalizable to multiple prediction problems are sought. To achieve this, participants will be asked to predict 2 separate compounds, each having specific targets to which they should bind, and a list of anti-targets to avoid. Participants should use the same methods to produce answers for questions 1 and 2.","","https://www.synapse.org/#!Synapse:syn8404040","completed","1","","2017-10-05","2018-02-26","2023-06-23 00:00:00","2023-10-14 05:38:33" +"30","single-cell-transcriptomics","Single Cell Transcriptomics","Reconstructing cell locations in Drosophila embryo from transcripts","In this Challenge on Single-Cell Transcriptomics, participants will reconstruct the location of single cells in the Drosophila embryo using single-cell transcriptomic data. Data will be made available in late August and participating challenge teams can work on the data and submit their results previous to the DREAM Conference. The best performers will be announced at the DREAM conference on Dec 8.","","https://www.synapse.org/#!Synapse:syn15665609","completed","1","","2018-09-04","2018-11-21","2023-06-23 00:00:00","2023-11-16 18:38:46" +"31","idg-drug-kinase-binding","IDG Drug-Kinase Binding","Drug-kinase binding prediction for IDG drug-kinase binding","This IDG-DREAM Drug-Kinase Binding Prediction Challenge seeks to evaluate the power of statistical and machine learning models as a systematic and cost-effective means for catalyzing compound-target interaction mapping efforts by prioritizing most potent interactions for further experimental evaluation. The Challenge will focus on kinase inhibitors, due to their clinical importance [2], and will be implemented in a screening-based, pre-competitive drug discovery project in collaboration with theIlluminating the Druggable Genome (IDG) Kinase-focused Data and Resource Generation Center, consortium, with the aim to establish kinome-wide target profiles of small-molecule agents, with the goal of extending the druggability of the human kinome space.","","https://www.synapse.org/#!Synapse:syn15667962","completed","1","","2018-10-01","2019-04-18","2023-06-23 00:00:00","2023-11-14 19:07:18" +"32","malaria","Malaria","Predict malaria drug resistance from parasite gene expression for malaria","The Malaria DREAM Challenge is open to anyone interested in contributing to the development of computational models that address important problems in advancing the fight against malaria. The overall goal of the first Malaria DREAM Challenge is to predict Artemisinin (Art) drug resistance level of a test set of malaria parasites using their in vitro transcription data and a training set consisting of published in vivo and unpublished in vitrotranscriptomes. The in vivodataset consists of ~1000 transcription samples from various geographic locations covering a wide range of life cycles and resistance levels, with other accompanying data such as patient age, geographic location, Art combination therapy used, etc [Mok et al (2015) Science]. The in vitro transcription dataset consists of 55 isolates, with transcription collected at two timepoints (6 and 24 hours post-invasion), in the absence or presence of an Art perturbation, for two biological replicates using a custom microarray a...","","https://www.synapse.org/#!Synapse:syn16924919","completed","1","","2019-04-30","2019-08-15","2023-06-23 00:00:00","2023-10-14 05:38:35" +"33","preterm-birth-prediction-transcriptomics","Preterm Birth Prediction - Transcriptomics","Determine gestational age for preterm birth prediction","A basic need in pregnancy care is to establish gestational age, and inaccurate estimates may lead to unnecessary interventions and sub-optimal patient management. Current approaches to establish gestational age rely on patient's recollection of her last menstrual period and/or ultrasound, with the latter being not only costly but also less accurate if not performed during the first trimester of pregnancy. Therefore development of an inexpensive and accurate molecular clock of pregnancy would be of benefit to patients and health care systems. Participants in sub-challenge 1 (Prediction of gestational age) will be given whole blood gene topic_3170 collected from pregnant women to develop prediction models for the gestational age at blood draw. Another challenge in obstetrics, in both low and high-income countries, is identification and treatment of women at risk of developing the ‘great obstetrical syndromes‘. Of these, preterm birth (PTB), defined as giving birth prior to completio...","","https://www.synapse.org/#!Synapse:syn18380862","completed","1","","2019-05-04","2019-12-05","2023-06-23 00:00:00","2023-11-14 19:07:28" +"34","single-cell-signaling-in-breast-cancer","Single-Cell Signaling in Breast Cancer","Exploring heterogeneous signaling in single cancer cells","Signaling underlines nearly every cellular event. Individual cells, even if genetically identical, respond to perturbation in different ways. This underscores the relevance of cellular heterogeneity, in particular in how cells respond to drugs. This is of high relevance since the fact that a subset of cells do not respond (or only weakly) to drugs can render this drug an ineffective treatment. In spite of its relevance to many diseases, comprehensive studies on the heterogeneous signaling in single cells are still lacking. We have generated the, to our knowledge, currently largest single cell signaling dataset on a panel of 67 well-characterized breast cancer cell lines by mass cytometry (3'015 conditions, ~80 mio single cells, 38 markers; Bandura et al. 2009; Bendall et al., 2011; Bodenmiller et al., 2012; Lun et al., 2017; Lun et al., 2019). These cell lines are, among others, also characterized at the genomic, transcriptomic, and proteomic level (Marcotte et al., 2016). We ask ...","","https://www.synapse.org/#!Synapse:syn20366914","completed","1","","2018-08-20","2019-11-15","2023-06-23 00:00:00","2023-10-14 05:38:37" +"35","ehr-dream-challenge-patient-mortality-prediction","EHR DREAM Challenge: Patient Mortality Prediction","New tools to reconstruct cell lineages from CRISPR mutations","The recent advent of new CRISPR-based molecular tools allows the reconstruction of cell lineages based on the phylogenetical analysis of DNA mutations induced by CRISPR during development and promises to solve the lineage of complex model organisms at single-cell resolution (see image from McKenna et al Science 2016). To date, however, no lineage reconstruction algorithms have been rigorously examined for their performance/robustness across diverse molecular tools, datasets, and number of cells/size of lineage trees. It also remains unclear whether new Machine-Learning algorithms that go beyond the classical ones developed for reconstructing phylogenetic trees, could consistently reconstruct cell lineages to a high degree of accuracy. The challenge-a partnership between The Allen Institute and DREAM-will comprise 3 subchallenges that consist of reconstructing cell lineage trees of different sizes and nature. In subchallenge 1, participants will be given experimental molecular data...","","https://www.synapse.org/#!Synapse:syn18405991","completed","1","https://doi.org/10.1093/jamia/ocad159","2019-09-09","2020-01-23","2023-06-23 00:00:00","2023-11-02 18:25:23" +"36","allen-institute-cell-lineage-reconstruction","Allen Institute Cell Lineage Reconstruction","New tools enable reconstructing complex cell lineages at single-cell resolution","The recent advent of new CRISPR-based molecular tools allows the reconstruction of cell lineages based on the phylogenetical analysis of DNA mutations induced by CRISPR during development and promises to solve the lineage of complex model organisms at single-cell resolution. To date, however, no lineage reconstruction algorithms have been rigorously examined for their performance/robustness across diverse molecular tools, datasets, and number of cells/size of lineage trees. It also remains unclear whether new Machine-Learning algorithms that go beyond the classical ones developed for reconstructing phylogenetic trees, could consistently reconstruct cell lineages to a high degree of accuracy. The challenge-a partnership between The Allen Institute and DREAM-will comprise 3 subchallenges that consist of reconstructing cell lineage trees of different sizes and nature. In subchallenge 1, participants will be given experimental molecular data to reconstruct in vitro cell lineages of l...","","https://www.synapse.org/#!Synapse:syn20692755","completed","1","","2019-10-15","2020-02-06","2023-06-23 00:00:00","2023-11-02 18:25:24" +"37","tumor-deconvolution","Tumor Deconvolution","Deconvolve bulk tumor data into immune components","The extent of stromal and immune cell infiltration within solid tumors has prognostic and predictive significance. Unfortunately, expression profiling of tumors has, until very recently, largely been undertaken using bulk techniques (e.g., microarray and RNA-seq). Unlike single-cell methods (e.g., single-cell RNA-seq, FACS, mass cytometry, or immunohistochemistry), bulk approaches average expression across all cells (cancer, stromal, and immune) within the sample and, hence, do not directly quantitate tumor infiltration. This information can be recovered by computational tumor deconvolution methods, which would thus allow interrogation of immune subpopulations across the large collection of public bulk topic_3170sets. The goal of this Challenge is to evaluate the ability of computational methods to deconvolve bulk topic_3170, reflecting a mixture of cell types, into individual immune components. Methods will be assessed based on in vitro and in silico admixtures specifically gener...","","https://www.synapse.org/#!Synapse:syn15589870","completed","1","","2019-06-26","2020-04-30","2023-06-23 00:00:00","2023-11-14 19:07:39" +"38","ctd2-pancancer-drug-activity","CTD2 Pancancer Drug Activity","Benchmark algorithms predicting drug targets from gene data","Over the last two years, the Columbia CTD2 Center developed PANACEA (Pancancer Analysis of Chemical Entity Activity), a comprehensive repertoire of dose response curves and molecular profiles representative of cellular responses to drug perturbations. PANACEA covers a broad spectrum of cellular contexts representative of poor outcome malignancies, including rare ones such as GIST sarcoma and gastroenteropancreatic neuroendocrine tumors (GEP-NETs). PANACEA is uniquely suited to support DREAM Challenges related to the elucidation of drug mechanism of action (MOA), drug sensitivity, and drug synergy. The goal of the CTD2 Pancancer Drug Activity DREAM Challenge is to foster the development and benchmarking of algorithms to predict targets of chemotherapeutic compounds from post-treatment transcriptional data.","","https://www.synapse.org/#!Synapse:syn20968331","completed","1","","2019-12-02","2020-02-13","2023-06-23 00:00:00","2023-10-20 23:11:10" +"39","ctd2-beataml","CTD2 BeatAML","Seeking new drug targets for precision AML treatment","In the era of precision medicine, AML patients have few therapeutic options, with “7 + 3” induction chemotherapy having been the standard for decades (Bertoli et al. 2017). While several agents targeting the myeloid marker CD33 or alterations in FLT3 or IDH2 have demonstrated efficacy in patients (Wei and Tiong 2017), responses are uncertain in some populations (Castaigne et al. 2012) and relapse remains prevalent (Stone et al. 2017). These drugs highlight both the promise of targeted therapies in AML and the urgent need for additional treatment options that are tailored to more refined patient subpopulations in order to achieve durable responses. The BeatAML initiative was launched as a comprehensive study of the relationship between molecular alterations and ex-vivo drug sensitivity in patients with AML. One of the primary goals of this multi-center study was to develop a discovery cohort that could yield new drug target hypotheses and predictive biomarkers of therapeutic respon...","","https://www.synapse.org/#!Synapse:syn20940518","completed","1","","2019-12-19","2020-04-28","2023-06-23 00:00:00","2023-10-14 05:38:42" +"40","metadata-automation","Metadata Automation","Semi-automating metadata annotation for enhanced data sharing in cancer research","The Cancer Research Data Commons (CRDC) will collate data across diverse groups of cancer researchers, each collecting biomedical data in different formats. This means the data must be retrospectively harmonized and transformed to enable this data to be submitted. In addition, to be findable by the broader scientific community, coherent information (metadata) is necessary about the data fields and values. Coherent metadata annotation of the data fields and their values can enable computational data transformation, query, and analysis. Creation of this type of descriptive metadata can require biomedical expertise to determine the best annotations and thus is a time-consuming and manual task which is both an obstacle and a bottleneck in data sharing and submissions. Goal-Using structured biomedical data files, challenge participants will develop tools to semi-automate annotation of metadata fields and values, using available research data annotations (e.g. caDSR CDEs) as well as es...","","https://www.synapse.org/#!Synapse:syn18065891","completed","1","","2020-01-14","2020-06-02","2023-06-23 00:00:00","2023-10-14 05:38:42" +"41","automated-scoring-of-radiographic-joint-damage","Automated Scoring of Radiographic Joint Damage","Develop automated method to quantify rheumatoid arthritis joint damage","The purpose of the RA2-DREAM Challenge is to develop an automated method to quickly and accurately quantify the degree of joint damage associated with rheumatoid arthritis (RA). Based on radiographs of the hands and feet, a novel, automated scoring method could be applied broadly for patient care and research. We challenge participants to develop algorithms to automatically assess joint space narrowing and erosions using a large set of existing radiographs with damage scores generated by visual assessment of images by trained readers using standard protocols. The end result will be a generalizable, publicly available, automated method to generate accurate, reproducible and unbiased RA damage scores to replace the current tedious, expensive, and non-scalable method of scoring by human visual inspection.","","https://www.synapse.org/#!Synapse:syn20545111","completed","1","","2019-11-04","2020-05-21","2023-06-23 00:00:00","2023-10-18 00:38:55" +"42","beat-pd","BEAT-PD","Develop mobile sensors to remotely monitor Parkinson's disease","Recent advances in mobile health have demonstrated great potential to leverage sensor-based technologies for quantitative, remote monitoring of health and disease-particularly for diseases affecting motor function such as Parkinson's disease. Such approaches have been rolled out using research-grade wearable sensors and, increasingly, through the use of smartphones and consumer wearables, such as smart watches and fitness trackers. These devices not only provide the ability to measure much more detailed disease phenotypes but also provide the ability to follow patients longitudinally with much higher frequency than is possible through clinical exams. However, the conversion of sensor-based data streams into digital biomarkers is complex and no methodological standards have yet evolved to guide this process. Parkinson's disease (PD) is a neurodegenerative disease that primarily affects the motor system but also exhibits other symptoms. Typical motor symptoms of the disease include...","","https://www.synapse.org/#!Synapse:syn20825169","completed","1","","2020-01-13","2020-05-13","2023-06-23 00:00:00","2023-10-14 05:38:45" +"43","ctd2-pancancer-chemosensitivity","CTD2 Pancancer Chemosensitivity","Predict drug sensitivity from cell line gene expression","Over the last two years, the Columbia CTD2 Center developed PANACEA (Pancancer Analysis of Chemical Entity Activity), a comprehensive repertoire of dose response curves and molecular profiles representative of cellular responses to drug perturbations. PANACEA covers a broad spectrum of cellular contexts representative of poor outcome malignancies, including rare ones such as GIST sarcoma and gastroenteropancreatic neuroendocrine tumors (GEP-NETs). PANACEA is uniquely suited to support DREAM Challenges related to the elucidation of drug mechanism of action (MOA), drug sensitivity, and drug synergy. The goal of this Challenge is to foster development and benchmarking of algorithms to predict the sensitivity, as measured by the area under the dose-response curve, of a cell line to a compound based on the baseline transcriptional profiles of the cell line. The drug perturbational RNAseq profiles of 11 cell lines for 30 chosen compounds will be provided to challenge participants, with...","","https://www.synapse.org/#!Synapse:syn21763589","completed","1","","2020-04-28","2020-07-27","2023-06-23 00:00:00","2023-10-14 05:38:45" +"44","ehr-dream-challenge-covid-19","EHR DREAM Challenge: COVID-19","Develop tools to predict COVID-19 risk without sharing data","The rapid rise of COVID-19 has challenged healthcare globally. The underlying risks and outcomes of infection are still incompletely characterized even as the world surpasses 4 million infections. Due to the importance and emergent need for better understanding of the condition and the development of patient specific clinical risk scores and early warning tools, we have developed a platform to support testing analytic and machine learning hypotheses on clinical data without data sharing as a platform to rapidly discover and implement approaches for care. We have previously applied this approach in the successful EHR DREAM Challenge focusing on Patient Mortality Prediction with UW Medicine. We have the goal of incorporating machine learning and predictive algorithms into clinical care and COVID-19 is an important and highly urgent challenge. In our first iteration, we will facilitate understanding risk factors that lead to a positive test utilizing electronic health recorded dat...","","https://www.synapse.org/#!Synapse:syn21849255","completed","1","https://doi.org/10.1001/jamanetworkopen.2021.24946","2020-04-30","2021-07-01","2023-06-23 00:00:00","2023-11-01 14:57:29" +"45","anti-pd1-response-prediction","Anti-PD1 Response Prediction","Predicting lung cancer response to immuno-oncology therapy","While durable responses and prolonged survival have been demonstrated in some lung cancer patients treated with immuno-oncology (I-O) anti-PD-1 therapy, there remains a need to improve the ability to predict which patients are more likely to receive benefit from treatment with I-O. The goal of this challenge is to leverage clinical and biomarker data to develop predictive models of response to I-O therapy in lung cancer and ultimately gain insights that may facilitate potential novel monotherapies or combinations with I-O.","","https://www.synapse.org/#!Synapse:syn18404605","completed","1","","2020-11-17","2021-02-25","2023-06-23 00:00:00","2023-11-02 18:25:16" +"46","brats-2021-challenge","BraTS 2021 Challenge","Developing ML methods to analyze brain tumor MRI scans","Glioblastoma, and diffuse astrocytic glioma with molecular features of glioblastoma (WHO Grade 4 astrocytoma), are the most common and aggressive malignant primary tumor of the central nervous system in adults, with extreme intrinsic heterogeneity in appearance, shape, and histology. Glioblastoma patients have very poor prognosis, and the current standard of care treatment comprises surgery, followed by radiotherapy and chemotherapy. The International Brain Tumor Segmentation (BraTS) Challenges —which have been running since 2012— assess state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans.","","https://www.synapse.org/#!Synapse:syn25829067","completed","1","","2021-07-07","2021-10-15","2023-06-23 00:00:00","2023-10-14 05:38:48" +"47","cancer-data-registry-nlp","Cancer Data Registry NLP","Predicting lung cancer response to immuno-oncology therapy","A critical bottleneck in translational and clinical research is access to large volumes of high-quality clinical data. While structured data exist in medical EHR systems, a large portion of patient information including patient status, treatments, and outcomes is contained in unstructured text fields. Research in Natural Language Processing (NLP) aims to unlock this hidden and often inaccessible information. However, numerous challenges exist in developing and evaluating NLP methods, much of it centered on having “gold-standard” metrics for evaluation, and access to data that may contain personal health information (PHI). This DREAM Challenge will focus on the development and evaluation of of NLP algorithms that can improve clinical trial matching and recruitment.","","https://www.synapse.org/#!Synapse:syn18361217","upcoming","1","","\N","\N","2023-06-23 00:00:00","2023-10-14 05:38:49" +"48","barda-community-challenge-pediatric-covid-19-data-challenge","BARDA Community Challenge - Pediatric COVID-19 Data Challenge","Models to predict severe COVID-19 in children sought","While most children with COVID-19 are asymptomatic or have mild symptoms, healthcare providers have difficulty determining which among their pediatric patients will progress to moderate or severe COVID-19 early in the progression. Some of these patients develop multisystem inflammatory syndrome in children (MIS-C), a life-threatening inflammation of organs and tissues. Methods to distinguish children at risk for severe COVID-19 complications, including conditions such as MIS-C, are needed for earlier interventions to improve pediatric patient outcomes. Multiple HHS divisions are coming together for a data challenge competition that will leverage de-identified electronic health record data to develop, train and validate computational models that can predict severe COVID-19 complications in children, equipping healthcare providers with the information and tools they need to identify pediatric patients at risk.","","https://www.synapse.org/#!Synapse:syn25875374/wiki/611225","completed","1","","2021-08-19","2021-12-17","2023-06-23 00:00:00","2023-10-14 05:38:50" +"49","brats-continuous-evaluation","BraTS Continuous Evaluation","Seeking innovations to improve brain tumor diagnosis and treatment","Brain tumors are among the deadliest types of cancer. Specifically, glioblastoma, and diffuse astrocytic glioma with molecular features of glioblastoma (WHO Grade 4 astrocytoma), are the most common and aggressive malignant primary tumor of the central nervous system in adults, with extreme intrinsic heterogeneity in appearance, shape, and histology, with a median survival of approximately 15 months. Brain tumors in general are challenging to diagnose, hard to treat and inherently resistant to conventional therapy because of the challenges in delivering drugs to the brain, as well as the inherent high heterogeneity of these tumors in their radiographic, morphologic, and molecular landscapes. Years of extensive research to improve diagnosis, characterization, and treatment have decreased mortality rates in the U.S by 7% over the past 30 years. Although modest, these research innovations have not translated to improvements in survival for adults and children in low-and middle-income...","","https://www.synapse.org/brats_ce","completed","1","","2022-01-01","\N","2023-06-23 00:00:00","2023-10-14 05:38:51" +"50","fets-2022","FeTS 2022","Federated Learning Challenge 2022: advancing brain tumor segmentation algorithms","FeTS 2022 focuses on benchmarking methods for federated learning (FL), and particularly i) weight aggregation methods for federated training, and ii) algorithmic generalizability on out-of-sample data based on federated evaluation. In line with its last instance (FeTS 2021-the 1st FL challenge ever organized), FeTS 2022 targets the task of brain tumor segmentation and builds upon i) the centralized dataset of >8,000 clinically-acquired multi-institutional MRI scans (from the RSNA-ASNR-MICCAI BraTS 2021 challenge) with their real-world partitioning, and ii) the collaborative network of remote independent institutions included in a real-world federation. Participants are welcome to compete in either of the two challenge tasks- Task 1 (“Federated Training”) seeks effective weight aggregation methods for the creation of a consensus model given a pre-defined segmentation algorithm for training, while also (optionally) accounting for network outages. Task 2 (“Federated Evaluation”) see...","","https://www.synapse.org/#!Synapse:syn28546456/wiki/617093","completed","1","","2022-04-08","2022-08-15","2023-06-23 00:00:00","2023-10-18 00:36:14" +"51","random-promotor","Random Promotor","Deciphering gene regulation: training models to predict gene expression patterns","Decoding how gene expression is regulated is critical to understanding disease. Regulatory DNA is decoded by the cell in a process termed “cis-regulatory logic”, where proteins called Transcription Factors (TFs) bind to specific DNA sequences within the genome and work together to produce as output a level of gene expression for downstream adjacent genes. This process is exceedingly complex to model as a large number of parameters is needed to fully describe the process (see Rationale, de Boer et al. 2020; Zeitingler J. 2020). Understanding the cis-regulatory logic of the human genome is an important goal and would provide insight into the origins of many diseases. However, learning models from human data is challenging due to limitations in the diversity of sequences present within the human genome (e.g. extensive repetitive DNA), the vast number of cell types that differ in how they interpret regulatory DNA, limited reporter assay data, and substantial technical biases present ...","","https://www.synapse.org/#!Synapse:syn28469146/wiki/617075","completed","1","","2022-05-02","2022-08-07","2023-06-23 00:00:00","2023-10-14 05:38:53" +"52","preterm-birth-prediction-microbiome","Preterm Birth Prediction - Microbiome","Seeking innovations to improve brain tumor diagnosis and treatment","Globally, about 11% of infants every year are born preterm, defined as birth prior to 37 weeks of gestation, totaling nearly 15 million births.(5) In addition to the emotional and financial toll on families, preterm births have higher rates of neonatal death, nearly 1 million deaths each year, and long-term health consequences for some children. Infants born preterm are at risk for a variety of adverse outcomes, such as respiratory illnesses, cerebral palsy, infections, and blindness, with infants born very preterm (i.e., before 32 weeks) at increased risk of these conditions.(6) The ability to accurately predict which women are at a higher risk for preterm birth would help healthcare providers to treat in a timely manner those at higher risk of delivering preterm. Currently available treatments for pregnant women at risk of preterm delivery include corticosteroids for fetal maturation and magnesium sulfate provided prior to 32 weeks to prevent cerebral palsy.(7) There are several...","","https://www.synapse.org/#!Synapse:syn26133770/wiki/612541","completed","1","","2022-07-19","2022-09-16","2023-06-23 00:00:00","2023-10-14 05:38:54" +"53","finrisk","FINRISK - Heart Failure and Microbiome","Predict incident risk for heart failure in a finnish adults","Cardiovascular diseases are the leading cause of death both in men and women worldwide. Heart failure (HF) is the most common form of heart disease, characterised by the heart's inability to pump a sufficient supply of blood to meet the needs of the body. The lifetime risk of developing HF is roughly 20%, yet, it remains difficult to diagnose due to its and a lack of agreement of diagnostic criteria. As the diagnosis of HF is dependent on ascertainment of clinical histories and appropriate screening of symptomatic individuals, identifying those at risk of HF is essential. This DREAM challenge focuses on the prediction of HF using a combination of gut microbiome and clinical variables. This challenge is designed to predict incident risk for heart failure in a large human population study of Finnish adults, FINRISK 2002 (Borodulin et al., 2018). The FINRISK study has been conducted in Finland to investigate the risk factors for cardiovascular disease every 5 years since 1972. A rand...","","https://www.synapse.org/#!Synapse:syn27130803/wiki/616705","completed","1","","2022-09-20","2023-01-30","2023-06-23 00:00:00","2023-11-14 19:07:49" +"54","scrna-seq-and-scatac-seq-data-analysis","scRNA-seq and scATAC-seq Data Analysis","Assess computational methods for scrna-seq and scatac-seq analysis","Understanding transcriptional regulation at individual cell resolution is fundamental to understanding complex biological systems such as tissues and organs. Emerging high-throughput sequencing technologies now allow for transcript quantification and chromatin accessibility at the single cell level. These technologies present unique challenges due to inherent data sparsity. Proper signal correction is key to accurate gene expression quantification via scRNA-seq, which propagates into downstream analyses such as differential gene expression analysis and cell-type identification. In the even more sparse scATAC-seq data, the correct identification of informative features is key to assessing cell heterogeneity at the chromatin level. The aims of this challenge will be two-fold- 1) To evaluate computational methods for signal correction and peak identification in scRNA-seq and scATAC-seq, respectively; 2) To assess the impact of these methods on downstream analysis","","https://www.synapse.org/#!Synapse:syn26720920/wiki/615338","completed","1","","2022-11-29","2023-02-08","2023-06-23 00:00:00","2023-10-14 05:38:56" +"55","cough-diagnostic-algorithm-for-tuberculosis","COugh Diagnostic Algorithm for Tuberculosis","Predict TB status using features extracted from audio of elicited coughs","Tuberculosis (TB), a communicable disease caused by Mycobacterium tuberculosis, is a major cause of ill health and one of the leading causes of death worldwide. Until the COVID-19 pandemic, TB was the leading cause of death from a single infectious agent, ranking even above HIV/AIDS. In 2020, an estimated 9.9 million people fell ill with TB and 1.3 million died of TB worldwide. However, approximately 40% of people with TB were not diagnosed or reported to public health authorities because of challenges in accessing health facilities or failure to be tested or treated when they do. The development of low-cost, non-invasive digital screening tools may improve some of the gaps in diagnosis. As cough is a common symptom of TB, it has the potential to be used as a biomarker for diagnosis of disease. Several previous studies have demonstrated the potential for cough sounds to be used to screen for TB[1-3], though these were typically done in small samples or limited settings. Further de...","","https://www.synapse.org/#!Synapse:syn31472953/wiki/617828","active","1","","2022-10-16","\N","2023-06-23 00:00:00","2023-12-06 00:58:30" +"56","nih-long-covid-computational-challenge","NIH Long COVID Computational Challenge","Understanding prevalence and outcomes of post-COVID syndrome","The overall prevalence of post-acute sequelae of SARS-CoV-2 (PASC) is currently unknown, but there is growing evidence that more than half of COVID-19 survivors experience at least one symptom of PASC/Long COVID at six months after recovery of the acute illness. Reports also reflect an underlying heterogeneity of symptoms, multi-organ involvement, and persistence of PASC/Long COVID in some patients. Research is ongoing to understand prevalence, duration, and clinical outcomes of PASC/Long COVID. Symptoms of fatigue, cognitive impairment, shortness of breath, and cardiac damage, among others, have been observed in patients who had only mild initial disease. The breadth and complexity of data created in today's health care encounters require advanced analytics to extract meaning from longitudinal data on symptoms, laboratory results, images, functional tests, genomics, mobile health/wearable devices, written notes, electronic health records (EHR), and other relevant data types. Adva...","","https://www.synapse.org/#!Synapse:syn33576900/wiki/618451","completed","1","","2022-08-25","2022-12-15","2023-06-23 00:00:00","2023-10-18 00:39:03" +"57","bridge2ai","Bridge2AI","What makes a good color palette?","What makes a good color palette?","","","upcoming","1","","\N","\N","2023-06-23 00:00:00","2023-11-20 20:19:26" +"58","rare-x-open-data-science","RARE-X Open Data Science","Unlocking rare disease mysteries through open science collaboration","The Xcelerate RARE-A Rare Disease Open Science Data Challenge is bringing together researchers and data scientists in a collaborative and competitive environment to make the best use of patient-provided data to solve big unknowns in healthcare. The Challenge will launch to researchers in late May 2023, focused on rare pediatric neurodevelopmental diseases.","","https://www.synapse.org/#!Synapse:syn51198355/wiki/621435","completed","1","","2023-05-17","2023-08-16","2023-06-23 00:00:00","2023-10-14 05:38:59" +"59","cagi5-regulation-saturation","CAGI5: Regulation saturation","Predicting effects of variants in disease-linked enhancers and promoters","17,500 single nucleotide variants (SNVs) in 5 human disease associated enhancers (including IRF4, IRF6, MYC, SORT1) and 9 promoters (including TERT, LDLR, F9, HBG1) were assessed in a saturation mutagenesis massively parallel reporter assay. Promoters were cloned into a plasmid upstream of a tagged reporter construct, and reporter expression was measured relative to the plasmid DNA to determine the impact of promoter variants. Enhancers were placed upstream of a minimal promoter and assayed similarly. The challenge is to predict the functional effects of these variants in the regulatory regions as measured from the reporter expression.","","https://genomeinterpretation.org/cagi5-regulation-saturation.html","completed","14","","2018-01-04","2018-05-03","2023-06-23 00:00:00","2023-11-01 23:42:37" +"60","cagi5-calm1","CAGI5: CALM1","Predicting effects of calmodulin variants on yeast growth","Calmodulin is a calcium-sensing protein that modulates the activity of a large number of proteins in the cell. It is involved in many cellular processes, and is especially important for neuron and muscle cell function. Variants that affect calmodulin function have been found to be causally associated with cardiac arrhythmias. A large library of calmodulin missense variants was assessed with respect to their effects on protein function using a high-throughput yeast complementation assay. The challenge is to predict the functional effects of these calmodulin variants on competitive growth in a high-throughput yeast complementation assay.","","https://genomeinterpretation.org/cagi5-calm1.html","completed","14","","2017-10-21","2017-12-20","2023-06-23 00:00:00","2023-10-18 15:35:49" +"61","cagi5-pcm1","CAGI5: PCM1","Assessing PCM1 variants' impact on zebrafish ventricle","The PCM1 (Pericentriolar Material 1) gene is a component of centriolar satellites occurring around centrosomes in vertebrate cells. Several studies have implicated PCM1 variants as a risk factor for schizophrenia. Ventricular enlargement is one of the most consistent abnormal structural brain findings in schizophrenia Therefore 38 transgenic human PCM1 missense mutations implicated in schizophrenia were assayed in a zebrafish model to determine their impact on the posterior ventricle area. The challenge is to predict whether variants implicated in schizophrenia impact zebrafish ventricular area.","","https://genomeinterpretation.org/cagi5-pcm1.html","completed","14","","2017-11-09","2018-04-19","2023-06-23 00:00:00","2023-10-18 15:35:49" +"62","cagi5-frataxin","CAGI5: Frataxin","Predicting ΔΔGH20 for Frataxin Variants","Fraxatin is a highly-conserved protein found in prokaryotes and eukaryotes that is required for efficient regulation of cellular iron homeostasis. Humans with a frataxin deficiency have the cardio-and neurodegenerative disorder Friedreich's ataxia. A library of eight missense variants was assessed by near and far-UV circular dichroism and intrinsic fluorescence spectra to determine thermodynamic stability at different concentration of denaturant. These were used to calculate a ΔΔGH20 value, the difference in unfolding free energy (ΔGH20) between the mutant and wild-type proteins for each variant. The challenge is to predict ΔΔGH20 for each frataxin variant.","","https://genomeinterpretation.org/cagi5-frataxin.html","completed","14","","2017-11-30","2018-04-18","2023-06-23 00:00:00","2023-10-18 15:35:50" +"63","cagi5-tpmt","CAGI5: TPMT and p10","Predicting TPMT and PTEN protein stability variants","The gene p10 encodes for PTEN (Phosphatase and TEnsin Homolog), an important secondary messenger molecule promoting cell growth and survival through signaling cascades including those controlled by AKT and mTOR. Thiopurine S-methyl transferase (TPMT) is a key enzyme involved in the metabolism of thiopurine drugs and functions by catalyzing the S-methylation of aromatic and heterocyclic sulfhydryl groups. A library of thousands of PTEN and TPMT mutations was assessed to measure the stability of the variant protein using a multiplexed variant stability profiling (VSP) assay, which detects the presence of EGFP fused to the mutated PTEN and TPMT protein respectively. The stability of the variant protein dictates the abundance of the fusion protein and thus the EGFP level of the cell. The challenge is to predict the effect of each variant on TPMT and/or PTEN protein stability.","","https://genomeinterpretation.org/cagi5-tpmt.html","completed","14","","2017-11-30","2017-12-01","2023-06-23 00:00:00","2023-10-14 05:39:03" +"64","cagi5-annotate-all-missense","CAGI5: Annotate all nonsynonymous variants","Annotate all nonsynonymous variants","dbNSFP describes 810,848,49 possible protein-altering variants in the human genome. The challenge is to predict the functional effect of every such variant. For the vast majority of these missense variants, the functional impact is not currently known, but experimental and clinical evidence are accruing rapidly. Rather than drawing upon a single discrete dataset as typical with CAGI, predictions will be assessed by comparing with experimental or clinical annotations made available after the prediction submission date, on an ongoing basis. if predictors assent, predictions will also incorporated into dbNSFP.","","https://genomeinterpretation.org/cagi5-annotate-all-missense.html","completed","14","","2017-11-30","2018-05-09","2023-06-23 00:00:00","2023-10-14 05:39:04" +"65","cagi5-gaa","CAGI5: GAA","Predict enzyme activity of GAA mutants in Pompe disease","Acid alpha-glucosidase (GAA) is a lysosomal alpha-glucosidase. Some mutations in GAA cause a rare disorder, Pompe disease, (Glycogen Storage Disease II). Rare GAA missense variants found in a human population sample have been assayed for enzymatic activity in transfected cell lysates. The assessment of this challenge will include evaluations that recognize novelty of approach. The challenge is to predict the fractional enzyme activity of each mutant protein compared to the wild-type enzyme.","","https://genomeinterpretation.org/cagi5-gaa.html","completed","14","","2017-11-09","2018-04-25","2023-06-23 00:00:00","2023-10-14 05:39:04" +"66","cagi5-chek2","CAGI5: CHEK2","Estimate CHEK2 gene variant probabilities in Latino breast cancer cases","Variants in the CHEK2 gene are associated with breast cancer. This challenge includes CHEK2 gene variants from approximately 1200 Latino breast cancer cases and 1200 ethnically matched controls. This challenge is to estimate the probability of each gene variant occurring in an individual from the cancer affected cohort.","","https://genomeinterpretation.org/cagi5-chek2.html","completed","14","","2017-12-20","2018-04-24","2023-06-23 00:00:00","2023-10-14 05:39:07" +"67","cagi5-enigma","CAGI5: ENIGMA","Predict cancer risk from BRCA1/2 gene variants","Breast cancer is the most prevalent cancer among women worldwide. The association between germline mutations in the BRCA1 and BRCA2 genes and the development of cancer has been well established. The most common high-risk mutations associated with breast cancer are those in the autosomal dominant breast cancer genes 1 and 2 (BRCA1 and BRCA2). Mutations in these genes are found in 1-3% of breast cancer cases. The challenge is to predict which variants are associated with increased risk for breast cancer.","","https://genomeinterpretation.org/cagi5-enigma.html","completed","14","","2017-12-20","2018-05-01","2023-06-23 00:00:00","2023-10-14 05:39:08" +"68","cagi5-mapsy","CAGI5: MaPSy","Predict the impact of genetic variants on splicing mechanisms","The Massively Parallel Splicing Assay (MaPSy) approach was used to screen 797 reported exonic disease mutations using a mini-gene system, assaying both in vivo via transfection in tissue culture, and in vitro via incubation in cell nuclear extract. The challenge is to predict the degree to which a given variant causes changes in splicing.","","https://genomeinterpretation.org/cagi5-mapsy.html","completed","14","","2017-11-29","2018-05-07","2023-06-23 00:00:00","2023-10-14 05:39:08" +"69","cagi5-vex-seq","CAGI5: Vex-seq","Predict splicing changes from variants in globin gene","A barcoding approach called Variant exon sequencing (Vex-seq) was applied to assess effect of 2,059 natural single nucleotide variants and short indels on splicing of a globin mini-gene construct transfected into HepG2 cells. This is reported as ΔΨ (delta PSI, or Percent Spliced In), between the variant Ψand the reference Ψ. The challenge is to predict ΔΨ for each variant.","","https://genomeinterpretation.org/cagi5-vex-seq.html","completed","14","","2017-12-14","2018-05-02","2023-06-23 00:00:00","2023-10-16 17:51:58" +"70","cagi5-sickkids5","CAGI5: SickKids clinical genomes","Predict genetic disorders from 30 child genomes and phenotypes","This challenge involves 30 children with suspected genetic disorders who were referred for clinical genome sequencing. Predictors are given the 30 genome sequences, and are also provided with the phenotypic descriptions as shared with the diagnostic laboratory. The challenge is to predict what class of disease is associated with each genome, and which genome corresponds to which clinical description. Predictors may additionally identify the diagnostic variant(s) underlying the predictions, and identify predictive secondary variants conferring high risk of other diseases whose phenotypes are not reported in the clinical descriptions.","","https://genomeinterpretation.org/cagi5-sickkids5.html","completed","14","","2017-12-22","2018-04-26","2023-06-23 00:00:00","2023-10-14 05:39:10" +"71","cagi5-intellectual-disability","CAGI5: ID Panel","Predict phenotypes and variants from gene panel sequences","The challenge presented here is to use computational methods to predict a patient's clinical phenotype and the causal variant(s) based on analysis of their gene panel sequence data. Sequence data for 74 genes associated with intellectual disability (ID) and/or Autism spectrum disorders (ASD) from a cohort of 150 patients with a range of neurodevelopmental presentations (ID, autism, epilepsy, etc..) have been made available for this challenge. For each patient, predictors must report the causative variants and which of seven phenotypes are present.","","https://genomeinterpretation.org/cagi5-intellectual-disability.html","completed","14","","2017-12-22","2018-04-30","2023-06-23 00:00:00","2023-10-18 15:28:06" +"72","cagi5-clotting-disease","CAGI5: Clotting disease exomes","Predict venous thromboembolism risk in African Americans","African Americans have a higher incidence of developing venous thromboembolisms (VTE), which includes deep vein thrombosis (DVT) and pulmonary embolism (PE), than people of European ancestry. Participants are provided with exome data and clinical covariates for a cohort of African Americans who have been prescribed Warfarin either because they had experienced a VTE event or had been diagnosed with atrial fibrillation (which predisposes to clotting). The challenge is to distinguish between these conditions. At present, in contrast to European ancestry, there are no genetic methods for anticipating which African Americans are most at risk of a venous thromboembolism, and the results of this challenge may contribute to the development of such tools.","","https://genomeinterpretation.org/cagi5-clotting-disease.html","completed","14","","2017-11-23","2018-04-28","2023-06-23 00:00:00","2023-10-18 15:30:55" +"73","cagi6-sickkids","CAGI6: SickKids clinical genomes and transcriptomes","Identify genes causing rare diseases using transcriptomics","This challenge involves data from 79 children who were referred to The Hospital for Sick Children's (SickKids) Genome Clinic for genome sequencing because of suspected but undiagnosed genetic disorders. Research subjects are consented for sharing of their sequence data and phenotype information with researchers working to understand the molecular causes of rare disease. When a candidate disease variant believed to be related to the phenotype is identified, the variant is adjudicated and confirmed in a clinical setting. In this challenge, transcriptomic and phenotype data from a subset of the “solved” (diagnosed) and “unsolved” SickKids patients will be provided, along with corresponding genomic sequence data. The challenge is to use a transcriptome-driven approach to identify the gene(s) and molecular mechanisms underlying the phenotypic descriptions in each case. For the unsolved cases, prioritized variants from the participating teams will be examined to see if additional diagno...","","https://genomeinterpretation.org/cagi6-sickkids.html","completed","1","","2021-08-04","2021-12-31","2023-06-23 00:00:00","2023-11-02 18:02:23" +"74","cagi6-cam","CAGI6: CaM","Predict the impact of point mutations on calmodulin stability","Calmodulin (CaM) is a ubiquitous calcium (Ca2+) sensor protein interacting with more than 200 molecular partners, thereby regulating a variety of biological processes. Missense point mutations in the genes encoding CaM have been associated with ventricular tachycardia and sudden cardiac death. A library encompassing up to 17 point mutations was assessed by far-UV circular dichroism (CD) by measuring melting temperature (Tm) and percentage of unfolding (%unfold) upon thermal denaturation at pH and salt concentration that mimic the physiological conditions. The challenge is to predict: the Tm and %unfold values for isolated CaM variants under Ca2+-saturating conditions (Ca2+-CaM) and in the Ca2+-free (apo) state; whether the point mutation stabilizes or destabilizes the protein (based on Tm and %unfold).","","https://genomeinterpretation.org/cagi6-cam.html","completed","1","","2021-06-08","2021-10-11","2023-06-23 00:00:00","2023-10-18 15:32:37" +"75","cami-ii","CAMI II","Assemble and classify microbial genomes in complex samples","CAMI II offers several challenges-an assembly, a genome binning, a taxonomic binning and a taxonomic profiling challenge, on several multi-sample data sets from different environments, including long and short read data. This includes a marine data set and a high-strain diversity data set, with a third data set to follow later. A pathogen detection challenge on a clinical sample is also provided.","","https://www.microbiome-cosi.org/cami/cami/cami2","completed","3","","2019-01-14","2021-01-31","2023-06-23 00:00:00","2023-10-17 23:15:00" +"76","camda18-metasub-forensics","CAMDA18-MetaSUB Forensics","Build a metagenomic map of mass-transit systems globally","The MetaSUB International Consortium is building a longitudinal metagenomic map of mass-transit systems and other public spaces across the globe. The consortium maintains a strategic partnership with CAMDA and this year provides data from global City Sampling Days for the first-ever multi-city forensic analyses.","","http://camda2018.bioinf.jku.at/doku.php/contest_dataset#metasub_forensics_challenge","completed","14","","\N","\N","2023-06-23 00:00:00","2023-11-01 20:37:34" +"77","camda18-cmap-drug-safety","CAMDA18-CMap Drug Safety","Predict drug toxicity using cell-based gene expression data","Attrition in drug discovery and development due to safety / toxicity issues remains a significant concern, and there are strong efforts to identify and mitigate risk as early as possible. Drug-induced liver injury (DILI) is one of the primary problems in drug development and regulatory clearance due to the poor performance of existing preclinical models. There is a pressing need to evaluate alternative methods for predicting DILI, with great hopes being placed in modern approaches from statistics and machine learning applied to genome scale profiling data. A critical question thus is if we can better integrate, understand, and exploit information from cell-based screens like the Broad Institute Connectivity Map (CMap, Science 313, Nature Reviews Cancer 7). This CAMDA challenge focuses on understanding or predicting drug induced liver injury in humans from cell-based screens, specifically the CMap gene expression responses of two different cancer cell lines (MCF7 and PC3) to 276 d...","","http://camda2018.bioinf.jku.at/doku.php/contest_dataset#cmap_drug_safety_challenge","completed","14","","\N","\N","2023-06-23 00:00:00","2023-11-01 20:37:35" +"78","camda18-cancer-data-integration","CAMDA18-Cancer Data Integration","Unify data integration approaches for breast cancer and neuroblastoma","Examine the power of data integration in a real-world clinical settings. Many approaches work well on some data-sets yet not on others. We here challenge you to demonstrate a unified single approach to data-integration that matches or outperforms the current state of the art on two different diseases, breast cancer and neuroblastoma. Breast cancer affects about 3 million women every year (McGuire et al, Cancers 7), and this number is growing fast, especially in developed countries. Can you improve on the large Metabric study (Curtis et al., Nature 486, and Dream Challenge, Margolin et al, Sci Transl Med 5)? The cohort is biologically heterogeneous with all five distinct PAM50 breast cancer subtypes represented. Matched profiles for microarray and copy number data as well as clinical information (survival times, multiple prognostic markers, therapy data) are available for about 2,000 patients. Neuroblastoma is the most common extracranial solid tumor in children. The base study com...","","http://camda2018.bioinf.jku.at/doku.php/contest_dataset#cancer_data_integration_challenge","completed","14","","\N","\N","2023-06-23 00:00:00","2023-11-01 20:37:36" +"79","cafa-4","CAFA 4","Assess algorithms for predicting protein function","The goal of the Critical Assessment of Functional Annotation(CAFA) challenge is to evaluate automated protein function prediction algorithms in the task of predicting Gene Ontology and Human Phenotype Ontology terms for a given set of protein sequences. For the GO-based predictions, the evaluation will be carried out for the Molecular Function Ontology, Biological Process Ontology and Cellular Component Ontology. Participants develop protein function prediction algorithms using training protein sequence data and submit their predictions on target protein sequence data.","","https://www.biofunctionprediction.org/cafa/","completed","1","","2019-10-21","2020-02-12","2023-06-23 00:00:00","2023-10-14 05:39:20" +"80","casp13","CASP13","CASP assesses protein structure prediction methods","CASP (Critical Assessment of Structure Prediction) is a community wide experiment to determine and advance the state of the art in modeling protein structure from amino acid sequence. Every two years, participants are invited to submit models for a set of proteins for which the experimental structures are not yet public. Independent assessors then compare the models with experiment. Assessments and results are published in a special issue of the journal PROTEINS. In the most recent CASP round, CASP12, nearly 100 groups from around the world submitted more than 50,000 models on 82 modeling targets","","https://predictioncenter.org/casp13/index.cgi","completed","14","","2018-04-18","2018-08-20","2023-06-23 00:00:00","2023-10-17 22:52:29" +"81","casp14","CASP14","Assess progress in protein structure prediction","CASP (Critical Assessment of Structure Prediction) is a community wide experiment to determine and advance the state of the art in modeling protein structure from amino acid sequence. Every two years, participants are invited to submit models for a set of proteins for which the experimental structures are not yet public. Independent assessors then compare the models with experiment. Assessments and results are published in a special issue of the journal PROTEINS. In the most recent CASP round, CASP14, nearly 100 groups from around the world submitted more than 67,000 models on 90 modeling targets.","","https://predictioncenter.org/casp14/index.cgi","completed","14","","2020-05-04","2020-09-07","2023-06-23 00:00:00","2023-10-17 22:47:26" +"82","cfsan-pathogen-detection","CFSAN Pathogen Detection","Rapidly identify food sources of outbreaks","In the U.S. alone, one in six individuals, an estimated 48 million people, fall prey to foodborne illness, resulting in 128,000 hospitalizations and 3,000 deaths per year. Economic burdens are estimated cumulatively at $152 billion dollars annually, including $39 billion due to contamination of fresh and processed produce. One longstanding problem is the ability to rapidly identify the food-source associated with the outbreak being investigated. The faster an outbreak is identified and the increased certainty that a given source (e.g., papayas from Mexico) and patients are linked, the faster the outbreak can be stopped, limiting morbidity and mortality. In the last few years, the application of next-generation sequencing (NGS) technology for whole genome sequencing (WGS) of foodborne pathogens has revolutionized food pathogen outbreak surveillance. WGS of foodborne pathogens enables high-resolution identification of pathogens isolated from food or environmental samples. These pat...","","https://precision.fda.gov/challenges/2","completed","6","","2018-02-15","2018-04-26","2023-06-23 00:00:00","2023-10-14 05:39:23" +"83","cdrh-biothreat","CDRH Biothreat","Identify infectious diseases from clinical samples using sequencing technology","Many infectious diseases have similar signs and symptoms, making it challenging for healthcare providers to identify the disease-causing agent. Clinical samples are often tested by multiple test methods to help reveal the microbe that is causing the infectious disease. The results of these test methods can help healthcare professionals determine the best treatment for patients. Today, High-Throughput Sequencing (HTS) or Next Generation Sequencing (NGS) technology has the capability, as a single test, to accomplish what might have required several different tests in the past. NGS technology may allow the diagnosis of infections without prior knowledge of disease(s) cause. NGS technology can potentially reveal the presence of all microorganisms in a patient sample. Using infectious disease NGS (ID-NGS) technology, each microbial pathogen may be identified by its unique genomic fingerprint. The vision of ID-NGS technology is to further improve patient care by delivering diagnostics ...","","https://precision.fda.gov/challenges/3","completed","6","","2018-08-03","2018-10-18","2023-06-23 00:00:00","2023-10-14 05:39:24" +"84","multi-omics-enabled-sample-mislabeling-correction","Multi-omics Enabled Sample Mislabeling Correction","Identify and correct sample and data mislabeling events","In biomedical research, sample mislabeling (accidental swapping of patient samples) or data mislabeling (accidental swapping of patient omics data) has been a long-standing problem that contributes to irreproducible results and invalid conclusions. These problems are particularly prevalent in large scale multi-omics studies, in which multiple different omics experiments are carried out at different time periods and/or in different labs. Human errors could arise during sample transferring, sample tracking, large-scale data generation, and data sharing/management. Thus, there is a pressing need to identify and correct sample and data mislabeling events to ensure the right data for the right patient. Simultaneous use of multiple types of omics platforms to characterize a large set of biological samples, as utilized in The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC) projects, has been demonstrated as a powerful approach to understanding the ...","","https://precision.fda.gov/challenges/4","completed","6","https://doi.org/10.1038/s41591-018-0180-x","2018-09-24","2018-12-19","2023-06-23 00:00:00","2023-11-14 19:07:58" +"85","biocompute-object-app-a-thon","BioCompute Object App-a-thon","Seeking standards for reproducible bioinformatics analysis","Like scientific laboratory experiments, bioinformatics analysis results and interpretation are faced with reproducibility challenges due to the variability in multiple computational parameters, including input format, prerequisites, platform dependencies, and more. Even small changes in these computational parameters may have a large impact on the results and carry big implications for their scientific validity. Because there are currently no standardized schemas for reporting computational scientific workflows and parameters together with their results, the ways in which these workflows are communicated is highly variable, incomplete, and difficult or impossible to reproduce. The US Food and Drug Administration (FDA) High Performance Virtual Environment (HIVE) group and George Washington University (GW) have partnered to establish a framework for community-based standards development and harmonization of high-throughput sequencing (HTS) computations and data formats based arou...","","https://precision.fda.gov/challenges/7/","completed","6","https://doi.org/10.1101/2020.11.02.365528","2019-05-14","2019-10-18","2023-06-23 00:00:00","2023-10-14 05:39:25" +"86","brain-cancer-predictive-modeling-and-biomarker-discovery","Brain Cancer Predictive Modeling and Biomarker Discovery","Seeking novel biomarkers to advance precision medicine for brain tumors","An estimated 86,970 new cases of primary brain and other central nervous system tumors are expected to be diagnosed in the US in 2019. Brain tumors comprise a particularly deadly subset of all cancers due to limited treatment options and the high cost of care. Only a few prognostic and predictive markers have been successfully implemented in the clinic so far for gliomas, the most common malignant brain tumor type. These markers include MGMT promoter methylation in high-grade astrocytomas, co-deletion of 1p/19q in oligodendrogliomas, and mutations in IDH1 or IDH2 genes (Staedtke et al. 2016). There remains significant potential for identifying new clinical biomarkers in gliomas. Clinical investigators at Georgetown University are seeking to advance precision medicine techniques for the prognosis and treatment of brain tumors through the identification of novel multi-omics biomarkers. In support of this goal, precisionFDA and the Georgetown Lombardi Comprehensive Cancer Center and ...","","https://precision.fda.gov/challenges/8/","completed","6","","2019-11-01","2020-02-14","2023-06-23 00:00:00","2023-10-14 05:39:25" +"87","gaining-new-insights-by-detecting-adverse-event-anomalies","Gaining New Insights by Detecting Adverse Event Anomalies","Seeking algorithms to detect adverse events in FDA data","The Food and Drug Administration (FDA) calls on the public to develop computational algorithms for automatic detection of adverse event anomalies using publicly available data.","","https://precision.fda.gov/challenges/9/","completed","6","","2020-01-17","2020-05-18","2023-06-23 00:00:00","2023-10-14 05:39:27" +"88","calling-variants-in-difficult-to-map-regions","Calling Variants in Difficult-to-Map Regions","Precision benchmarking: evaluating variant calling in complex genomic regions","This challenge calls on the public to assess variant calling pipeline performance on a common frame of reference, with a focus on benchmarking in difficult-to-map regions, segmental duplications, and the Major Histocompatibility Complex (MHC).","","https://precision.fda.gov/challenges/10/","completed","6","https://doi.org/10.1016/j.xgen.2022.100129","2020-05-01","2020-06-15","2023-06-23 00:00:00","2023-10-14 05:39:28" +"89","vha-innovation-ecosystem-and-covid-19-risk-factor-modeling","VHA Innovation Ecosystem and COVID-19 Risk Factor Modeling","AI for COVID-19: predicting health outcomes in the veteran population","The novel coronavirus disease 2019 (COVID-19) is a respiratory disease caused by a new type of coronavirus, known as “severe acute respiratory syndrome coronavirus 2,” or SARS-CoV-2. On March 11, 2020, the World Health Organization (WHO) declared the outbreak a global pandemic. As of Monday, June 1, the Johns Hopkins University COVID-19 dashboard reports over 6.21 million total confirmed cases worldwide, including over 1.79 million cases in the United States. Although most people have mild to moderate symptoms, the disease can cause severe medical complications leading to death in some people. The Centers for Disease Control and Prevention (CDC) have identified several groups at elevated risk for severe illness, including people 65 years and older, individuals living in nursing homes or long term care facilities, and those with serious underlying medical conditions, such as severe obesity, diabetes, chronic lung disease or moderate to severe asthma, chronic kidney or liver disease...","","https://precision.fda.gov/challenges/11/","completed","6","","2020-06-02","2020-07-03","2023-06-23 00:00:00","2023-10-14 05:39:28" +"90","covid-19-precision-immunology-app-a-thon","COVID-19 Precision Immunology App-a-thon","Seeking insights on COVID-19 pathophysiology to enable effective strategies","The novel coronavirus disease 2019 (COVID-19), a respiratory disease caused by a new type of coronavirus, known as “severe acute respiratory syndrome coronavirus 2” or SARS-CoV-2, was declared a global pandemic by the World Health Organization on March 11, 2020. To date, the Johns Hopkins University COVID-19 dashboard reports over 62 million confirmed cases worldwide, with a wide range of disease severity from asymptomatic to deaths (over 1.46 million). To effectively combat the widespread transmission of COVID-19 infection and save lives especially of those vulnerable individuals, it is imperative to better understand its pathophysiology to enable effective diagnosis, prognosis and treatment strategies using rapidly shared data.","","https://precision.fda.gov/challenges/12/","completed","6","","2020-11-30","2021-01-29","2023-06-23 00:00:00","2023-10-14 05:39:29" +"91","smarter-food-safety-low-cost-tech-enabled-traceability","Smarter Food Safety Low Cost Tech-Enabled Traceability","Seeking affordable tech solutions for food traceability","The motivation is tapping into new technologies and integrating data streams will help to advance the widespread, consistent implementation of traceability systems across the food industry. However, the affordability of such technologies, particularly for smaller companies, can be a barrier to implementing tech-enabled traceability systems. FDA's New Era of Smarter Food Safety initiative strives to work with stakeholders to explore low-cost or no-cost options so that our approaches are inclusive of and viable for human and animal food operations of all sizes. Democratizing the benefits of digitizing data will allow the entire food system to move more rapidly towards digital traceability systems. The primary goal is to encourage stakeholders, including technology providers, public health advocates, entrepreneurs, and innovators from all disciplines and around the world, to develop traceability hardware, software, or data analytics platforms that are low-cost or no-cost to the en...","","https://precision.fda.gov/challenges/13","completed","6","","2021-06-01","2021-07-30","2023-06-23 00:00:00","2023-10-17 23:05:49" +"92","tumor-mutational-burden-tmb-challenge-phase-1","Tumor Mutational Burden (TMB) Challenge Phase 1","Standardize tumor mutational burden (TMB) calculation in cancer research","Tumor mutational burden (TMB) is generally defined as the number of mutations detected in a patient's tumor sample per megabase of DNA sequenced. However different algorithms use different methods for calculating TMB. Mutations in genes in tumor cells may lead to the creation of neoantigens, which have the potential to activate an immune system response against the tumor, and the likelihood of an immune system response may increase with the number of mutations. Thus, TMB is a biomarker for some immunotherapy drugs, called immune checkpoint inhibitors, such as those that target the PD-1 and PD-L1 pathways (Chan et al., 2019). An outstanding problem is the lack of standardization for TMB calculation and reporting between different assays. To address this problem, the Friends of Cancer Research convened a working group of industry and regulatory stakeholders to develop guidance and tools for TMB harmonization. Results from the first phase of this effort were presented at AACR 2020 (...","","https://precision.fda.gov/challenges/17","completed","6","","2021-06-21","2021-09-13","2023-06-23 00:00:00","2023-11-02 18:28:46" +"93","kits21","KiTS21","Contest seeks best kidney tumor segmentation system","The 2021 Kidney and Kidney Tumor Segmentation challenge (abbreviated KiTS21) is a competition in which teams compete to develop the best system for automatic semantic segmentation of renal tumors and surrounding anatomy. Kidney cancer is one of the most common malignancies in adults around the world, and its incidence is thought to be increasing [1]. Fortunately, most kidney tumors are discovered early while they're still localized and operable. However, there are important questions concerning management of localized kidney tumors that remain unanswered [2], and metastatic renal cancer remains almost uniformly fatal [3]. Kidney tumors are notorious for their conspicuous appearance in computed tomography (CT) imaging, and this has enabled important work by radiologists and surgeons to study the relationship between tumor size, shape, and appearance and its prospects for treatment [4,5,6]. It's laborious work, however, and it relies on assessments that are often subjective and impr...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/594/rendering_dimmed.png","https://kits21.grand-challenge.org/","completed","5","","2021-08-23","2021-09-17","2023-06-23 00:00:00","2023-11-28 00:29:34" +"94","realnoisemri","RealNoiseMRI","Brain MRI reconstruction challenge with realistic noise","In recent years, there is a growing focus on the application of fast magnetic resonance imaging (MRI) based on prior knowledge. In the 1980s and 2000s the community used either purely mathematical models such as the partial Fourier transform or solutions derived through advanced engineering such as parallel imaging to speed up MRI acquisition. Since the mid-2000's, compressed sensing and artificial intelligence have been employed to speed up MRI acquisition. These newer methods rely on under sampling the data acquired in Fourier (aka k-) space and then interpolating or augmenting k-space data based on training data content. One of the underlying problems for the development of fast imaging techniques, that just as in e.g. [1], it is common to use a fully sampled image as ground truth and then under sample it in k-space in order to simulate under sampled data. The problem with this approach is that in cases were the under sampled data is corrupted, through e.g. motion, this under s...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/597/Logo_Challenge.png","https://realnoisemri.grand-challenge.org/","completed","5","","2021-09-21","2021-12-06","2023-06-23 00:00:00","2023-11-27 20:40:05" +"95","deep-generative-model-challenge-for-da-in-surgery","Deep Generative Model Challenge for DA in Surgery","Challenge aims to adapt algorithms from simulation to mitral valve surgery","Mitral regurgitation (MR) is the second most frequent indication for valve surgery in Europe and may occur for organic or functional causes [1]. Mitral valve repair, although considerably more difficult, is prefered over mitral valve replacement, since the native tissue of the valve is preserved. It is a complex on-pump heart surgery, often conducted only by a handful of surgeons in high-volume centers. Minimally invasive procedures, which are performed with endoscopic video recordings, became more and more popular in recent years. However, data availability and data privacy concerns are still an issue for the development of automatic scene analysis algorithms. The AdaptOR challenge aims to address these issues by formulating a domain adaptation problem from simulation to surgery. We provide a smaller number of datasets from real surgeries, and a larger number of annotated recordings of training and planning sessions from a physical mitral valve simulator. The goal is to reduce th...","","https://adaptor2021.github.io/","completed","1","","2021-04-01","2021-07-16","2023-06-23 00:00:00","2023-10-14 05:39:34" +"96","aimdatathon","AIM Datathon 2020","AI in Medicine (AIM) Datathon 2020","Join the AI in Medicine ( AIM ) Datathon 2020","","https://www.kaggle.com/competitions/aimdatathon","completed","8","","2020-11-09","2020-11-22","2023-06-23 00:00:00","2023-11-15 22:43:19" +"97","opc-recurrence","Oropharynx Cancer (OPC) Radiomics Challenge :: Local Recurrence Prediction","Determine whether a tumor will be controlled by definitive radiation therapy","Determine from CT data whether a tumor will be controlled by definitive radiation therapy.","","https://www.kaggle.com/competitions/opc-recurrence","completed","8","","2016-07-26","2016-09-12","2023-06-23 00:00:00","2023-11-14 19:11:07" +"98","oropharynx-radiomics-hpv","Oropharynx Cancer (OPC) Radiomics Challenge :: Human Papilloma Virus (HPV) Status Prediction","Predict hpv phenotype of oropharynx tumors; compare to ground truth data","Predict from CT data the HPV phenotype of oropharynx tumors; compare to ground-truth results previously obtained by p16 or HPV testing.","","https://www.kaggle.com/competitions/oropharynx-radiomics-hpv","completed","8","","2016-07-26","2016-09-12","2023-06-23 00:00:00","2023-11-14 19:11:17" +"99","data-science-bowl-2017","Data Science Bowl 2017","Can you improve lung cancer detection?","Can you improve lung cancer detection?","","https://www.kaggle.com/competitions/data-science-bowl-2017","completed","8","","2017-01-12","2017-04-12","2023-06-23 00:00:00","2023-10-14 05:39:38" +"100","predict-impact-of-air-quality-on-death-rates","Predict impact of air quality on mortality rates","Predict CVD and cancer caused mortality rates in England using air quality data","Predict CVD and cancer caused mortality rates in England using air quality data available from Copernicus Atmosphere Monitoring Service","","https://www.kaggle.com/competitions/predict-impact-of-air-quality-on-death-rates","completed","8","","2017-02-13","2017-05-05","2023-06-23 00:00:00","2023-10-14 05:39:38" +"101","intel-mobileodt-cervical-cancer-screening","Intel & MobileODT Cervical Cancer Screening","Which cancer treatment will be most effective?","Which cancer treatment will be most effective?","","https://www.kaggle.com/competitions/intel-mobileodt-cervical-cancer-screening","completed","8","","2017-03-15","2017-06-21","2023-06-23 00:00:00","2023-10-14 05:39:39" +"102","msk-redefining-cancer-treatment","Personalized Medicine-Redefining Cancer Treatment","Predict the effect of genetic variants to enable personalized medicine","Predict the effect of Genetic Variants to enable Personalized Medicine","","https://www.kaggle.com/competitions/msk-redefining-cancer-treatment","completed","8","","2017-06-26","2017-10-02","2023-06-23 00:00:00","2023-11-02 18:32:51" +"103","mubravo","Predicting Cancer Diagnosis","Bravo's machine learning competition!","Bravo's machine learning competition!","","https://www.kaggle.com/competitions/mubravo","completed","8","","2018-07-31","2018-08-13","2023-06-23 00:00:00","2023-10-14 05:39:41" +"104","histopathologic-cancer-detection","Histopathologic Cancer Detection","Identify metastatic tissue in histopathologic scans of lymph node sections","Identify metastatic tissue in histopathologic scans of lymph node sections","","https://www.kaggle.com/competitions/histopathologic-cancer-detection","completed","8","","2018-11-16","2019-03-30","2023-06-23 00:00:00","2023-10-14 05:39:41" +"105","tjml1920-decision-trees","TJML 2019-20 Breast Cancer Detection Competition","Use a decision tree to identify malignant breast cancer tumors","Use a decision tree to identify malignant breast cancer tumors","","https://www.kaggle.com/competitions/tjml1920-decision-trees","completed","8","","2019-09-22","2019-10-16","2023-06-23 00:00:00","2023-10-14 05:39:42" +"106","prostate-cancer-grade-assessment","Prostate cANcer graDe Assessment (PANDA) Challenge","Prostate cancer diagnosis using the gleason grading system","Prostate cancer diagnosis using the Gleason grading system","","https://www.kaggle.com/competitions/prostate-cancer-grade-assessment","completed","8","","2020-04-21","2020-07-22","2023-06-23 00:00:00","2023-10-14 05:39:43" +"107","breast-cancer","Breast Cancer","Use cell nuclei categories to predict breast cancer tumor","Use cell nuclei categories to predict breast cancer tumor.","","https://www.kaggle.com/competitions/breast-cancer","completed","8","","2020-08-12","2020-08-13","2023-06-23 00:00:00","2023-10-14 05:39:43" +"108","breast-cancer-detection","Breast Cancer Detection","Breast cancer detection","breast cancer detection","","https://www.kaggle.com/competitions/breast-cancer-detection","completed","8","","2020-09-25","2020-12-31","2023-06-23 00:00:00","2023-10-14 05:39:44" +"109","hrpred","Prediction of High Risk Patients","Classification of high and low risk cancer patients","Classification of high and low risk cancer patients","","https://www.kaggle.com/competitions/hrpred","completed","8","","2020-11-25","2020-12-05","2023-06-23 00:00:00","2023-10-14 05:39:44" +"110","ml4moleng-cancer","MIT ML4MolEng-Predicting Cancer Progression","MIT 3.100, 10.402, 20.301 In class ML competition (Spring 2021)","MIT 3.100, 10.402, 20.301 In class ML competition (Spring 2021)","","https://www.kaggle.com/competitions/ml4moleng-cancer","completed","8","","2021-05-06","2021-05-21","2023-06-23 00:00:00","2023-11-16 18:41:14" +"111","uw-madison-gi-tract-image-segmentation","UW-Madison GI Tract Image Segmentation","Track healthy organs in medical scans to improve cancer treatment","Track healthy organs in medical scans to improve cancer treatment","","https://www.kaggle.com/competitions/uw-madison-gi-tract-image-segmentation","completed","8","","2022-04-14","2022-07-14","2023-06-23 00:00:00","2023-10-14 05:39:46" +"112","rsna-miccai-brain-tumor-radiogenomic-classification","RSNA-MICCAI Brain Tumor Radiogenomic Classification","Predict the status of a genetic biomarker important for brain cancer treatment","The Brain Tumor Segmentation (BraTS) challenge celebrates its 10th anniversary, and this year is jointly organized by the Radiological Society of North America (RSNA), the American Society of Neuroradiology (ASNR), and the Medical Image Computing and Computer Assisted Interventions (MICCAI) society. The RSNA-ASNR-MICCAI BraTS 2021 challenge utilizes multi-institutional pre-operative baseline multi-parametric magnetic resonance imaging (mpMRI) scans, and focuses on the evaluation of state-of-the-art methods for (Task 1) the segmentation of intrinsically heterogeneous brain glioblastoma sub-regions in mpMRI scans. Furthemore, this BraTS 2021 challenge also focuses on the evaluation of (Task 2) classification methods to predict the MGMT promoter methylation status. Participants are free to choose whether they want to focus only on one or both tasks.","","https://www.kaggle.com/competitions/rsna-miccai-brain-tumor-radiogenomic-classification","completed","8","","2021-07-13","2021-10-15","2023-06-23 00:00:00","2023-10-14 05:39:46" +"113","breastcancer","Breast Cancer - Beginners ML","Beginners hands-on experience with ML basics","Beginners hands-on experience with ML basics","","https://www.kaggle.com/competitions/breastcancer","completed","8","","2021-12-21","2022-02-12","2023-06-23 00:00:00","2023-10-18 21:18:15" +"114","ml-olympiad-health-and-education","ML Olympiad -Let's Fight lung cancer","Use your ml expertise to help us step another step toward defeating cancer","Use your ML expertise to help us step another step toward defeating cancer [ Starts on the 14th February ]","","https://www.kaggle.com/competitions/ml-olympiad-health-and-education","completed","8","","2022-01-31","2022-03-19","2023-06-23 00:00:00","2023-11-15 18:45:55" +"115","cs98-22-dl-task1","CS98X-22-DL-Task1","This competition is related to task 1 in coursework-breast cancer classification","This competition is related to Task 1 in coursework-breast cancer classification","","https://www.kaggle.com/competitions/CS98-22-DL-Task1","completed","8","","2022-02-28","2022-04-11","2023-06-23 00:00:00","2023-10-14 05:39:48" +"116","parasitedetection-iiitb2019","Parasite detection","Detect if cell image has parasite or is uninfected","detect if cell image has parasite or is uninfected","","https://www.kaggle.com/competitions/parasitedetection-iiitb2019","completed","8","","2019-10-13","2019-11-25","2023-06-23 00:00:00","2023-10-14 05:39:49" +"117","hpa-single-cell-image-classification","Human Protein Atlas -Single Cell Classification","Find individual human cell differences in microscope images","Find individual human cell differences in microscope images","","https://www.kaggle.com/competitions/hpa-single-cell-image-classification","completed","8","","2021-01-26","2021-05-11","2023-06-23 00:00:00","2023-10-14 05:39:50" +"118","stem-cell-predcition","Stem Cell Predcition","Classify stem and non-stem cells using RNA-seq data","Classify stem and non-stem cells using RNA-seq data","","https://www.kaggle.com/competitions/stem-cell-predcition","completed","8","","2021-04-01","2021-07-01","2023-06-23 00:00:00","2023-10-14 05:39:50" +"119","sartorius-cell-instance-segmentation","Sartorius - Cell Instance Segmentation","Detect single neuronal cells in microscopy images","In this competition, you’ll detect and delineate distinct objects of interest in biological images depicting neuronal cell types commonly used in the study of neurological disorders. More specifically, you'll use phase contrast microscopy images to train and test your model for instance segmentation of neuronal cells. Successful models will do this with a high level of accuracy. If successful, you'll help further research in neurobiology thanks to the collection of robust quantitative data. Researchers may be able to use this to more easily measure the effects of disease and treatment conditions on neuronal cells. As a result, new drugs could be discovered to treat the millions of people with these leading causes of death and disability.","","https://www.kaggle.com/competitions/sartorius-cell-instance-segmentation","completed","8","","2021-10-14","2021-12-30","2023-06-23 00:00:00","2023-10-16 18:05:17" +"120","pvelad","Photovoltaic cell anomaly detection","Photovoltaic cell anomaly detection","Hosted by Hebei University of Technology (AIHebut research group) and Beihang University (NAVE research group)","","https://www.kaggle.com/competitions/pvelad","completed","8","","2022-03-15","2022-07-30","2023-06-23 00:00:00","2023-10-14 05:39:51" +"121","blood-mnist","Blood-MNIST","Classifying blood cell types using weights and biases","Classifying blood cell types using Weights and Biases","","https://www.kaggle.com/competitions/blood-mnist","completed","8","","2022-03-19","2022-03-19","2023-06-23 00:00:00","2023-11-14 20:33:37" +"122","insilicomolhack","MolHack","Apply deep learning to speedup drug validation","Apply deep learning to speedup drug validation","","https://www.kaggle.com/competitions/insilicomolhack","completed","8","","2018-04-02","2018-05-25","2023-06-23 00:00:00","2023-10-14 05:39:53" +"123","codata2019challenge","Cell Response Classification","From recorded timeseries of many cells in a well, predict which drug treatme","From recorded timeseries of many cells in a well, predict which drug treatment has been applied","","https://www.kaggle.com/competitions/codata2019challenge","completed","8","","2019-04-08","2019-05-07","2023-06-23 00:00:00","2023-10-14 05:39:53" +"124","drug-solubility-challenge","Drug solubility challenge","Crucial role of solubility in drug formulation for optimal efficacy","Solubility is vital to achieve desired concentration of drug for anticipated pharmacological response.","","https://www.kaggle.com/competitions/drug-solubility-challenge","completed","8","","2019-05-18","2019-10-18","2023-06-23 00:00:00","2023-10-14 05:39:54" +"125","kinase-inhibition-challenge","Kinase inhibition challenge","Unlocking the therapeutic potential of protein kinases: big data insights","Protein kinases have become a major class of drug targets, accumulating a huge amount of data","","https://www.kaggle.com/competitions/kinase-inhibition-challenge","completed","8","","2019-05-20","2019-12-28","2023-06-23 00:00:00","2023-10-14 05:39:54" +"126","ai-drug-discovery","AI Drug Discovery Workshop and Coding Challenge","Fostering core AI programming proficiency for drug discovery advancements","Developing Fundamental AI Programming Skills for Drug Discovery","","https://www.kaggle.com/competitions/ai-drug-discovery","completed","8","","2021-11-12","2021-12-31","2023-06-23 00:00:00","2023-11-02 18:41:48" +"127","protein-compound-affinity","Structure-free protein-ligand affinity prediction - Task 1 Fitting","Developing new AI models for drug discovery","Developing new AI models for drug discovery, main portal (Task-1 fitting)","","https://www.kaggle.com/competitions/protein-compound-affinity","completed","8","","2021-12-06","2021-12-31","2023-06-23 00:00:00","2023-11-14 20:34:30" +"128","cisc873-dm-f21-a5","CISC873-DM-F21-A5","Anti-cancer drug activity prediction","Anti-Cancer Drug Activity Prediction","","https://www.kaggle.com/competitions/cisc873-dm-f21-a5","completed","8","","2021-11-26","2021-12-10","2023-06-23 00:00:00","2023-10-14 05:39:56" +"129","pro-lig-aff-task2-mse","Structure-free protein-ligand affinity prediction - Task 2 Fitting","Developing new AI models for drug discovery","Developing new AI models for drug discovery (Task-2 fitting)","","https://www.kaggle.com/competitions/pro-lig-aff-task2-mse","completed","8","","2021-12-08","2021-12-31","2023-06-23 00:00:00","2023-11-15 22:42:37" +"130","pro-lig-aff-task1-pearsonr","Structure-free protein-ligand affinity prediction - Task 1 Ranking","Developing new AI models for drug discovery","Developing new AI models for drug discovery (Task-1 ranking)","","https://www.kaggle.com/competitions/pro-lig-aff-task1-pearsonr","completed","8","","2021-12-08","2021-12-31","2023-06-23 00:00:00","2023-11-15 22:42:40" +"131","pro-lig-aff-task2-pearsonr","Structure-free protein-ligand affinity prediction - Task 2 Ranking","Developing new AI models for drug discovery","Developing new AI models for drug discovery (Task-2 ranking)","","https://www.kaggle.com/competitions/pro-lig-aff-task2-pearsonr","completed","8","","2021-12-08","2021-12-31","2023-06-23 00:00:00","2023-11-15 22:42:43" +"132","pro-lig-aff-task3-spearmanr","Structure-free protein-ligand affinity prediction - Task 3 Ranking","Developing new AI models for drug discovery","Developing new AI models for drug discovery (Task-3 ranking)","","https://www.kaggle.com/competitions/pro-lig-aff-task3-spearmanr","completed","8","","2021-12-08","2021-12-31","2023-06-23 00:00:00","2023-11-15 22:42:44" +"133","hhp","Heritage Health Prize","Identify patients who will be admitted to a hospital within the next year","Identify patients who will be admitted to a hospital within the next year using historical claims data. (Enter by 06-59-59 UTC Oct 4 2012)","","https://www.kaggle.com/competitions/hhp","completed","8","","2011-04-04","2013-04-04","2023-06-23 00:00:00","2023-11-14 19:11:25" +"134","pf2012","Practice Fusion Analyze This! 2012 - Prediction Challenge","Propose innovative predictive modeling challenges","Start digging into electronic health records and submit your ideas for the most promising, impactful or interesting predictive modeling competitions","","https://www.kaggle.com/competitions/pf2012","completed","8","","2012-06-07","2012-06-30","2023-06-23 00:00:00","2023-11-14 19:11:32" +"135","pf2012-at","Practice Fusion Analyze This! 2012 - Open Challenge","Propose innovative predictive modeling challenges","Start digging into electronic health records and submit your creative, insightful, and visually striking analyses.","","https://www.kaggle.com/competitions/pf2012-at","completed","8","","2012-06-07","2012-09-10","2023-06-23 00:00:00","2023-11-14 19:21:00" +"136","seizure-detection","UPenn and Mayo Clinic's Seizure Detection Challenge","Detect seizures in intracranial EEG recordings","Detect seizures in intracranial EEG recordings","","https://www.kaggle.com/competitions/seizure-detection","completed","8","","2014-05-19","2014-08-19","2023-06-23 00:00:00","2023-10-14 05:40:02" +"137","seizure-prediction","American Epilepsy Society Seizure Prediction Challenge","Predict seizures in intracranial EEG recordings","Predict seizures in intracranial EEG recordings","","https://www.kaggle.com/competitions/seizure-prediction","completed","8","","2014-08-25","2014-11-17","2023-06-23 00:00:00","2023-10-14 05:40:03" +"138","deephealth-1","Deep Health - alcohol","Find correlations and patterns with medical data","Find Correlations and patterns with Medical data","","https://www.kaggle.com/competitions/deephealth-1","completed","8","","2017-02-13","2017-02-19","2023-06-23 00:00:00","2023-10-16 18:14:48" +"139","deep-health-3","Deep Health - Diabetes 2","Deep health hackathon: predicting future diabetes occurrences challenge","This competition is for those attending the Deep Health Hackathon. Predict the next occurrence of diabetes","","https://www.kaggle.com/competitions/deep-health-3","completed","8","","2017-02-15","2017-02-19","2023-06-23 00:00:00","2023-10-16 18:14:50" +"140","d012554-2021","D012554 - 2021","Classify the health of a fetus using CTG data","Classify the health of a fetus using CTG data","","https://www.kaggle.com/competitions/d012554-2021","completed","8","","2021-04-11","2021-05-09","2023-06-23 00:00:00","2023-10-16 18:15:04" +"141","idao-2022-bootcamp-insomnia","IDAO 2022. ML Bootcamp - Insomnia","Predict sleep disorder on given human health data","Predict sleep disorder on given human health data","","https://www.kaggle.com/competitions/idao-2022-bootcamp-insomnia","completed","8","","2021-12-04","2021-12-05","2023-06-23 00:00:00","2023-10-16 18:15:12" +"142","tweet-mental-health-classification","Tweet Mental Health Classification","Build models to classify tweets to determine mental health","Build Models to classify tweets to determine mental health","","https://www.kaggle.com/competitions/tweet-mental-health-classification","completed","8","","2021-12-27","2022-01-31","2023-06-23 00:00:00","2023-10-14 05:40:07" +"143","ml-olympiad-good-health-and-well-being","ML Olympiad - GOOD HEALTH AND WELL BEING","Use your ML expertise to classify if a patient has heart disease or not","Use your ML expertise to classify if a patient has heart disease or not","","https://www.kaggle.com/competitions/ml-olympiad-good-health-and-well-being","completed","8","","2022-02-03","2022-03-01","2023-06-23 00:00:00","2023-10-16 18:15:20" +"144","rsna-breast-cancer-detection","RSNA Screening Mammography Breast Cancer Detection","Find breast cancers in screening mammograms","Find breast cancers in screening mammograms","","https://www.kaggle.com/competitions/rsna-breast-cancer-detection","completed","8","","2022-11-28","2023-02-27","2023-06-23 00:00:00","2023-10-14 05:40:12" +"145","biocreative-vii-text-mining-drug-and-chemical-protein-interactions-drugprot","BioCreative VII: Text mining drug and chemical-protein interactions (DrugProt)","Develop systems to extract drug-gene relations from text","With the rapid accumulation of biomedical literature, it is getting increasingly challenging to exploit efficiently drug-related information described in the scientific literature. One of the most relevant aspects of drugs and chemical compounds are their relationships with certain biomedical entities, in particular genes and proteins. The aim of the DrugProt track (similar to the previous CHEMPROT task of BioCreative VI) is to promote the development and evaluation of systems that are able to automatically detect in relations between chemical compounds/drug and genes/proteins. There are a range of different types of drug-gene/protein interactions, and their systematic extraction and characterization is essential to analyze, predict and explore key biomedical properties underlying high impact biomedical applications. These application scenarios include use cases related to drug discovery, drug repurposing, drug design, metabolic engineering, modeling drug response, pharmacogenet...","","https://biocreative.bioinformatics.udel.edu/tasks/biocreative-vii/track-1/","completed","14","","2021-06-15","2021-09-22","2023-06-23 00:00:00","2023-11-01 20:37:37" +"146","extended-literature-ai-for-drug-induced-liver-injury","Extended Literature AI for Drug Induced Liver Injury","Develop ML tools to analyze drug texts for liver injury data","Unexpected Drug-Induced Liver Injury (DILI) still is one of the main killers of promising novel drug candidates. It is a clinically significant disease that can lead to severe outcomes such as acute liver failure and even death. It remains one of the primary liabilities in drug development and regulatory clearance due to the limited performance of mandated preclinical models even today. The free text of scientific publications is still the main medium carrying DILI results from clinical practice or experimental studies. The textual data still has to be analysed manually. This process, however, is tedious and prone to human mistakes or omissions, as results are very rarely available in a standardized form or organized form. There is thus great hope that modern techniques from machine learning or natural language processing could provide powerful tools to better process and derive the underlying knowledge within free form texts. The pressing need to faster process potential drug can...","","http://camda2022.bioinf.jku.at/contest_dataset#extended_literature_ai_for_drug_induced_liver_injury","completed","14","","\N","2022-05-20","2023-06-23 00:00:00","2023-11-01 20:37:38" +"147","anti-microbial-resistance-forensics","Anti-Microbial Resistance Forensics","Classifying bacteriophages to understand microbial evolution","Bacteriophages, being the re-occuring mystery in the history of science are believed to be they key for understanding of microbial evolution and the transfer of AMR genes. Recent studies show that there is a significant correlation between occurence of Phages and AMR genes, indicating that they are indeed taking part in the spread of them. While taking part in AMR dissemination the phages are also considered as the potential alternative to antibiotics. In such contradictory world there is a huge potential as well as urgent need for precise classification, description and analysis of capabilities. Due to pandemic of SARS-CoV-2, advance in phylogenetic algorithms and k-mer based methods have been extremely rapid and those improvements are witing to be adapted to different branches of life sciences.","","http://camda2022.bioinf.jku.at/contest_dataset#anti-microbial_resistance_forensics","completed","14","","\N","2022-05-20","2023-06-23 00:00:00","2023-10-14 05:40:14" +"148","disease-maps-to-modelling-covid-19","Disease Maps to Modelling COVID-19","Suggest drugs candidate for repurposing","The Disease Maps to modeling COVID-19 Challenge provides highly detailed expert-curated molecular mechanistic maps for COVID-19. Combine them with available omic data to expand the current biological knowledge on COVID-19 mechanism of infection and downstream consequences. The main topic for this year's challenge is drug repurposing with the possibility of Real World Data based validation of the most promising candidates suggested.","","http://camda2022.bioinf.jku.at/contest_dataset#disease_maps_to_modelling_covid-19","completed","14","","\N","2022-05-20","2023-06-23 00:00:00","2023-11-14 19:23:47" +"149","crowdsourced-evaluation-of-inchi-based-tautomer-identification","Crowdsourced Evaluation of InChI-based Tautomer Identification","Test a modified InChi algorithm","This challenge focuses on the International Chemical Identifier (InChI), which was developed and is maintained under the auspices of the International Union of Pure and Applied Chemistry (IUPAC) and the InChI Trust. The InChI Trust, the IUPAC Working Group on Tautomers, and the U.S. Food and Drug Administration (FDA) call on the scientific community dealing with chemical repositories/data sets and analytics of compounds to test the recently modified InChI algorithm, which was designed for advanced recognition of tautomers. Participants will evaluate this algorithm against real chemical samples in this Crowdsourced Evaluation of InChI-based Tautomer Identification.","","https://precision.fda.gov/challenges/29","completed","6","","2022-11-01","2023-03-01","2023-06-23 00:00:00","2023-11-14 19:21:10" +"150","nctr-indel-calling-from-oncopanel-sequencing-challenge-phase-2","NCTR Indel Calling from Oncopanel Sequencing Challenge Phase 2","Calling from oncopanel sequencing data","The high value of clinically actionable information obtained by oncopanel sequencing makes it a crucial tool for precision oncology[1,2]. With the surge in availability of oncopanels, it is critical to ensure that they have been thoroughly tested and are properly used. FDA has initiated the Sequencing Quality Control phase II (SEQC2) project[3] to develop standard analysis protocols and quality control metrics for fit-for-purpose use of Next Generation Sequencing (NGS) data including oncopanel sequencing to inform regulatory science research and precision medicine. The Oncopanel Sequencing Working Group of FDA-led SEQC2 has developed a reference sample[4] suitable for benchmarking oncopanels and comprehensively assessed the analytical performance of several oncopanels[1,2]. The genomic deoxyribonucleic acid (gDNA) reference sample was derived from ten Universal Human Reference RNA (UHRR, Agilent Technologies, Inc) cell-lines and made publicly available by Agilent. Substantial gen...","","https://precision.fda.gov/challenges/22","completed","6","","2022-07-11","2022-07-26","2023-06-23 00:00:00","2023-11-15 22:53:48" +"151","nctr-indel-calling-from-oncopanel-sequencing-data-challenge-phase-1","NCTR Indel Calling from Oncopanel Sequencing Data Challenge Phase 1","Identify indels in oncopanel sequencing datasets","The high value of clinically actionable information obtained by oncopanel sequencing makes it a crucial tool for precision oncology[1,2]. With the surge in availability of oncopanels, it is critical to ensure that they have been thoroughly tested and are properly used. FDA has initiated the Sequencing Quality Control phase II (SEQC2) project[3] to develop standard analysis protocols and quality control metrics for fit-for-purpose use of Next Generation Sequencing (NGS) data including oncopanel sequencing to inform regulatory science research and precision medicine. The Oncopanel Sequencing Working Group of FDA-led SEQC2 has developed a reference sample[4] suitable for benchmarking oncopanels and comprehensively assessed the analytical performance of several oncopanels[1,2]. The genomic deoxyribonucleic acid (gDNA) reference sample was derived from ten Universal Human Reference RNA (UHRR, Agilent Technologies, Inc) cell-lines and made publicly available by Agilent. Substantial gen...","","https://precision.fda.gov/challenges/21","completed","6","","2022-05-02","2022-07-08","2023-06-23 00:00:00","2023-11-14 19:24:33" +"152","vha-innovation-ecosystem-and-precisionfda-covid-19-risk-factor-modeling-challenge-phase-2","VHA Innovation Ecosystem and precisionFDA COVID-19 Risk Factor Modeling Challenge Phase 2","Validate the top performing models on two additional VA sites' data","The novel coronavirus disease 2019 (COVID-19) is a respiratory disease caused by a new type of coronavirus, known as “severe acute respiratory syndrome coronavirus 2,” or SARS-CoV-2. On March 11, 2020, the World Health Organization (WHO) declared the outbreak a global pandemic. As of January 22nd, 2022, the Johns Hopkins University COVID-19 dashboard reports over 338 million total confirmed cases worldwide. Although most people have mild to moderate symptoms, the disease can cause severe medical complications leading to death in some people. The Centers for Disease Control and Prevention (CDC) have identified several risk factors for severe COVID-19 illness, including people 65 years and older, individuals living in nursing homes or long-term care facilities, and those with serious underlying medical conditions. The Veteran population has a higher prevalence of several of the known risk factors for severe COVID-19 illness, such as advanced age, heart disease, and diabetes. Identif...","","https://precision.fda.gov/challenges/20","completed","6","","2021-04-14","2022-01-28","2023-06-23 00:00:00","2023-11-14 19:24:37" +"153","tumor-mutational-burden-tmb-challenge-phase-2","Tumor Mutational Burden (TMB) Challenge Phase 2","Evaluating various computational pipelines for TMB estimation","Tumor mutational burden (TMB) is generally defined as the number of mutations detected in a patient's tumor sample per megabase of DNA sequenced. However different algorithms use different methods for calculating TMB. Mutations in genes in tumor cells may lead to the creation of neoantigens, which have the potential to activate an immune system response against the tumor, and the likelihood of an immune system response may increase with the number of mutations. Thus, TMB is a biomarker for some immunotherapy drugs, called immune checkpoint inhibitors, such as those that target the PD-1 and PD-L1 pathways (Chan et al., 2019). An outstanding problem is the lack of standardization for TMB calculation and reporting between different assays. To address this problem, the Friends of Cancer Research convened a working group of industry and regulatory stakeholders to develop guidance and tools for TMB harmonization. Results from the first phase of this effort were presented at AACR 2020 (s...","","https://precision.fda.gov/challenges/18","completed","6","","2021-07-19","2021-09-12","2023-06-23 00:00:00","2023-11-14 19:24:44" +"154","predicting-gene-expression-using-millions-of-random-promoter-sequences","Predicting Gene Expression Using Millions of Random Promoter Sequences","Decoding gene expression regulation to understand disease","Decoding how gene expression is regulated is critical to understanding disease. Regulatory DNA is decoded by the cell in a process termed “cis-regulatory logic”, where proteins called Transcription Factors (TFs) bind to specific DNA sequences within the genome and work together to produce as output a level of gene expression for downstream adjacent genes. This process is exceedingly complex to model as a large number of parameters is needed to fully describe the process (see Rationale, de Boer et al. 2020; Zeitingler J. 2020). Understanding the cis-regulatory logic of the human genome is an important goal and would provide insight into the origins of many diseases. However, learning models from human data is challenging due to limitations in the diversity of sequences present within the human genome (e.g. extensive repetitive DNA), the vast number of cell types that differ in how they interpret regulatory DNA, limited reporter assay data, and substantial technical biases present i...","","https://www.synapse.org/#!Synapse:syn28469146/wiki/617075","completed","1","","2022-06-15","2022-08-07","2023-06-23 00:00:00","2023-10-14 05:40:21" +"155","brats-2023","BraTS 2023","Benchmarking brain tumor segmentation with expanded dataset","The International Brain Tumor Segmentation (BraTS) challenge. BraTS, since 2012, has focused on the generation of a benchmarking environment and dataset for the delineation of adult brain gliomas. The focus of this year’s challenge remains the generation of a common benchmarking environment, but its dataset is substantially expanded to ~4,500 cases towards addressing additional i) populations (e.g., sub-Saharan Africa patients), ii) tumors (e.g., meningioma), iii) clinical concerns (e.g., missing data), and iv) technical considerations (e.g., augmentations). Specifically, the focus of BraTS 2023 is to identify the current state-of-the-art algorithms for addressing (Task 1) the same adult glioma population as in the RSNA-ANSR-MICCAI BraTS challenge, as well as (Task 2) the underserved sub-Saharan African brain glioma patient population, (Task 3) intracranial meningioma, (Task 4) brain metastasis, (Task 5) pediatric brain tumor patients, (Task 6) global & local missing data, (Task 7...","","https://www.synapse.org/brats","completed","1","","2023-06-01","2023-08-25","2023-06-23 00:00:00","2023-10-26 23:20:21" +"156","cagi7","CAGI7","The seventh round of CAGI","There have been six editions of CAGI experiments, held between 2010 and 2022. The seventh round of CAGI is planned to take place over the Summer of 2024.","","https://genomeinterpretation.org/challenges.html","upcoming","1","","\N","\N","2023-08-04 21:47:38","2023-11-20 20:19:08" +"157","casp15","CASP15","Establish the state-of-art in modeling proteins and protein complexes","CASP14 (2020) saw an enormous jump in the accuracy of single protein and domain models such that many are competitive with experiment. That advance is largely the result of the successful application of deep learning methods, particularly by the AlphaFold and, since that CASP, RosettaFold. As a consequence, computed protein structures are becoming much more widely used in a broadening range of applications. CASP has responded to this new landscape with a revised set of modeling categories. Some old categories have been dropped (refinement, contact prediction, and aspects of model accuracy estimation) and new ones have been added (RNA structures, protein ligand complexes, protein ensembles, and accuracy estimation for protein complexes). We are also strengthening our interactions with our partners CAPRI and CAMEO. We hope that these changes will maximize the insight that CASP15 provides, particularly in new applications of deep learning.","","https://predictioncenter.org/casp15/index.cgi","completed","14","","2022-04-18","\N","2023-08-04 21:52:12","2023-09-28 23:09:59" +"158","synthrad2023","SynthRAD2023","Automatic generation of synthetic computed tomography (sCT) for radiotherapy","This challenge aims to provide the first platform offering public data evaluation metrics to compare the latest developments in sCT generation methods. The accepted challenge design approved by MICCAI can be found at https://doi.org/10.5281/zenodo.7746019. A type 2 challenge will be run, where the participant needs to submit their algorithm packaged in a docker both for validation and test.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/678/SynthRAD_square_logo_MnAqldI.png","https://synthrad2023.grand-challenge.org/","completed","5","","2023-04-01","2023-08-22","2023-08-04 21:54:31","2023-11-14 19:24:54" +"159","synthetic-data-for-instrument-segmentation-in-surgery-syn-iss","Synthetic Data for Instrument Segmentation in Surgery (Syn-ISS)","Surgical instrument segmentation with synthetic data","A common limitation noted by the surgical data science community is the size of datasets and the resources needed to generate training data at scale for building reliable and high-performing machine learning models. Beyond unsupervised and self-supervised approaches another solution within the broader machine learning community has been a growing volume of literature in the use of synthetic data (simulation) for training algorithms than can be applied to real world data. Synthetic data has multiple benefits like free groundtruth at large scale, possibility to collect larger sample of rare events, include anatomical variations, etc. A first step towards proving the validity of using synthetic data for real world applications is to demonstrate the feasibility within the simulation world itself. Our proposed challenge is to train machine learning methods for instrument segmentation using synthetic datasets and test their performance on synthetic datasets. That is, the challenge parti...","","https://www.synapse.org/#!Synapse:syn50908388/wiki/620516","completed","1","","2023-07-19","2023-09-07","2023-08-04 23:49:44","2023-11-14 19:25:04" +"160","pitvis","PitVis","Surgical workflow and instrument recognition in endonasal surgery","The pituitary gland, found just off the base of the brain, is commonly known as “the master gland”, performing essential functions required for sustaining human life. Clinically relevant tumours that have grown on the pituitary gland have an estimated prevalence of 1 in 1000 of the population, and if left untreated can be life-limiting. The “gold standard” treatment is endoscopic pituitary surgery, where the tumour is directly removed by entering through a nostril. This surgery is particularly challenging due to the small working space which limits both vision and instrument manoeuvrability and thus can lead to poor surgical technique causing adverse outcomes for the patient. Computer-assisted intervention can help overcome these challenges by providing guidance for senior surgeons and operative staff during surgery, and for junior surgeons during training.","","https://www.synapse.org/#!Synapse:syn51232283/wiki/","completed","1","","2023-06-29","2023-09-10","2023-08-04 23:58:01","2023-10-26 23:20:30" +"161","mvseg2023","MVSEG2023","Single frame 3D trans-esophageal echocardiography","Mitral valve (MV) disease is a common pathologic problem occurring in approximately 2 % of the general population but climbing to 10 % in those over the age of 75. The preferred intervention for mitral regurgitation is valve repair, due to superior patient outcomes compared to those following valve replacement. Mitral valve interventions are technically challenging due to the functional and anatomical complexity of mitral pathologies. Repair must be tailored to the patient-specific anatomy and pathology, which requires considerable expert training and experience. Automatic segmentation of the mitral valve leaflets from 3D transesophageal echocardiography (TEE) may play an important role in treatment planning, as well as physical and computational modelling of patient-specific valve pathologies and potential repair approaches. This may have important implications in the drive towards personalized care and has the potential to impact clinical outcomes for those undergoing mitral val...","","https://www.synapse.org/#!Synapse:syn51186045/wiki/621356","completed","1","","2023-05-29","2023-08-07","2023-08-05 0-04-36","2023-11-14 19:25:13" +"162","crossmoda23","crossMoDA23","Medical imaging benchmark for unsupervised domain adaptation","Domain Adaptation (DA) has recently raised strong interest in the medical imaging community. By encouraging algorithms to be robust to unseen situations or different input data domains, Domain Adaptation improves the applicability of machine learning approaches to various clinical settings. While a large variety of DA techniques has been proposed, most of these techniques have been validated either on private datasets or on small publicly available datasets. Moreover, these datasets mostly address single-class problems. To tackle these limitations, the crossMoDA challenge introduced the first large and multi-class dataset for unsupervised cross-modality Domain Adaptation. From an application perspective, crossMoDA focuses on MRI segmentation for Vestibular Schwannoma. Compared to the previous crossMoDA instance, which made use of multi-institutional data acquired in controlled conditions for radiosurgery planning and focused on a 2 class segmentation task (tumour and cochlea), the...","","https://www.synapse.org/#!Synapse:syn51236108/wiki/621615","completed","1","","2023-04-15","2023-07-10","2023-08-05 0-13-23","2023-11-14 19:27:00" +"163","icr-identify-age-related-conditions","ICR - Identifying Age-Related Conditions","Detect conditions with measurements of anonymous characteristics of a subject","The goal of this competition is to predict if a person has any of three medical conditions. You are being asked to predict if the person has one or more of any of the three medical conditions (Class 1), or none of the three medical conditions (Class 0). You will create a model trained on measurements of health characteristics. To determine if someone has these medical conditions requires a long and intrusive process to collect information from patients. With predictive models, we can shorten this process and keep patient details private by collecting key characteristics relative to the conditions, then encoding these characteristics.","","https://www.kaggle.com/competitions/icr-identify-age-related-conditions","completed","8","","2023-05-11","2023-08-10","2023-08-05 0-32-01","2023-11-14 19:25:37" +"164","cafa-5-protein-function-prediction","CAFA 5: Protein Function Prediction","Predict the biological function of a protein","The goal of this competition is to predict the function of a set of proteins. You will develop a model trained on the amino-acid sequences of the proteins and on other data. Your work will help ​​researchers better understand the function of proteins, which is important for discovering how cells, tissues, and organs work. This may also aid in the development of new drugs and therapies for various diseases.","","https://www.kaggle.com/competitions/cafa-5-protein-function-prediction","completed","8","","2023-04-18","2023-08-21","2023-08-05 5-18-40","2023-10-19 00:13:14" +"165","rsna-2023-abdominal-trauma-detection","RSNA 2023 Abdominal Trauma Detection","Detect and classify traumatic abdominal injuries","Traumatic injury is the most common cause of death in the first four decades of life and a major public health problem around the world. There are estimated to be more than 5 million annual deaths worldwide from traumatic injury. Prompt and accurate diagnosis of traumatic injuries is crucial for initiating appropriate and timely interventions, which can significantly improve patient outcomes and survival rates. Computed tomography (CT) has become an indispensable tool in evaluating patients with suspected abdominal injuries due to its ability to provide detailed cross-sectional images of the abdomen. Interpreting CT scans for abdominal trauma, however, can be a complex and time-consuming task, especially when multiple injuries or areas of subtle active bleeding are present. This challenge seeks to harness the power of artificial intelligence and machine learning to assist medical professionals in rapidly and precisely detecting injuries and grading their severity. The development...","","https://www.kaggle.com/competitions/rsna-2023-abdominal-trauma-detection","completed","8","","2023-07-26","2023-10-13","2023-08-05 5-24-09","2023-09-28 23:14:12" +"166","hubmap-hacking-the-human-vasculature","HuBMAP: Hacking the Human Vasculature","Microvascular structures from healthy human kidney tissue images","The goal of this competition is to segment instances of microvascular structures, including capillaries, arterioles, and venules. You'll create a model trained on 2D PAS-stained histology images from healthy human kidney tissue slides. Your help in automating the segmentation of microvasculature structures will improve researchers' understanding of how the blood vessels are arranged in human tissues.","","https://www.kaggle.com/competitions/hubmap-hacking-the-human-vasculature","completed","8","","2023-05-22","2023-07-31","2023-08-05 5-31-12","2023-11-14 19:25:45" +"167","amp-parkinsons-disease-progression-prediction","AMP(R)-Parkinson's Disease Progression Prediction","Predict clinical and molecular progression of the disease","The goal of this competition is to predict MDS-UPDR scores, which measure progression in patients with Parkinson's disease. The Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) is a comprehensive assessment of both motor and non-motor symptoms associated with Parkinson's. You will develop a model trained on data of protein and peptide levels over time in subjects with Parkinson’s disease versus normal age-matched control subjects. Your work could help provide important breakthrough information about which molecules change as Parkinson’s disease progresses.","","https://www.kaggle.com/competitions/amp-parkinsons-disease-progression-prediction","completed","8","","2023-02-16","2023-05-18","2023-08-05 5-37-12","2023-11-14 19:25:52" +"168","open-problems-multimodal","Open Problems -Multimodal Single-Cell Integration","Predict how DNA, RNA & protein measurements co-vary in single cells","The goal of this competition is to predict how DNA, RNA, and protein measurements co-vary in single cells as bone marrow stem cells develop into more mature blood cells. You will develop a model trained on a subset of 300,000-cell time course dataset of CD34+ hematopoietic stem and progenitor cells (HSPC) from four human donors at five time points generated for this competition by Cellarity, a cell-centric drug creation company. In the test set, taken from an unseen later time point in the dataset, competitors will be provided with one modality and be tasked with predicting a paired modality measured in the same cell. The added challenge of this competition is that the test data will be from a later time point than any time point in the training data. Your work will help accelerate innovation in methods of mapping genetic information across layers of cellular state. If we can predict one modality from another, we may expand our understanding of the rules governing these complex re...","","https://www.kaggle.com/competitions/open-problems-multimodal","completed","8","","2022-08-15","2022-11-15","2023-08-05 5-43-25","2023-10-10 19:52:41" +"169","multi-atlas-labeling-beyond-the-cranial-vault","Multi-Atlas Labeling Beyond the Cranial Vault","Innovative multi-atlas labeling for soft tissue segmentation on clinical CT","Multi-atlas labeling has proven to be an effective paradigm for creating segmentation algorithms from training data. These approaches have been extraordinarily successful for brain and cranial structures (e.g., our prior MICCAI workshops-MLSF’11, MAL’12, SATA’13). After the original challenges closed, the data continue to drive scientific innovation; 144 groups have registered for the 2012 challenge (brain only) and 115 groups for the 2013 challenge (brain/heart/canine leg). However, innovation in application outside of the head and to soft tissues has been more limited. This workshop will provide a snapshot of the current progress in the field through extended discussions and provide researchers an opportunity to characterize their methods on a newly created and released standardized dataset of abdominal anatomy on clinically acquired CT. The datasets will be freely available both during and after the challenge. We have two separate new challenges-abdomen and cervix on routinely ...","","https://www.synapse.org/#!Synapse:syn3193805/wiki/89480","active","1","","2015-04-15","\N","2023-08-07 20:21:22","2023-10-10 19:52:39" +"170","hubmap-organ-segmentation","HuBMAP + HPA: Hacking the Human Body","Segment multi-organ functional tissue units","In this competition, you’ll identify and segment functional tissue units (FTUs) across five human organs. You'll build your model using a dataset of tissue section images, with the best submissions segmenting FTUs as accurately as possible. If successful, you'll help accelerate the world’s understanding of the relationships between cell and tissue organization. With a better idea of the relationship of cells, researchers will have more insight into the function of cells that impact human health. Further, the Human Reference Atlas constructed by HuBMAP will be freely available for use by researchers and pharmaceutical companies alike, potentially improving and prolonging human life.","","https://www.kaggle.com/competitions/hubmap-organ-segmentation","completed","8","","2022-06-22","2022-09-22","2023-08-08 16:30:22","2023-11-02 18:44:27" +"171","hubmap-kidney-segmentation","HuBMAP: Hacking the Kidney","Identify glomeruli in human kidney tissue images","This competition, “Hacking the Kidney, starts by mapping the human kidney at single cell resolution. Your challenge is to detect functional tissue units (FTUs) across different tissue preparation pipelines. An FTU is defined as a “three-dimensional block of cells centered around a capillary, such that each cell in this block is within diffusion distance from any other cell in the same block” ([de Bono, 2013](https://www.ncbi.nlm.nih.gov/pubmed/24103658)). The goal of this competition is the implementation of a successful and robust glomeruli FTU detector. You will also have the opportunity to present your findings to a panel of judges for additional consideration. Successful submissions will construct the tools, resources, and cell atlases needed to determine how the relationships between cells can affect the health of an individual. Advancements in HuBMAP will accelerate the world’s understanding of the relationships between cell and tissue organization and function and human health.","","https://www.kaggle.com/competitions/hubmap-kidney-segmentation","completed","8","","2020-11-16","2021-05-10","2023-08-08 17:31:46","2023-10-12 18:14:16" +"172","ventilator-pressure-prediction","Google Brain: Ventilator Pressure Prediction","Simulate a ventilator connected to a sedated patient's lung","In this competition, you’ll simulate a ventilator connected to a sedated patient's lung. The best submissions will take lung attributes compliance and resistance into account. If successful, you'll help overcome the cost barrier of developing new methods for controlling mechanical ventilators. This will pave the way for algorithms that adapt to patients and reduce the burden on clinicians during these novel times and beyond. As a result, ventilator treatments may become more widely available to help patients breathe.","","https://www.kaggle.com/competitions/ventilator-pressure-prediction","completed","8","","2021-09-22","2021-11-03","2023-08-08 17:53:33","2023-11-02 18:44:22" +"173","stanford-covid-vaccine","OpenVaccine - COVID-19 mRNA Vaccine Degradation Prediction","Urgent need to bring the COVID-19 vaccine to mass production","In this competition, we are looking to leverage the data science expertise of the Kaggle community to develop models and design rules for RNA degradation. Your model will predict likely degradation rates at each base of an RNA molecule, trained on a subset of an Eterna dataset comprising over 3000 RNA molecules (which span a panoply of sequences and structures) and their degradation rates at each position. We will then score your models on a second generation of RNA sequences that have just been devised by Eterna players for COVID-19 mRNA vaccines. These final test sequences are currently being synthesized and experimentally characterized at Stanford University in parallel to your modeling efforts--Nature will score your models!","","https://www.kaggle.com/competitions/stanford-covid-vaccine","completed","8","","2020-09-10","2020-10-06","2023-08-08 18:06:17","2023-10-12 18:14:27" +"174","openvaccine","OpenVaccine","To develop mRNA vaccines stable enough to be deployed to everyone in the world","mRNA vaccines are a relatively new technology that have come into the limelight with the onset of COVID-19. They were the first COVID-19 vaccines to start clinical trials (initially formulated in a matter of days) and the first to be approved and distributed. mRNA vaccines have the potential to transform immunization, being significantly faster to formulate and produce, cheaper, and more effective-including against mutant strains. However, there is one key bottleneck to their widespread viability and our ability to immunize the entire world-poor refrigerator stability in prefilled syringes. The OpenVaccine challenge aims to allow a worldwide community of game players to create an enhanced vaccine to be injected into millions of people. The challenge-design an mRNA that codes for the same amino acid sequence of the spike protein, but is 2x-10x+ more stable. Through a number of academic partnerships and the launch of a Kaggle machine learning challenge to create best-in-class algori...","","https://eternagame.org/challenges/10845741","completed","13","https://doi.org/10.1038/s41467-022-28776-w","\N","2021-12-12","2023-08-08 18:22:49","2023-11-14 19:26:10" +"175","opentb","OpenTB","Detect a gene sequence found to be present only in people with active TB","OpenTB used a recently reported gene signature for active tuberculosis based on three RNAs in the blood. This signature could form the basis for a fast, color-based test for TB, similar to an over-the-counter pregnancy test. What was needed was a sensor that could detect the concentrations of three RNAs, carry out the needed calculation, and report the result by binding another molecule. Over four rounds, players designed RNA sensors that can do the math on these 3 genes. Through experimental feedback, they honed their skills and techniques, which resulted in the creation of multiple designs that have been shown to be successful. These findings are being prepared to be published, and future work will be done to develop diagnostic devices integrating these designs","","https://eternagame.org/challenges/10845742","completed","13","","2016-05-04","2018-04-15","2023-08-08 18:43:09","2023-11-14 19:32:31" +"176","opencrispr","OpenCRISPR","Discover RNAs to make gene editing more precisely controllable","CRISPR gene editing is a RNA-based method that can target essentially any gene in a living organism for genetic changes. Since its first demonstration, CRISPR has been revolutionizing biology and promises to change how we tackle numerous human diseases from malaria to cancer. Stanford's Center for Personal Dynamic Regulomes and UC Berkeley's Innovative Genomics Institute have challenged Eterna players to solve a remaining hurdle in making this technology safe for use. Scientists want the power to turn on and off CRISPR on demand with small molecules. This is almost a perfect match to the small-molecule switches that the Eterna community has worked on. In fact, the MS2 RNA hairpin often used in Eterna is routinely used to recruit new functionality to CRISPR complexes through other molecules tethered to the MS2 protein. The puzzles began with OpenCRISPR Controls, looking for solutions to lock in or lock out the MS2 RNA hairpin within a special loop in the CRISPR RNA. We hope the res...","","https://eternagame.org/challenges/10845743","completed","13","https://doi.org/10.1021/acssynbio.9b00142","2017-08-26","\N","2023-08-08 18:43:14","2023-11-14 19:33:25" +"177","openknot","OpenKnot","Build a diverse library of RNAs that form pseudoknot structures","RNA pseudoknots have significant biological importance in various processes. They participate in gene regulation by influencing translation initiation or termination in mRNA molecules. Pseudoknots also play a role in programmed ribosomal frameshifting, leading to the production of different protein products from a single mRNA. RNA viruses, including SARS-CoV-2 and Dengue virus, utilize pseudoknots to regulate their replication and control the synthesis of viral proteins. Additionally, certain RNA molecules with pseudoknot structures exhibit enzymatic activity, acting as ribozymes and catalyzing biochemical reactions. These functions highlight the crucial role of RNA pseudoknots in gene expression, proteomic diversity, viral replication, and enzymatic processes. Several unanswered scientific questions surround RNA pseudoknots. One key area of inquiry is understanding the folding pathways of pseudoknots and how they form from linear RNA sequences. Elucidating the structural dynamics...","","https://eternagame.org/challenges/11843006","active","13","","2022-06-17","\N","2023-08-08 18:43:22","2023-11-14 19:32:46" +"178","openaso","OpenASO","Design principles for RNA-based therapeutics","The DNA genome is the blueprint for building and operating cells, but this information must be decoded into RNA molecules to be useful. Transcription is the process of decoding DNA genomic information into RNA, resulting in RNA transcripts. Genes are specific sequences of DNA that contain information to produce a specific RNA transcript. The fate of most mRNA molecules in the cell is to be translated by ribosomes into protein molecules. However, mRNA splicing is a crucial step that occurs between the formation of an RNA transcript and protein translation. This step is essential because genes contain non-protein coding introns and protein-coding exons. Splicing removes introns and joins exons to produce a mature mRNA molecule that can be decoded into the correct protein molecule. When the splicing process is corrupted due to genetic mutations, the resulting RNA can become toxic, leading to the synthesis of non-functional proteins or no protein at all, causing various human diseases...","","https://eternagame.org/challenges/11546273","active","13","","2023-02-20","\N","2023-08-08 18:43:25","2023-11-14 19:32:51" +"179","openribosome","OpenRibosome","Learn and change the ribosome's RNAs","Our modern world has many challenges-challenges like climate change, increasing waste production, and human health. Imagine-we could replace petrochemistry with biology, single-use plastics with selectively degradable polymers, broad chemotherapeutics with targeted medicines for fighting specific cancer cells, and complex health equipment with point-of-care diagnostics. These innovations and many more can empower us to confront the challenges affecting humanity, our world, and beyond. But how do we actually create these smart materials and medicines? Is it possible to do so by repurposing one of Nature's molecular machines? We think we can. The answer? Customized ribosomes. In Nature, ribosomes are the catalysts for protein assembly. And proteins are more or less similar, chemically, to the smart materials and medicines we want to synthesize. If we could modify ribosomes to build polymers with diverse components-beyond the canonical amino acids us","","https://eternagame.org/challenges/11043833","active","13","https://doi.org/10.1038/s41467-023-35827-3","2019-01-31","\N","2023-08-08 18:43:27","2023-11-14 19:33:01" +"180","lish-moa","Mechanisms of Action (MoA) Prediction","Improve the algorithm that classifies drugs based on their biological activity","Can you improve the algorithm that classifies drugs based on their biological activity?","","https://www.kaggle.com/competitions/lish-moa","completed","8","","2020-09-03","2020-11-30","2023-08-08 19:09:31","2023-11-14 19:33:49" +"181","recursion-cellular-image-classification","Recursion Cellular Image Classification","CellSignal-Disentangling biological signal in cellular images","This competition will have you disentangling experimental noise from real biological signals. Your entry will classify images of cells under one of 1,108 different genetic perturbations. You can help eliminate the noise introduced by technical execution and environmental variation between experiments. If successful, you could dramatically improve the industry’s ability to model cellular images according to their relevant biology. In turn, applying AI could greatly decrease the cost of treatments, and ensure these treatments get to patients faster.","","https://www.kaggle.com/competitions/recursion-cellular-image-classification","completed","8","","2019-06-27","2019-09-26","2023-08-08 19:38:42","2023-11-14 19:34:11" +"182","tlvmc-parkinsons-freezing-gait-prediction","Parkinson's Freezing of Gait Prediction","Event detection from wearable sensor data","The goal of this competition is to detect freezing of gait (FOG), a debilitating symptom that afflicts many people with Parkinson’s disease. You will develop a machine learning model trained on data collected from a wearable 3D lower back sensor. Your work will help researchers better understand when and why FOG episodes occur. This will improve the ability of medical professionals to optimally evaluate, monitor, and ultimately, prevent FOG events.","","https://www.kaggle.com/competitions/tlvmc-parkinsons-freezing-gait-prediction","completed","8","","2023-03-09","2023-06-08","2023-08-08 19:47:54","2023-10-10 19:53:08" +"183","chaimeleon","CHAIMELEON Open Challenges","AI-powered solutions driving innovation in cancer diagnosis and treatment","The CHAIMELEON Open Challenges is a competition designed to train and refine AI models to answer clinical questions about five types of cancer-prostate, lung, breast, colon, and rectal. Participants are challenged to collaborate and develop innovative AI-powered solutions that can significantly impact cancer diagnosis, management, and treatment. They will be evaluated considering a balance between the performance of their AI algorithms to predict different clinical endpoints such as disease staging, treatment response or progression free survival and their trustworthiness. The challenges are open to the whole scientific and tech community interested in AI. They are a unique opportunity to showcase how AI can be used to advance medical research and improve patient outcomes within the CHAIMELEON project.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/744/Logo_Grand_Challenge_-_2.png","https://chaimeleon.grand-challenge.org/","active","5","","2023-11-02","2023-11-30","2023-08-09 17:13:09","2023-11-14 19:34:50" +"184","topcow23","Topology-Aware Anatomical Segmentation of the Circle of Willis for CTA and MRA","Segment the Circle of Willis (CoW) vessel components for both CTA and MRA","The aim of the challenge is to extract the CoW angio-architecture from 3D angiographic imaging by segmentation of the vessel components. There are two sub-tasks-binary segmentation of CoW vessels, and multi-class CoW anatomical segmentation. We release a new dataset of joint-modalities, CTA and MRA of the same patient cohort, both with annotations of the anatomy of CoW. Our challenge has two tracks for the same segmentation task, namely CTA track and MRA track. We made use of the clinical information from both modalities during our annotation. And participants can pick whichever modality they want, both CTA and MRA, and choose to tackle the task for either modality.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/733/TopCow_logo.jpg","https://topcow23.grand-challenge.org/","completed","5","","2023-08-20","2023-09-25","2023-08-09 17:16:22","2023-11-08 00:53:26" +"185","circle-of-willis-intracranial-artery-classification-and-quantification-challenge-2023","Circle of Willis Intracranial Artery Classification and Quantification Challenge 2023","Classify the circle of Willis (CoW) configuration and quantification","The purpose of this challenge is to compare automatic methods for classification of the circle of Willis (CoW) configuration and quantification of the CoW major artery diameters and bifurcation angles.","","https://crown.isi.uu.nl/","completed","14","","2023-05-01","2023-08-15","2023-08-09 22:13:24","2023-09-28 23:24:54" +"186","making-sense-of-electronic-health-record-ehr-race-and-ethnicity-data","Making Sense of Electronic Health Record (EHR) Race and Ethnicity Data","Make sense of electronic health record race and ethnicity data","The urgency of the coronavirus disease 2019 (COVID-19) pandemic has heightened interest in the use of real-world data (RWD) to obtain timely information about patients and populations and has focused attention on EHRs. The pandemic has also heightened awareness of long-standing racial and ethnic health disparities along a continuum from underlying social determinants of health, exposure to risk, access to insurance and care, quality of care, and responses to treatments. This highlighted the potential that EHRs can be used to describe and contribute to our understanding of racial and ethnic health disparities and their solutions. The OMB Revisions to the Standards for the Classification of Federal Data on Race and Ethnicity provides minimum standards for maintaining, collecting, and presenting data on race and ethnicity for all Federal reporting purposes, and defines the two separate constructs of race and ethnicity.","","https://precision.fda.gov/challenges/30","completed","6","","2023-05-31","2023-06-23","2023-08-10 18:28:06","2023-11-14 19:34:58" +"187","the-veterans-cardiac-health-and-ai-model-predictions-v-champs","The Veterans Cardiac Health and AI Model Predictions (V-CHAMPS)","Predict cardiovascular health related outcomes in veterans","To better understand the risk and protective factors in the Veteran population, the VHA IE and its collaborating partners are calling upon the public to develop AI/ML models to predict cardiovascular health outcomes, including readmission and mortality, using synthetically generated Veteran health records. The Challenge consists of two Phases-Phase 1 is focused on synthetic data. In this Phase of the Challenge, AI/ML models will be developed by Challenge participants and trained and tested on the synthetic data sets provided to them, with a view towards predicting outcome variables for Veterans who have been diagnosed with chronic heart failure (please note that in Phase 1, the data is synthetic Veteran health records). Phase 2 will focus on validating and further exploring the limits of the AI/ML models. During this Phase, high-performing AI/ML models from Phase 1 will be brought into the VA system and validated on the real-world Veterans health data within the VHA. These models...","","https://precision.fda.gov/challenges/31","completed","6","","2023-05-25","2023-08-02","2023-08-10 21:41:10","2023-11-14 19:35:53" +"188","predicting-high-risk-breast-cancer-phase-1","Predicting High Risk Breast Cancer - Phase 1","Predicting High Risk Breast Cancer-a Nightingale OS & AHLI data challenge","Every year, 40 million women get a mammogram; some go on to have an invasive biopsy to better examine a concerning area. Underneath these routine tests lies a deep—and disturbing—mystery. Since the 1990s, we have found far more ‘cancers’, which has in turn prompted vastly more surgical procedures and chemotherapy. But death rates from metastatic breast cancer have hardly changed. When a pathologist looks at a biopsy slide, she is looking for known signs of cancer-tubules, cells with atypical looking nuclei, evidence of rapid cell division. These features, first identified in 1928, still underlie critical decisions today-which women must receive urgent treatment with surgery and chemotherapy? And which can be prescribed “watchful waiting”, sparing them invasive procedures for cancers that would not harm them? There is already evidence that algorithms can predict which cancers will metastasize and harm patients on the basis of the biopsy image. Fascinatingly, these algorithms also h...","","https://app.nightingalescience.org/contests/3jmp2y128nxd","completed","15","","2022-06-01","2023-01-12","2023-08-22 17:07:00","2023-10-12 17:55:10" +"189","predicting-high-risk-breast-cancer-phase-2","Predicting High Risk Breast Cancer - Phase 2","Predicting High Risk Breast Cancer-a Nightingale OS & AHLI data challenge","Every year, 40 million women get a mammogram; some go on to have an invasive biopsy to better examine a concerning area. Underneath these routine tests lies a deep—and disturbing—mystery. Since the 1990s, we have found far more ‘cancers’, which has in turn prompted vastly more surgical procedures and chemotherapy. But death rates from metastatic breast cancer have hardly changed. When a pathologist looks at a biopsy slide, she is looking for known signs of cancer-tubules, cells with atypical looking nuclei, evidence of rapid cell division. These features, first identified in 1928, still underlie critical decisions today-which women must receive urgent treatment with surgery and chemotherapy? And which can be prescribed “watchful waiting”, sparing them invasive procedures for cancers that would not harm them? There is already evidence that algorithms can predict which cancers will metastasize and harm patients on the basis of the biopsy image. Fascinatingly, these algorithms also...","","https://app.nightingalescience.org/contests/vd8g98zv9w0p","completed","15","","2023-02-03","2023-05-13","2023-08-22 17:07:01","2023-10-12 17:55:08" +"190","dream-2-in-silico-network-inference","DREAM 2 - In Silico Network Inference","Predict the connectivity and properties of in-silico networks","Three in-silico networks were created and endowed with a dynamics that simulate biological interactions. The challenge consists of predicting the connectivity and some of the properties of one or more of these three networks.","","https://www.synapse.org/#!Synapse:syn2825394/wiki/71150","completed","1","","2007-03-25","\N","2023-08-24 18:54:05","2023-10-12 17:55:03" +"191","dream-3-in-silico-network-challenge","DREAM 3 - In Silico Network Challenge","Reverse engineering of gene networks from biological data","The goal of the in silico challenges is the reverse engineering of gene networks from steady state and time series data. Participants are challenged to predict the directed unsigned network topology from the given in silico generated gene topic_3170sets.","","https://www.synapse.org/#!Synapse:syn2853594/wiki/71567","completed","1","https://doi.org/10.1089/cmb.2008.09TT","2008-06-09","\N","2023-08-25 16:43:41","2023-11-14 19:35:58" +"192","dream-4-in-silico-network-challenge","DREAM 4 - In Silico Network Challenge","Reverse engineer gene regulatory networks","The goal of the in silico network challenge is to reverse engineer gene regulation networks from simulated steady-state and time-series data. Participants are challenged to infer the network structure from the given in silico gene topic_3170sets. Optionally, participants may also predict the response of the networks to a set of novel perturbations that were not included in the provided datasets.","","https://www.synapse.org/#!Synapse:syn3049712/wiki/74628","completed","1","https://doi.org/10.1073/pnas.0913357107","2009-06-09","\N","2023-08-25 16:43:42","2023-11-14 19:36:02" +"193","dream-5-network-inference-challenge","DREAM 5 - Network Inference Challenge","Reverse engineer gene regulatory networks","The goal of this Network Inference Challenge is to reverse engineer gene regulatory networks from gene topic_3170sets. Participants are given four microarray compendia and are challenged to infer the structure of the underlying transcriptional regulatory networks. Three of the four compendia were obtained from microorganisms, some of which are pathogens of clinical relevance. The fourth compendium is based on an in-silico (i.e., simulated) network. Each compendium consists of hundreds of microarray experiments, which include a wide range of genetic, drug, and environmental perturbations (or in the in-silico network case, simulations thereof). Network predictions will be evaluated on a subset of known interactions for each organism, or on the known network for the in-silico case.","","https://www.synapse.org/#!Synapse:syn2787209/wiki/70349","completed","1","https://doi.org/10.1038/nmeth.2016","2010-06-09","2010-10-31","2023-08-25 16:43:43","2023-11-14 19:36:08" +"194","nlp-sandbox-date-annotation","NLP Sandbox Date Annotation","Identify dates in clinical notes","An NLP Sandbox Date Annotator takes as input a clinical note and outputs a list of predicted date annotations found in the clinical note.","","https://www.synapse.org/#!Synapse:syn22277123/wiki/609134","completed","1","https://doi.org/10.7303/syn22277123","2021-06-04","2023-09-01","2023-08-25 16:45:22","2023-11-15 22:41:56" +"195","nlp-sandbox-person-name-annotation","NLP Sandbox Person Name Annotation","Identify person names in clinical notes","An NLP Sandbox Person Name Annotator takes as input a clinical note and outputs a list of predicted person name annotations found in the clinical note.","","https://www.synapse.org/#!Synapse:syn22277123/wiki/609134","completed","1","https://doi.org/10.7303/syn22277123","2021-06-04","2023-09-01","2023-09-08 16:44:20","2023-09-28 23:59:20" +"196","nlp-sandbox-location-annotation","NLP Sandbox Location Annotation","Identify location information in clinical notes","An NLP Sandbox Location Annotator takes as input a clinical note and outputs a list of predicted location annotations found in the clinical note.","","https://www.synapse.org/#!Synapse:syn22277123/wiki/609134","completed","1","https://doi.org/10.7303/syn22277123","2021-06-04","2023-09-01","2023-09-08 16:44:21","2023-09-28 23:59:21" +"197","nlp-sandbox-contact-annotation","NLP Sandbox Contact Annotation","Identify contact information in clinical notes","An NLP Sandbox contact annotator takes as input a clinical note and outputs a list of predicted contact annotations found in the clinical note.","","https://www.synapse.org/#!Synapse:syn22277123/wiki/609134","completed","1","https://doi.org/10.7303/syn22277123","2021-06-04","2023-09-01","2023-09-08 16:44:22","2023-09-28 23:59:21" +"198","nlp-sandbox-id-annotation","NLP Sandbox ID Annotation","Identify identifiers in clinical notes","An NLP Sandbox ID annotator takes as input a clinical note and outputs a list of predicted ID annotations found in the clinical note.","","https://www.synapse.org/#!Synapse:syn22277123/wiki/609134","completed","1","https://doi.org/10.7303/syn22277123","2021-06-04","2023-09-01","2023-09-08 16:44:22","2023-09-28 23:59:22" +"199","dream-2-bcl6-transcriptomic-target-prediction","DREAM 2 - BCL6 Transcriptomic Target Prediction","Predict BCL6 transcriptomic targets from biological data","A number of potential transcriptional targets of BCL6, a gene that encodes for a transcription factor active in B cells, have been identified with ChIP-on-chip data and functionally validated by perturbing the BCL6 pathway with CD40 and anti-IgM, and by over-expressing exogenous BCL6 in Ramos cell. We subselected a number of targets found in this way (the gold standard positive set), and added a number decoys (genes that have no evidence of being BCL6 targets, named the gold standard negative set), compiling a list of 200 genes in total. Given this list of 200 genes, the challenge consists of identifying which ones are the true targets and which ones are the decoys, using an independent panel of gene topic_3170.","","https://www.synapse.org/#!Synapse:syn3034857/wiki/","completed","1","https://doi.org/10.1073/pnas.0437996100","2007-04-19","\N","2023-09-12 21:26:22","2023-10-12 17:53:55" +"200","dream-2-protein-protein-interaction-network-inference","DREAM 2 - Protein-Protein Interaction Network Inference","Predict a protein-protein interaction network of 47 proteins","For many pairs of bait and prey genes, yeast protein-protein interactions were tested in an unbiased fashion using a high saturation, high-stringency variant of the yeast two-hybrid (Y2H) method. A high confidence subset of gene pairs that were found to interact in at least three repetitions of the experiment but that hadn’t been reported in the literature was extracted. There were 47 yeast genes involved in these pairs. Including self interactions, there are a total of 47*48/2 possible pairs of genes that can be formed with these 47 genes. As mentioned above some of these gene pairs were seen to consistently interact in at least three repetitions of the Y2H experiments-these gene pairs form the gold standard positive set. A second set among these gene pairs were seen never to interact in repeated experiments and were not reported as interacting in the literature; we call this the gold standard negative set. Finally in a third set of gene pairs, which we shall call the undecided s...","","https://www.synapse.org/#!Synapse:syn2825374/wiki/","completed","1","https://doi.org/10.1126/science.1158684","2007-05-24","\N","2023-09-12 21:26:28","2023-10-12 17:54:00" +"201","dream-2-genome-scale-network-inference","DREAM 2 - Genome-Scale Network Inference","Reconstruct genome-scale networks from microarray data","A panel of single-channel microarrays was collected for a particular microorganism, including some already published and some in-print data. The data was appropriately normalized (to the logarithmic scale). The challenge consists of reconstructing a genome-scale transcriptional network for this organism. The accuracy of network inference will be judged using chromatin precipitation and otherwise experimentally verified Transcription Factor (TF)-target interactions.","","https://www.synapse.org/#!Synapse:syn3034894/wiki/74418","completed","1","https://doi.org/10.1371/journal.pbio.0050008","2007-06-05","2007-10-31","2023-09-12 21:26:34","2023-10-12 17:54:03" +"202","dream-2-synthetic-five-gene-network-inference","DREAM 2 - Synthetic Five-Gene Network Inference","Inferring five-gene networks from synthetic data","A synthetic-biology network consisting of 5 interacting genes was created and transfected to an in-vivo model organism. The challenge consists of predicting the connectivity of the five-gene network from in-vivo measurements.","","https://www.synapse.org/#!Synapse:syn3034869/wiki/74411","completed","1","https://doi.org/10.1016/j.cell.2009.01.055","2007-06-20","2007-10-31","2023-09-12 21:26:56","2023-10-12 17:54:05" +"203","dream-3-signaling-cascade-identification","DREAM 3 - Signaling Cascade Identification","Inferring signaling cascade dynamics from flow cytometry data","The concentration of four intracellular proteins or phospho-proteins (X1, X2, X3 and X4) participating in a signaling cascade were measured in about 104 cells by antibody staining and flow cytometry. The idea of this challenge is to explore what key aspects of the dynamics and topology of interactions of a signaling cascade can be inferred from incomplete flow cytometry data.","","https://www.synapse.org/#!Synapse:syn3033068/wiki/74362","completed","1","","2008-06-01","2008-10-31","2023-09-12 21:27:04","2023-10-12 17:54:08" +"204","dream-3-gene-expression-prediction","DREAM 3 - Gene Expression Prediction","Predicting gene expression from gene datasets","Gene expression time course data is provided for four different strains of yeast (S. Cerevisiae), after perturbation of the cells. The challenge is to predict the rank order of induction/repression of a small subset of genes (the prediction targets) in one of the four strains, given complete data for three of the strains, and data for all genes except the prediction targets in the other strain. You are also allowed to use any information that is in the public domain and are expected to be forthcoming about what information was used.","","https://www.synapse.org/#!Synapse:syn3033083/wiki/74369","completed","1","","2008-06-01","2008-10-31","2023-09-12 21:27:12","2023-10-12 17:54:10" +"205","dream-4-predictive-signaling-network-modelling","DREAM 4 - Predictive Signaling Network Modelling","Cell-type specific high-throughput experimental data","This challenge explores the extent to which our current knowledge of signaling pathways, collected from a variety of cell types, agrees with cell-type specific high-throughput experimental data. Specifically, we ask the challenge participants to create a cell-type specific model of signal transduction using the measured activity levels of signaling proteins in HepG2 cell lines. The model, which can leverage prior information encoded in a generic signaling pathway provided in the challenge, should be biologically interpretable as a network, and capable of predicting the outcome of new experiments.","","https://www.synapse.org/#!Synapse:syn2825304/wiki/71129","completed","1","","2009-03-09","\N","2023-09-12 21:27:14","2023-10-12 17:54:30" +"206","dream-3-signaling-response-prediction","DREAM 3 - Signaling Response Prediction","Predict missing protein concentrations from a large corpus of measurements","Approximately 10,000 intracellular measurements (fluorescence signals proportional to the concentrations of phosphorylated proteins) and extracellular measurements (concentrations of cytokines released in response to cell stimulation) were acquired in human normal hepatocytes and the hepatocellular carcinoma cell line HepG2 cells. The datasets consist of measurements of 17 phospho-proteins (at 0 min, 30 min, and 3 hrs) and 20 cytokines (at 0 min, 3 hrs, and 24 hrs) in two cell types (normal and cancer) after perturbations to the pathway induced by the combinatorial treatment of 7 stimuli and 7 selective inhibitors.","","https://www.synapse.org/#!Synapse:syn2825325/wiki/","completed","1","https://doi.org/10.1126%2Fscisignal.2002212","2009-03-09","\N","2023-09-12 21:27:20","2023-10-12 17:54:33" +"207","dream-4-peptide-recognition-domain-prd-specificity-prediction","DREAM 4 - Peptide Recognition Domain (PRD) Specificity Prediction","Predict binding specificity of peptide-antibody interactions","Many important protein-protein interactions are mediated by peptide recognition domains (PRD), which bind short linear sequence motifs in other proteins. For example, SH3 domains typically recognize proline-rich motifs, PDZ domains recognize hydrophobic C-terminal tails, and kinases recognize short sequence regions around a phosphorylatable residue (Pawson, 2003). Given the sequence of the domains, the challenge consists of predicting a position weight matrix (PWM) that describes the specificity profile of each of the given domains to their target peptides. Any publicly accessible peptide specificity information available for the domain may be used.","","https://www.synapse.org/#!Synapse:syn2925957/wiki/72976","completed","1","","2009-06-01","2009-10-31","2023-09-12 21:27:35","2023-10-12 17:54:35" +"208","dream-5-transcription-factor-dna-motif-recognition-challenge","DREAM 5 - Transcription-Factor, DNA-Motif Recognition Challenge","Predict binding intensities for transcription factors from motifs","Transcription factors (TFs) control the expression of genes through sequence-specific interactions with genomic DNA. Different TFs bind preferentially to different sequences, with the majority recognizing short (6-12 base), degenerate ‘motifs’. Modeling the sequence specificities of TFs is a central problem in understanding the function and evolution of the genome, because many types of genomic analyses involve scanning for potential TF binding sites. Models of TF binding specificity are also important for understanding the function and evolution of the TFs themselves. The challenge consists of predicting the signal intensities for the remaining TFs.","","https://www.synapse.org/#!Synapse:syn2887863/wiki/72185","completed","1","https://doi.org/10.1038/nbt.2486","2011-06-01","2011-09-30","2023-09-12 21:27:41","2023-10-12 17:54:36" +"209","dream-5-epitope-antibody-recognition-ear-challenge","DREAM 5 - Epitope-Antibody Recognition (EAR) Challenge","Predict the binding specificity of peptide-antibody interactions","Humoral immune responses are mediated through antibodies. About 1010 to 1012 different antigen binding sites called paratopes are generated by genomic recombination. These antibodies are capable to bind to a variety of structures ranging from small molecules to protein complexes, including any posttranslational modification thereof. When studying protein-antibody interactions, two types of epitopes (the region paratopes interact with) are to be distinguished from each other-i) conformational and ii) linear epitopes. All potential linear epitopes of a protein can be represented by short peptides derived from the primary amino acid sequence. These peptides can be synthesized and arrayed on solid supports, e.g. glass slides (see Lorenz et al., 2009 [1]). By incubating these peptide arrays with antibody mixtures such as human serum or plasma, peptides can be determined that interact with antibodies in a specific fashion.","","https://www.synapse.org/#!Synapse:syn2820433/wiki/71017","completed","1","","2010-06-09","\N","2023-09-12 21:27:44","2023-10-12 17:54:39" +"210","dream-gene-expression-prediction-challenge","DREAM Gene Expression Prediction Challenge","Predict gene expression levels from promoter sequences in eukaryotes","The level by which genes are transcribed is determined in large part by the DNA sequence upstream to the gene, known as the promoter region. Although widely studied, we are still far from a quantitative and predictive understanding of how transcriptional regulation is encoded in gene promoters. One obstacle in the field is obtaining accurate measurements of transcription derived by different promoters. To address this, an experimental system was designed to measure the transcription derived by different promoters, all of which are inserted into the same genomic location upstream to a reporter gene -a yellow florescence protein gene (YFP). The challenge consists of the prediction of the promoter activity given a promoter sequence and a specific experimental condition. To study a set of promoters that share many elements of the regulatory program, and thus are suitable for computational learning, the data pertains to promoters of most of the ribosomal protein genes (RP) of yeast (S....","","https://www.synapse.org/#!Synapse:syn2820426/wiki/71010","completed","1","","2010-07-09","\N","2023-09-12 21:28:00","2023-10-19 23:32:10" +"211","dream-5-systems-genetics-challenge","DREAM 5 - Systems Genetics Challenge","Predict disease phenotypes and infer gene networks from systems genetics data","The central goal of systems biology is to gain a predictive, system-level understanding of biological networks. This can be done, for example, by inferring causal networks from observations on a perturbed biological system. An ideal experimental design for causal inference is randomized, multifactorial perturbation. The recognition that the genetic variation in a segregating population represents randomized, multifactorial perturbations (Jansen and Nap (2001), Jansen (2003)) gave rise to Systems Genetics (SG), where a segregating or genetically randomized population is genotyped for many DNA variants, and profiled for phenotypes of interest (e.g. disease phenotypes), gene expression, and potentially other ‘omics’ variables (protein expression, metabolomics, DNA methylation, etc.; Figure 1. Figure 1 was taken from Jansen and Nap (2001)). In this challenge we explore the use of Systems Genetics data for elucidating causal network models among genes, i.e. Gene Networks (DREAM5 SYSGEN...","","https://www.synapse.org/#!Synapse:syn2820440/wiki/","completed","1","","2010-07-09","\N","2023-09-12 21:28:10","2023-10-12 17:54:42" +"212","dream-6-estimation-of-model-parameters-challenge","DREAM 6 - Estimation of Model Parameters Challenge","Challenge to estimate model parameters","Given the complete model structures (including expressions for the kinetic rate laws) for three gene regulatory networks, participants are asked to develop and/or apply optimization methods, including the selection of the most informative experiments, to accurately estimate parameters and predict outcomes of perturbations in Systems Biology models.","","https://www.synapse.org/#!Synapse:syn2841366/wiki/71372","completed","1","","2011-06-01","2011-10-31","2023-09-12 21:28:12","2023-10-12 17:54:45" +"213","dream-6-flowcap2-molecular-classification-of-acute-myeloid-leukemia-challenge","DREAM 6 - FlowCAP2 Molecular Classification of Acute Myeloid Leukemia Challenge","Diagnose acute myeloid leukemia from patient data using flow cytometry","Flow cytometry (FCM) has been widely used by immunologists and cancer biologists for more than 30 years as a biomedical research tool to distinguish different cell types in mixed populations, based on the expression of cellular markers. It has also become a widely used diagnostic tool for clinicians to identify abnormal cell populations associated with disease. In the last decade, advances in instrumentation and reagent technologies have enabled simultaneous single-cell measurement of tens of surface and intracellular markers, as well as tens of signaling molecules, positioning FCM to play an even bigger role in medicine and systems biology [1,2]. However, the rapid expansion of FCM applications has outpaced the functionality of traditional analysis tools used to interpret FCM data such that scientists are faced with the daunting prospect of manually identifying interesting cell populations in 20 dimensional data from a collection of millions of cells. For these reasons a reliable...","","https://www.synapse.org/#!Synapse:syn2887788/wiki/72178","completed","1","https://doi.org/10.1038/nmeth.2365","2011-06-01","2011-09-30","2023-09-12 21:28:19","2023-11-14 19:36:22" +"214","dream-6-alternative-splicing-challenge","DREAM 6 - Alternative Splicing Challenge","Compare mRNA-seq methods on primate and rhino transcripts","The goal of the mRNA-seq alternative splicing challenge is to assess the accuracy of the reconstruction of alternatively spliced mRNA transcripts from Illumina short-read mRNA-seq. Reconstructed transcripts will be scored against Pacific Biosciences long-read mRNA-seq. The ensuing analysis of the transcriptomes from mandrill and rhinoceros fibroblasts and their derived induced pluripotent stem cells (iPSC), as well as the transcriptome for human Embrionic Stem Cells (hESC) is an opportunity to discover novel biology as well as investigate species-bias of different methods.","","https://www.synapse.org/#!Synapse:syn2817724/wiki/","completed","1","","2011-08-09","\N","2023-09-12 21:28:25","2023-10-12 17:54:50" +"215","causalbench-challenge","CausalBench Challenge","Gene network inference from single-cell perturbation data","Mapping gene-gene interactions in cellular systems is a fundamental step in early-stage drug discovery that helps generate hypotheses on what molecular mechanisms may effectively be targeted by potential future medicines. In the CausalBench Challenge, we invite the machine-learning community to advance the state-of-the-art in deriving gene-gene networks from large-scale real-world perturbational single-cell datasets to improve our ability to glean causal insights into disease-relevant biology.","","https://www.gsk.ai/causalbench-challenge/","completed","16","https://doi.org/10.48550/arXiv.2308.15395","2023-03-01","2023-04-21","2023-09-12 21:28:25","2023-11-14 19:36:27" +"216","iclr-computational-geometry-and-topology-challenge-2022","ICLR Computational Geometry & Topology Challenge 2022","Advancing computational geometry and topology with python","The purpose of this challenge is to foster reproducible research in geometric (deep) learning, by crowdsourcing the open-source implementation of learning algorithms on manifolds. Participants are asked to contribute code for a published/unpublished algorithm, following Scikit-Learn/Geomstats' or pytorch's APIs and computational primitives, benchmark it, and demonstrate its use in real-world scenarios.","","https://github.com/geomstats/challenge-iclr-2022","completed","14","","\N","2022-04-04","2023-09-13 16:54:06","2023-10-19 23:28:44" +"217","iclr-computational-geometry-and-topology-challenge-2021","ICLR Computational Geometry & Topology Challenge 2021","Advancing computational geometry and topology with python","The purpose of this challenge is to push forward the fields of computational differential geometry and topology, by creating the best data analysis, computational method, or numerical experiment relying on state-of-the-art geometric and topological Python packages.","","https://github.com/geomstats/challenge-iclr-2021","completed","14","https://doi.org/10.48550/arXiv.2108.09810","\N","2021-05-02","2023-09-13 17:02:12","2023-10-19 23:28:44" +"218","genedisco-challenge","GeneDisco Challenge","Exploring experimental design with active learning for genetics","The GeneDisco challenge is a machine learning community challenge for evaluating batch active learning algorithms for exploring the vast experimental design space in genetic perturbation experiments. Genetic perturbation experiments, using for example CRISPR technologies to perturb the genome, are a vital component of early-stage drug discovery, including target discovery and target validation. The GeneDisco challenge is organized in conjunction with the Machine Learning for Drug Discovery workshop at ICLR-22.","","https://www.gsk.ai/genedisco-challenge/","completed","16","https://doi.org/10.48550/arXiv.2110.11875","2022-01-31","2022-03-31","2023-09-13 17:20:30","2023-10-19 23:32:43" +"219","hidden-treasures-warm-up","Hidden Treasures: Warm Up","Assess genome sequencing software accuracy with unknown variants","In the context of human genome sequencing, software pipelines typically involve a wide range of processing elements, including aligning sequencing reads to a reference genome and subsequently identifying variants (differences). One way of assessing the performance of such pipelines is by using well-characterized datasets such as Genome in a Bottle’s NA12878. However, because the existing NGS reference datasets are very limited and have been widely used to train/develop software pipelines, benchmarking of pipeline performance would ideally be done on samples with unknown variants. This challenge will provide a unique opportunity for participants to investigate the accuracy of their pipelines by testing the ability to find in silico injected variants in FASTQ files from exome sequencing of reference cell lines. It will be a warm up for the community ahead of a more difficult in silico challenge to come in the fall. This challenge will provide users with a FASTQ file of a NA12878 se...","","https://precision.fda.gov/challenges/1","completed","6","","2017-07-17","2017-09-13","2023-09-13 23:31:39","2023-10-12 17:55:23" +"220","data-management-and-graph-extraction-for-large-models-in-the-biomedical-space","Data management and graph extraction for large models in the biomedical space","Advancing biomedical knowledge graphs","This fall, CMU Libraries is hosting a hackathon in partnership with DNAnexus on the topic of data management and graph extraction for large models in the biomedical space. The hackathon will be held in person at CMU, October 19-21, 2023. The hackathon is a collaborative, rather than competitive, event, with each team working on a dedicated part of the problem. The teams will be focused on the following topics-1) Knowledge graph-based validation for variant (genomic) assertions; 2) Continuous monitoring for RLHF and flexible infrastructure for layering assertions with rollback; 3) Flexible tokenization of complex data types; 4) Assertion tracking in large models; 5) Column headers for data harmonization. The outputs are often published as preprints or on the F1000 hackathon channel. Contact Ben Busby (bbusby@dnanexus.com) with any questions about the hackathon or serving as a team lead.","","https://library.cmu.edu/about/news/2023-08/hackathon-2023","completed","14","","2023-10-19","2023-10-21","2023-09-13 23:32:59","2023-11-14 19:36:32" +"221","cagi2-asthma-twins","CAGI2: Asthma discordant monozygotic twins","Identify genetic differences between asthmatic and healthy twins","The dataset includes whole genomes of 8 pairs of discordant monozygotic twins (randomly numbered from 1 to 16) that is, in each pair identical twins one has asthma and one does not. In addition, RNA sequencing data for each individual is provided. One of the twins in each pair suffers from asthma while the other twin is healthy.","","https://genomeinterpretation.org/cagi2-asthma-twins.html","completed","14","","\N","2011-10-06","2023-09-28 18:19:48","2023-10-12 18:11:42" +"222","cagi4-bipolar","CAGI4: Bipolar disorder","Predicting bipolar disorder from exome data","Bipolar disorder (BD) is a serious mental illness characterized by recurrent episodes of manias and depression, which are syndromes of abnormal mood, thinking and behavior. It affects 1.0-4.5% of the population [1], and it is among the major causes of disability worldwide. This challenge involved the prediction of which of a set of individuals have been diagnosed with bipolar disorder, given exome data. 500 of the 1000 exome samples were provided for training.","","https://genomeinterpretation.org/cagi4-bipolar.html","completed","14","","\N","2016-04-04","2023-09-28 18:19:48","2023-09-28 18:25:17" +"223","cagi3-brca","CAGI3: BRCA1 & BRCA2","Assess hereditary cancer risk via BRCA gene analysis","In normal cells, the BRCA1 and BRCA2 genes are involved in homologous recombination for double strand break repair and ensure the stability of a cell's genetic material. Mutations in these genes have been linked to development of breast and ovarian cancer. Myriad Genetics created the BRACAnalysis test in order to assess a woman’s risk of developing hereditary breast or ovarian cancer based on detection of mutations in the BRCA1 and BRCA2 genes. This test has become the standard of care in identification of individuals with hereditary breast and ovarian cancer (HBOC) syndrome. It is based on proprietary methods.","","https://genomeinterpretation.org/cagi3-brca.html","completed","14","","\N","2013-04-25","2023-09-28 18:19:48","2023-10-19 23:32:48" +"224","cagi2-breast-cancer-pkg","CAGI2: Breast cancer pharmacogenomics","Exploring CHEK2 as a candidate gene for cancer susceptibility","Cell-cycle-checkpoint kinase 2 (CHEK2; OMIM #604373) is a protein that plays an important role in the maintenance of genome integrity and in the regulation of the G2/M cell cycle checkpoint. CHEK2 has been shown to interact with other proteins involved in DNA repair processes such as BRCA1 and TP53. These findings render CHEK2 an 23 attractive candidate susceptibility gene for a variety of cancers.","","https://genomeinterpretation.org/cagi2-breast-cancer-pkg.html","completed","14","","\N","2011-10-06","2023-09-28 18:19:48","2023-10-12 17:46:22" +"225","cagi4-2eqtl","CAGI4: eQTL causal SNPs","Identify regulatory variants causing gene expression differences","Identifying the causal alleles responsible for variation in expression of human genes has been particularly difficult. This is an important problem, as genome-wide association studies (GWAS) suggest that much of the variation underlying common traits and diseases maps within regions of the genome that do not encode protein. A massively parallel reporter assay (MPRA) has been applied to thousands of single nucleotide polymorphisms (SNPs) and small insertion/deletion polymorphisms in linkage disequilibrium (LD) with cis-expression quantitative trait loci (eQTLs). The results identify variants showing differential expression between alleles. The challenge is to identify the regulatory sequences and the expression-modulating variants (emVars) underlying each eQTL and estimate their effects in the assay.","","https://genomeinterpretation.org/cagi4-2eqtl.html","completed","14","","\N","2016-04-04","2023-09-28 18:19:48","2023-09-29 3-58-33" +"226","cagi1-cbs","CAGI1: CBS","Seeking to understand CBS enzyme function in cysteine production","CBS is a vitamin-dependent enzyme involved in cysteine biosynthesis. The human CBS requires two cofactors for function, vitamin B6 and heme. Homocystinuria due to CBS deficiency (OMIM #236200) is a recessive inborn error of sulfur amino acid metabolism.","","https://genomeinterpretation.org/cagi1-cbs.html","completed","14","","\N","2010-12-10","2023-09-28 18:19:48","2023-10-12 17:46:07" +"227","cagi2-cbs","CAGI2: CBS","Developing treatment for homocystinuria caused by cbs deficiency","CBS is a vitamin-dependent enzyme involved in cysteine biosynthesis. The human CBS requires two cofactors for function, vitamin B6 and heme. Homocystinuria due to CBS deficiency (OMIM #236200) is a recessive inborn error of sulfur amino acid metabolism.","","https://genomeinterpretation.org/cagi2-cbs.html","completed","14","","\N","2011-10-06","2023-09-28 18:19:48","2023-11-15 22:46:32" +"228","cagi1-chek2","CAGI1: CHEK2","Variants in the ATM & CHEK2 genes are associated with breast cancer","Predictors will be provided with 41 rare missense, nonsense, splicing, and indel variants in CHEK2.","","https://genomeinterpretation.org/cagi1-chek2.html","completed","14","","\N","2010-12-10","2023-09-28 18:19:48","2023-10-19 23:32:57" +"229","cagi3-fch","CAGI3: FCH","Seeking to understand genetic basis of common hyperlipidemia disorder","Familial combined hyperlipidemia (FCH; OMIM 14380) the most prevalent hyperlipidemia, is a complex metabolic disorder characterized by variable occurrence of elevated low-density lipoprotein cholesterol (LDL-C) level and high triglycerides (TG)—a condition that is commonly associated with coronary artery disease (CAD).","","https://genomeinterpretation.org/cagi3-fch.html","completed","14","","\N","2013-04-25","2023-09-28 18:19:48","2023-11-01 22:26:44" +"230","cagi3-ha","CAGI3: HA","Raising HDL levels to reduce heart disease risk","Hypoalphalipoproteinemia (HA; OMIM #604091) is characterized by severely decreased serum high-density lipoprotein cholesterol (HDL-C) levels and low apolipoprotein A1 (APOA1). Low HDL-C is a risk factor for coronary artery disease.","","https://genomeinterpretation.org/cagi3-ha.html","completed","14","","\N","2013-04-25","2023-09-28 18:19:48","2023-11-15 22:46:55" +"231","cagi2-croshn-s","CAGI2: Crohn's disease","Seeking genes linked to Crohn's, an inflammatory bowel disease","Crohn's disease (CD [MIM 266600]) a form of inflammatory bowel disease (IBD) is a complex genetic disorder characterized by chronic relapsing inflammation that can involve any part of the gastrointestinal tract.","","https://genomeinterpretation.org/cagi2-croshn-s.html","completed","14","","\N","2011-10-06","2023-09-28 18:19:48","2023-11-15 22:46:26" +"232","cagi3-crohn-s","CAGI3: Crohn's disease","Understanding the genetics behind Crohn's disease","Crohn's disease (CD [MIM 266600]) a form of inflammatory bowel disease (IBD) is a complex genetic disorder characterized by chronic relapsing inflammation that can involve any part of the gastrointestinal tract.","","https://genomeinterpretation.org/cagi3-crohn-s.html","completed","14","","\N","2013-04-25","2023-09-28 18:19:48","2023-11-15 22:46:27" +"233","cagi4-chron-s-exome","CAGI4: Crohn's exomes","Seeking to understand genetic basis of Crohn's bowel disease","Crohn's disease (CD [MIM 266600]) a form of inflammatory bowel disease (IBD) is a complex genetic disorder characterized by chronic relapsing inflammation that can involve any part of the gastrointestinal tract.","","https://genomeinterpretation.org/cagi4-chron-s-exome.html","completed","14","","\N","2016-04-04","2023-09-28 18:19:48","2023-11-15 22:46:23" +"234","cagi4-hopkins","CAGI4: Hopkins clinical panel","Exonic sequences of 83 genes linked to 14 diseases analyzed","The Johns Hopkins challenge, provided by the Johns Hopkins DNA Diagnostic Laboratory (http://www.hopkinsmedicine.org/dnadiagnostic), comprised of exonic sequence for 83 genes associated with one of 14 disease classes, including 5 decoys","","https://genomeinterpretation.org/cagi4-hopkins.html","completed","14","","\N","2016-04-04","2023-09-28 18:19:48","2023-10-12 17:45:27" +"235","cagi2-mouse-exomes","CAGI2: Mouse exomes","Predict causative variants from exome sequencing data","Predictors were given SNVs and indels found from exome sequencing. Causative variants had been identified for the L11Jus74 and Sofa phenotypes by the use of traditional breeding crosses,47 and the predictions were compared to these results, which were unpublished at the time of the CAGI submissions. The L11Jus74 phenotype is caused by two SNVs (chr11-102258914A> and chr11-77984176A>T), whereas a 15-nucleotide deletion in the Pfas gene is responsible for the Sofa phenotype. The predictions for Frg and Stn phenotypes could not be compared to experimental data, as the causative variants could not successfully be mapped by linkage","","https://genomeinterpretation.org/cagi2-mouse-exomes.html","completed","14","","\N","2011-10-06","2023-09-28 18:19:48","2023-10-12 17:45:19" +"236","cagi3-mrn-mre11","CAGI3: MRE11","Genomes are subject to constant threat by damaging agents that generate dna","Predict probability of pathogenicity (a number between 0 and 1) for individual rare variants of MRE11 and NBS1.","","https://genomeinterpretation.org/cagi3-mrn.html","completed","14","","\N","2013-04-25","2023-09-28 18:19:48","2023-11-15 22:47:19" +"237","cagi4-naglu","CAGI4: NAGLU","Predicting enzymatic activity of NAGLU mutants","NAGLU is a lysosomal glycohydrolyase. Deficiency of NAGLU causes the rare disorder Mucopolysaccharidosis IIIB or Sanfilippo B disease. Naturally occurring NAGLU mutants have been assayed for enzymatic activity in transfected cell lysates. The challenge is to predict the fractional activity of each mutant protein compared to the wild-type enzyme.","","https://genomeinterpretation.org/cagi4-naglu.html","completed","14","","\N","2016-04-04","2023-09-28 18:19:48","2023-11-15 22:47:24" +"238","cagi4-npm-alk","CAGI4: NPM: ALK","Predicting kinase activity of NPM-ALK fusion mutants","NPM-ALK is a fusion protein in which the ALK tyrosine kinase is constitutively activated, contributing to cancer. NPM-ALK constructs with mutations in the kinase domain have been assayed in extracts of transfected cells. The challenge is to predict the kinase activity and the Hsp90 binding affinity of the mutant proteins relative to the reference NPM-ALK fusion protein.","","https://genomeinterpretation.org/cagi4-npm-alk.html","completed","14","","\N","2016-04-04","2023-09-28 18:19:48","2023-11-15 22:47:32" +"239","cagi3-mrn-nbs1","CAGI3: NBS1","Predicting Pathogenicity of Rare MRE11 and NBS1 Variants","Predict probability of pathogenicity (a number between 0 and 1) for individual rare variants of MRE11 and NBS1.","","https://genomeinterpretation.org/cagi3-mrn.html","completed","14","","\N","2013-04-25","2023-09-28 18:19:48","2023-10-16 18:38:55" +"240","cagi3-p16","CAGI3: p16","Assessing p16 protein variants' effects on cell growth","Evaluate how different variants of p16 protein impact its ability to block cell proliferation.","","https://genomeinterpretation.org/cagi3-p16.html","completed","14","","\N","2013-04-25","2023-09-28 18:19:48","2023-10-20 23:28:57" +"241","cagi2-p53","CAGI2: p53 reactivation","Predictors are asked to submit predictions on the effect of the cancer rescue","The transcription factor p53 is a central tumor suppressor protein that controls DNA repair, cell cycle arrest, and apoptosis (programmed cell death). About half of human cancers have p53 mutations that inactivate p53. Over 250,000 US deaths yearly are due to tumors that express full-length p53 that has been inactivated by a single point mutation. For the past several years, the group of Rick Lathrop at University of California, Irvine, has been engaged in a complete functional census of p53 second-site suppressor (“cancer rescue”) mutations. These cancer rescue mutations are additional amino acids changes (to otherwise cancerous p53 mutations), which have been found to rescue p53 tumor suppressor function, reactivating otherwise inactive p53. These intragenic rescue mutations reactivate cancer mutant p53 in yeast and human cell assays by providing structural changes that compensate for the cancer mutation.","","https://genomeinterpretation.org/cagi2-p53.html","completed","14","","\N","2011-10-06","2023-09-28 18:19:48","2023-10-20 23:28:58" +"242","cagi1-pgp","CAGI1: PGP","CAGI challenges utilizing public genomic and phenotypic data resources","Participants in the project make their full sequence and phenotypic profile data publicly available. The four CAGI challenges were based on prerelease samples from this resource.","","https://genomeinterpretation.org/cagi1-pgp.html","completed","14","","\N","2010-12-10","2023-09-28 18:19:48","2023-09-27 21:05:22" +"243","cagi2-pgp","CAGI2: PGP","CAGI challenges utilizing public genomic and phenotypic data resources","Participants in the project make their full sequence and phenotypic profile data publicly available. The four CAGI challenges were based on prerelease samples from this resource.","","https://genomeinterpretation.org/cagi2-pgp.html","completed","14","","\N","2011-10-06","2023-09-28 18:19:48","2023-09-27 21:05:23" +"244","cagi3-pgp","CAGI3: PGP","CAGI challenges utilizing public genomic and phenotypic data resources","Participants in the project make their full sequence and phenotypic profile data publicly available. The four CAGI challenges were based on prerelease samples from this resource.","","https://genomeinterpretation.org/cagi3-pgp.html","completed","14","","\N","2013-04-25","2023-09-28 18:19:48","2023-09-27 21:05:23" +"245","cagi4-pgp","CAGI4: PGP","CAGI challenges utilizing public genomic and phenotypic data resources","Participants in the project make their full sequence and phenotypic profile data publicly available. The four CAGI challenges were based on prerelease samples from this resource.","","https://genomeinterpretation.org/cagi4-pgp.html","completed","14","","\N","2016-04-04","2023-09-28 18:19:48","2023-11-01 22:26:17" +"246","cagi4-pyruvate-kinase","CAGI4: Pyruvate kinase","Predicting mutation impacts on pyruvate kinase activity and regulation","Pyruvate kinase catalyzes the last step in glycolysis and is regulated by allosteric effectors. Variants in the gene encoding the isozymes expressed in red blood cells and liver, including missense variants mapping near the effector binding sites, cause PK deficiency. A large set of single amino acid mutations in the liver enzyme has been assayed in E. coli extracts for the effect on allosteric regulation of enzyme activity. The challenge is to predict the impacts of mutations on enzyme activity and allosteric regulation.","","https://genomeinterpretation.org/cagi4-pyruvate-kinase.html","completed","14","","\N","2015-01-11","2023-09-28 18:19:48","2023-11-01 22:26:25" +"247","cagi2-rad50","CAGI2: RAD50","Assessing RAD50 variants for breast cancer risk","RAD50 is a candidate intermediate-risk breast cancer susceptibility gene. The RAD50 data provided for CAGI challenge include a list of potentially interesting sequence variants observed from sequencing RAD50 gene in about 1,400 breast cancer cases and 1,200 ethnically matched controls. Variants in the list were observed between 1 and 20 times.","","https://genomeinterpretation.org/cagi2-rad50.html","completed","14","","\N","2011-10-06","2023-09-28 18:19:48","2023-11-15 22:47:40" +"248","cagi2-risksnps","CAGI2: riskSNPs","Exploring molecular mechanisms linking SNPs to disease risk","The goal of this experiment is to explore current understanding of the molecular level mechanisms underlying associations between SNPs and disease risk, incorporating expertise in each of the known mechanism areas, and as far as possible assigning possible mechanisms for each association locus. The correct mechanisms are unknown, so there can be no ranking of accuracy-that is not the point of the experiment. Rather, the goal is to ascertain which mechanisms appear most relevant, how confidently they can be assigned, and what fraction of loci can currently be assigned plausible mechanisms.","","https://genomeinterpretation.org/cagi2-risksnps.html","completed","14","","\N","2011-10-06","2023-09-28 18:19:48","2023-10-19 23:33:11" +"249","cagi3-risksnps","CAGI3: riskSNPs","Exploring molecular mechanisms linking SNPs to disease risk","The goal of this experiment is to explore current understanding of the molecular level mechanisms underlying associations between SNPs and disease risk, incorporating expertise in each of the known mechanism areas, and as far as possible assigning possible mechanisms for each association locus. The correct mechanisms are unknown, so there can be no ranking of accuracy-that is not the point of the experiment. Rather, the goal is to ascertain which mechanisms appear most relevant, how confidently they can be assigned, and what fraction of loci can currently be assigned plausible mechanisms.","","https://genomeinterpretation.org/cagi3-risksnps.html","completed","14","","\N","2013-04-25","2023-09-28 18:19:48","2023-10-19 23:33:13" +"250","cagi2-nav1-5","CAGI2: SCN5A","Predict the effect of SCN5A mutants in cardiac electrophysiology","The cardiac action potential (AP) is the sum of a number of distinct ionic currents. It can be divided into five phases (phase 0‐4). From pacemaker cells of the SA node the initial depolarizing wave front will spread throughout the cardiomyocytes via gap junctions. If the depolarization is sufficient voltage‐dependent sodium channels (Nav1.5) are activated and allow Na+ influx. This results in a further depolarization of the membrane which will lead to opening of even more Nav channels. This positive feedback mechanism is seen as the rapid upstroke in the initial phase (phase 0) of the action potential. Nav1.5 is encoded by SCN5A and mutations in this gene have been associated with various diseases such as Atrial fibrillation, Long QT syndrome, Cardiac Conduction Defect, Sick Sinus Disease, and Brugada Syndrome (BrS).","","https://genomeinterpretation.org/cagi2-nav1.5.html","completed","14","","\N","2011-10-06","2023-09-28 18:19:48","2023-11-14 19:36:54" +"251","cagi2-mr-1","CAGI2: Shewanella oneidensis strain MR-1","How MR-1 affect the fitness of that gene in a given condition","Predictors are asked to submit predictions on how insertions in the given gene of MR-1 affect the fitness of that gene in a given condition (stressor).","","https://genomeinterpretation.org/cagi2-mr-1.html","completed","14","","\N","2011-10-06","2023-09-28 18:19:55","2023-11-14 19:37:40" +"252","cagi3-mr-1","CAGI3: Shewanella oneidensis strain MR-1","How MR-1 affect the fitness of that gene in a given condition","Predictors are asked to submit predictions on how insertions in the given gene of MR-1 affect the fitness of that gene in a given condition (stressor).","","https://genomeinterpretation.org/cagi3-mr-1.html","completed","14","","\N","2013-04-25","2023-09-28 18:20:01","2023-11-14 19:37:47" +"253","cagi4-sickkids","CAGI4: SickKids","Match genome sequence to clinical descriptions","Realizing the promise of precision medicine will require developing methods for interpreting genome sequence data to infer individuals’ phenotypic traits and predispositions to disease. This challenge involves 25 children with suspected genetic disorders who were referred for clinical genome sequencing. Predictors are given their genome sequences and their clinical phenotypic descriptions, as provided to the diagnostic laboratory, and asked to predict which genome corresponds to which clinical description. Additionally, identify the diagnostic variants underlying the predictions. Optionally, identify predictive secondary variants conferring high risk of other diseases whose phenotypes are not reported in the clinical descriptions.","","https://genomeinterpretation.org/cagi4-sickkids.html","completed","14","","\N","2016-04-04","2023-09-28 18:19:48","2023-11-14 19:38:30" +"254","cagi4-sumo-ligase","CAGI4: SUMO ligase","Predict effect of the variants on SUMO ligase","SUMO ligase identifies target proteins and covalently attaches SUMO to them, thereby modulating the functions of hundreds of proteins including proteins implicated in cancer, neurodegeneration, and other diseases. A large library of missense mutations in human SUMO ligase has been assessed for competitive growth in a high-throughput yeast-based complementation assay. The challenge is to predict the effect of mutations on function, as measured by the change in fractional representation of each mutant SUMO ligase clone, relative to wild-type clones, in a competitive yeast growth assay.","","https://genomeinterpretation.org/cagi4-sumo-ligase.html","completed","14","","\N","2016-04-04","2023-09-28 18:19:48","2023-11-14 19:38:48" +"255","cagi3-splicing","CAGI3: TP53 splicing","Which TP53 mutations potentially contribute to cancer","The function of exonic splicing regulatory elements can be undermined by DNA sequence variation and in some cases can contribute to pathogenesis. Thousands of disease-causing mutations disrupt exonic splicing regulatory elements. These data suggest that >25 percent of missense mutations may impact pre-mRNA splicing rather than mRNA translation. Using minigene constructs derived from a fragment of the TP53 gene, we have experimentally determined if each mutation influences splicing fidelity in HEK293T cells. We hope that CAGI participants will be able to predict the outcome of our experiments. A long-term goal will be the computational prioritization of disease-causing mutations prior to experimental validation. This contribution is expected to have major impacts in understanding the pathogenic basis of disease-causing mutations.","","https://genomeinterpretation.org/cagi3-splicing.html","completed","14","","\N","2013-04-25","2023-09-28 18:19:48","2023-11-14 19:39:00" +"256","cagi4-warfarin","CAGI4: Warfarin exomes","Predict the therapeutic doses of warfarin","With over 33 million prescriptions in 2011, warfarin is the most commonly used anticoagulant for preventing thromboembolic events. Warfarin has a twenty-fold inter-individual dose variability and a narrow therapeutic index, and it is responsible for a third of adverse drug event hospitalizations in older Americans [2]. Alternatives to warfarin, such as direct thrombin inhibitors and factor Xa inhibitors, are now available. However, these are more expensive, irreversible, and may cause a higher rate of acute coronary events compared to warfarin [3,4]. Thus, warfarin remains a mainstay of anticoagulant therapy, and better methods of dosing warfarin will lead to fewer adverse events due to overcoagulation.","","https://genomeinterpretation.org/cagi4-warfarin.html","completed","14","","\N","2016-04-04","2023-09-28 18:19:48","2023-11-14 19:39:08" +"257","cagi6-calmodulin","CAGI6: Calmodulin","Predict competitive growth score of different Calmodulin variants","Calmodulin (CaM) is a ubiquitous calcium (Ca2+) sensor protein interacting with more than 200 molecular partners, thereby regulating a variety of biological processes. Missense point mutations in the genes encoding CaM have been associated with ventricular tachycardia and sudden cardiac death. A library encompassing up to 17 point mutations was assessed by far-UV circular dichroism (CD) by measuring melting temperature (Tm) and percentage of unfolding (%unfold) upon thermal denaturation at pH and salt concentration that mimic the physiological conditions. The challenge is to predict- the Tm and %unfold values for isolated CaM variants under Ca2+-saturating conditions (Ca2+-CaM) and in the Ca2+-free (apo) state; whether the point mutation stabilizes or destabilizes the protein (based on Tm and %unfold).","","https://genomeinterpretation.org/cagi6-cam.html","completed","1","","\N","2021-12-31","2023-09-28 18:19:48","2023-11-15 22:47:52" +"258","cagi2-splicing","CAGI2: splicing","Compare exons to understand the mechanisms underlying pre-mRNA splicing errors","Accurate precursor mRNA (pre-mRNA) splicing is required for the expression of protein coding genes from the human genome. In this process, intervening sequences (introns) are removed from pre-mRNA and coding/regulatory sequences (exons) are ligated together generating a mature mRNA. A large ribonucleoprotein machine called the spliceosome assembles de novo upon every nascent intron and catalyzes the chemical steps of splicing.","","https://genomeinterpretation.org/cagi2-splicing.html","completed","14","","\N","2011-10-06","2023-09-28 18:19:48","2023-10-18 15:32:55" +"259","cagi6-lc-arsa","CAGI6: ARSA","Predict the effect of naturally occurring missense mutations","Metachromatic Leukodystrophy (MLD) is an autosomal recessive, lysosomal-storage disease caused by mutations in Arylsulfatase A (ARSA) and toxic accumulation of sulfatide substrate. Genome sequencing has revealed hundreds of protein-altering, ARSA missense variants, but the functional effect of most variants remains unknown. ARSA enzyme activity using a high-throughput cellular assay was measured for a large set of variants of known significance and variants of unknown significance. The challenge is to predict the fractional enzyme activity of each mutant protein compared to the wildtype protein.","","https://genomeinterpretation.org/cagi6-lc-arsa.html","completed","1","","\N","2022-11-16","2023-09-28 18:20:23","2023-11-14 19:39:42" +"260","predict-hits-for-the-wdr-domain-of-lrrk2","CACHE1: Predict Hits for The WDR Domain of LRRK2","Finding ligands targeting the central cavity of the WDR domain of LRRK2","The first CACHE Challenge target is LRRK2, the most commonly mutated gene in familial Parkinson's Disease. Participants are asked to find hits for the WD40 repeat (WDR) domain of LRRK2. Read more under Details below.","","https://cache-challenge.org/challenges/predict-hits-for-the-wdr-domain-of-lrrk2","completed","17","","2021-12-01","2022-01-31","2023-09-27 19:01:55","2023-11-14 19:39:53" +"261","finding-ligands-targeting-the-conserved-rna-binding-site-of-sars-cov-2-nsp13","CACHE2: Finding Ligands Targeting The Conserved RNA Binding Site of SARS-CoV-2 NSP13","Target the NSP13 helicase of SARS-CoV-2","Predicted compounds will be procured and tested at CACHE using both enzymatic and binding assays","","https://cache-challenge.org/challenges/finding-ligands-targeting-the-conserved-rna-binding-site-of-sars-cov-2-nsp13","completed","17","","2022-06-22","2022-09-04","2023-09-27 19:02:43","2023-11-14 19:41:01" +"262","finding-ligands-targeting-the-macrodomain-of-sars-cov-2-nsp3","CACHE3: Finding ligands targeting the macrodomain of SARS-CoV-2 Nsp3","Study the macrodomain of SARS-CoV-2 Nsp3 for potential therapeutic applications","To predict ligands that bind to the ADPr site of SARS-CoV-2 Nsp3 macrodomain (Mac1).","","https://cache-challenge.org/challenges/finding-ligands-targeting-the-macrodomain-of-sars-cov-2-nsp3","completed","17","","2022-11-02","2023-01-01","2023-09-27 19:03:13","2023-10-16 19:01:19" +"263","finding-ligands-targeting-the-tkb-domain-of-cblb","CACHE4: Finding ligands targeting the TKB domain of CBLB","Investigate the TKB domain of CBLB to discover novel compounds for treatment","Predict compounds that bind to the closed conformation of the CBLB TKB domain with novel chemical templates and KD below 30 micromolar.","","https://cache-challenge.org/challenges/finding-ligands-targeting-the-tkb-domain-of-cblb","completed","17","","2023-03-09","2023-05-09","2023-09-27 19:03:14","2023-10-16 19:01:22" +"264","rare-disease-ai-hackathon","Rare Disease AI Hackathon","Advance rare disease diagnosis using artificial intelligence (AI) models","Bring AI and medical experts together to build open source models for rare diseases. Create zero-barrier access to rare disease expertise for patients, researchers and physicians. Use AI to Uncover novel links between rare diseases. Establish validation methods for medical AI models. Jumpstart an open source community for rare disease AI models. Launch models for Beta testing on Hypophosphatasia.ai and EhlersDanlos.ai.","","https://www.rarediseaseaihackathon.org/","active","14","","2023-09-30","2024-01-15","2023-09-27 19:10:40","2023-11-11 07:01:13" +"265","cometh-benchmark","COMETH Benchmark","Quantify tumor heterogeneity","Successful treatment of cancer is still a challenge and this is partly due to a wide heterogeneity of cancer composition across patient population. Unfortunately, accounting for such heterogeneity is very difficult. Clinical evaluation of tumor heterogeneity often requires the expertise of anatomical pathologists and radiologists.This benchmark is dedicated to the quantification of intra-tumor heterogeneity using appropriate statistical methods on cancer omics data.In particular, it focuses on estimating cell types and proportion in biological samples based on methylation and methylome data sets. The goal is to explore various statistical methods for source separation/deconvolution analysis (Non-negative Matrix Factorization, Surrogate Variable Analysis, Principal component Analysis, Latent Factor Models, ...) using both RNA-seq and methylome data.","","https://www.codabench.org/competitions/218/","completed","10","","2020-06-14","2020-12-29","2023-09-28 23:25:52","2023-11-14 19:41:05" +"266","the-miccai-2014-machine-learning-challenge","The MICCAI 2014 Machine Learning Challenge","Predict binary and continuous phenotypes from Structural Brain MRI","Machine learning tools are increasingly applied to brain MRI scans for predicting individual-level clinical phenotypes. Despite methodological advancements, benchmark studies with standardized datasets are scarce, hindering tool validation and comparison. The MICCAI 2014 Machine Learning Challenge (MLC) addresses this gap, utilizing four large-scale (N > 70) brain MRI datasets with clinically relevant phenotypes. The aim is to showcase the current state of neuroimage-based prediction, drawing machine-learning practitioners to MICCAI and medical image computing. MICCAI 2014 MLC complements the main conference, the Machine Learning in Medical Imaging Workshop, and the CADDementia challenge focused on Alzheimer's diagnosis from brain MR scans.","","https://competitions.codalab.org/competitions/1471","completed","9","","2014-04-16","2014-06-14","2023-09-28 23:36:12","2023-11-14 19:41:17" +"267","cagi6-annotate-all-missense","CAGI6: Annotate All Missense","Predict the functional effect of every coding SNV in the human genome","dbNSFP currently describes 81,782,923 possible protein-altering variants in the human genome. The challenge is to predict the functional effect of every such variant. For the vast majority of these missense and nonsense variants, the functional impact is not currently known, but experimental and clinical evidence is accruing rapidly. Rather than drawing upon a single discrete dataset as typical with CAGI, predictions will be assessed by comparing with experimental or clinical annotations made available after the prediction submission date, on an ongoing basis. If predictors assent, predictions will also be incorporated into dbNSFP.","","https://genomeinterpretation.org/cagi6-annotate-all-missense.html","completed","1","","2021-06-01","2021-10-11","2023-06-23 00:00:00","2023-11-15 22:48:16" +"268","cagi6-hmbs","CAGI6: HMBS","Submit the fitness score for each of the variants in the HMBS gene","Hydroxymethylbilane synthase (HMBS), also known as porphobilinogen deaminase (PBGD) or uroporphyrinogen I synthase, is an enzyme involved in heme production. In humans, variants that affect HMBS function result in acute intermittent porphyria (AIP), an autosomal dominant genetic disorder caused by a build-up of porphobilinogen in the cytoplasm. A large library of HMBS missense variants was assessed with respect to their effects on protein function using a high-throughput yeast complementation assay. The challenge is to predict the functional effects of these variants.","","https://genomeinterpretation.org/cagi6-hmbs.html","completed","1","","2021-06-08","2021-10-11","2023-06-23 00:00:00","2023-11-15 22:48:31" +"269","cagi6-id-panel","CAGI6: Intellectual Disability Panel","Analyze data of Intellectual Disability Panel to identify causative variants","The objective in this challenge is to predict a patient's clinical phenotype and the causal variant(s) based on their gene panel sequences. Sequence data for 74 genes from a cohort of 500 patients with a range of neurodevelopmental presentations (intellectual disability, autistic spectrum disorder, epilepsy, microcephaly, macrocephaly, hypotonia, ataxia) has been made available for this challenge. Additional data from 150 patients from the same clinical study is available for training and validation.","","https://genomeinterpretation.org/cagi6-id-panel.html","completed","1","","2021-06-08","2021-10-11","2023-06-23 00:00:00","2023-11-14 19:43:25" +"270","cagi6-mapk1","CAGI6: MAPK1","Predict the ΔΔG(H2O) value for the MAPK1","MAPK1 (ERK2) is active as serine/threonine kinase in the Ras-Raf-MEK-ERK signal transduction cascade that regulates cell proliferation, transcription, differentiation, and cell cycle progression. MAPK1 is activated by phosphorylation which occurs with strict specificity by MEK1/2 on Thr185 and Tyr187, and may also act as a transcriptional repressor independent of its kinase activity. A library of eleven missense variants selected from the COSMIC database was assessed by near and far-UV circular dichroism and intrinsic fluorescence spectra to determine thermodynamic stability at different concentrations of denaturant. These data were used to calculate a ΔΔGH20 value; i.e., the difference in unfolding free energy ΔGH20 between each variant and the wildtype protein, both in phosphorylated and unphosphorylated forms. The challenge is to predict these two ΔΔGH20 values and the catalytic efficiency (kcat/km)mut/(kcat/km)wt, as determined by a fluorescence assay, of the phosphorylated fo...","","https://genomeinterpretation.org/cagi6-mapk1.html","completed","1","","2021-07-08","2021-10-11","2023-06-23 00:00:00","2023-11-15 22:48:43" +"271","cagi6-mapk3","CAGI6: MAPK3","Predict the ΔΔG(H2O) value for the MAPK3","MAPK3 (ERK1) is active as serine/threonine kinase in the Ras-Raf-MEK-ERK signal transduction cascade that regulates cell proliferation, transcription, differentiation, and cell cycle progression. MAPK3 is activated by phosphorylation which occurs with strict specificity by MEK1/2 on Thr202 and Tyr204, and may also act as a transcriptional repressor independent of its kinase activity. A library of twelve missense variants selected from the COSMIC database was assessed by near and far-UV circular dichroism and intrinsic fluorescence spectra to determine thermodynamic stability at different concentrations of denaturant. These data were used to calculate a ΔΔGH20 value; i.e., the difference in unfolding free energy ΔGH20 between each variant and the wildtype protein, both in phosphorylated and unphosphorylated forms. The challenge is to predict these two ΔΔGH20 values and the catalytic efficiency (kcat/km)mut/(kcat/km)wt, as determined by a fluorescence assay, of the phosphorylated fo...","","https://genomeinterpretation.org/cagi6-mapk3.html","completed","1","","2021-08-04","2021-10-11","2023-06-23 00:00:00","2023-11-15 22:48:47" +"272","cagi6-mthfr","CAGI6: MTHFR","Submit predictions for each missense variant in the MTHFR","Methylenetetrahydrofolate reductase (MTHFR) catalyzes the production of 5-methyltetrahydrofolate, which is needed for conversion of homocysteine to methionine. Humans with variants affecting MTHFR function present with a wide range of phenotypes, including homocystinuria, homocysteinemia, developmental delay, severe mental retardation, psychiatric disturbances, and late-onset neurodegenerative disorders. A further complication to interpretation of variants in this gene is a common variant, Ala222Val, carried by a large fraction of the human population. A large library of MTHFR missense variants was assessed with respect to their effects on protein function using a high-throughput yeast complementation assay. The challenge is to predict the functional effects of these variants in two different settings- for the wildtype protein, and for the protein with the common Ala222Val variant.","","https://genomeinterpretation.org/cagi6-mthfr.html","completed","1","","2021-05-03","2021-06-30","2023-06-23 00:00:00","2023-11-15 22:48:59" +"273","cagi6-prs","CAGI6: Polygenic Risk Scores","Estimate polygenic risk scores (PRS) for complex diseases","Polygenic risk scores (PRS) have potential clinical utility for risk surveillance, prevention and personalized medicine. Participants will be provided with datasets of four real phenotypes (Type 2 Diabetes, Breast Cancer, Inflammatory Bowel Disease and Coronary Artery Disease) and of thirty simulated phenotypes representing a range of genetic architectures of common polygenic diseases. The challenge is to predict the disease outcomes of individuals in held-out validation cohorts.","","https://genomeinterpretation.org/cagi6-prs.html","completed","1","","2021-06-08","2021-10-11","2023-06-23 00:00:00","2023-11-14 19:42:40" +"274","cagi6-rgp","CAGI6: Rare Genomes Project","Identify causative variants in rare disease genomes for diagnosis","The Rare Genomes Project (RGP) is a direct-to-participant research study on the utility of genome sequencing for rare disease diagnosis and gene discovery. The study is led by genomics experts and clinicians at the Broad Institute of MIT and Harvard. Research subjects are consented for genomic sequencing and the sharing of their sequence and phenotype information with researchers working to understand the molecular causes of rare disease. When a candidate disease variant believed to be related to the phenotype is identified, the variant is confirmed with Sanger sequencing in a clinical setting and returned to the participant via his or her local physician. In this challenge, whole genome sequence data and phenotype data from a subset of the solved and unsolved RGP families will be provided. Participants in the challenge will try to identify the causative variant(s) in each case. For the unsolved cases, prioritized variants from the participating teams will be examined to see if ad...","","https://genomeinterpretation.org/cagi6-rgp.html","completed","1","","2021-06-08","2021-10-11","2023-06-23 00:00:00","2023-10-12 18:12:27" +"275","cagi6-invitae","CAGI6: Sherloc clinical classification","122,000 coding variants predicted for ClinVar","Invitae is a genetic testing company that publishes their variant interpretations to ClinVar. In this challenge, over 122,000 previously uncharacterized variants are provided, spanning the range of effects seen in the clinic. Following the close of this challenge, Invitae will submit their interpretations for these variants to ClinVar. Predictors are asked to interpret the pathogenicity of these variants, and the clinical utility of predictions will be assessed across multiple categories by Invitae.","","https://genomeinterpretation.org/cagi6-invitae.html","completed","1","","2021-07-08","2021-12-01","2023-06-23 00:00:00","2023-11-16 17:44:21" +"276","cagi6-splicing-vus","CAGI6: Splicing VUS","Predict whether vus disrupt splicing and contribute to genetic disorders","Variants causing aberrant splicing have been implicated in a range of common and rare disorders, including retinitis pigmentosa, autism spectrum disorder, amyotrophic lateral sclerosis, and a variety of cancers. However, such variants are frequently overlooked by diagnostic sequencing pipelines, leading to missed diagnoses for patients. Clinically ascertained variants of unknown significance underwent whole-blood based RT-PCR to test for impact on splicing. The challenge is to predict which of the tested variants disrupt splicing.","","https://genomeinterpretation.org/cagi6-splicing-vus.html","completed","1","","2021-06-08","2021-10-11","2023-06-23 00:00:00","2023-11-14 19:44:47" +"277","cagi6-stk11","CAGI6: STK11","Impact of variants in STK11 gene for Peutz-Jeghers syndrome","Serine/Threonine Kinase 11 (STK11) is considered a master kinase that functions as a tumor suppressor and nutrient sensor within a heterotrimeric complex with pseudo-kinase STRAD-alpha and structural protein MO25. Germline variants resulting in loss of STK11 define Peutz-Jaghers Syndrome, an autosomal dominant cancer predisposition syndrome marked by gastrointestinal hamartomas and freckling of the oral mucosa. Somatic loss of function variants, both nonsense and missense, occur in 15-30% of non-small cell lung adenocarcinomas, where they correlate clinically with insensitivity to anti-PD1 monoclonal antibody therapy. The challenge is to predict the impact on STK11 function for each missense variant in relation to wildtype STK11.","","https://genomeinterpretation.org/cagi6-stk11.html","completed","1","","2021-06-08","2021-09-01","2023-06-23 00:00:00","2023-11-16 17:44:00" +"278","qbi-hackathon","QBI hackathon","The QBI hackathon","The QBI hackathon is a 48-hour event connecting the vibrant Bay Area developer community with the scientists from UCSF, UCB and UCSC, during which we work together on the cutting edge biomedical problems. Advances in computer vision, AI, and machine learning have enabled computers to pick out cat videos, recognize people’s faces from photos, play video games and drive cars. More recently, application of deep neural nets to protein structure prediction completely revolutionized the field. We look forward to seeing how far we can push science ahead when we apply these latest algorithms to biomedically relevant light microscopy, electron microscopy, and proteomics data. If you love FFTs, transformers, language models, topological data processing, or simply writing code, this is your chance to apply your skills to make an impact on global healthcare. Beyond the actual event, we hope to establish a better connection between talented developers and scientists in the Bay Area, so that we...","","https://www.eventbrite.com/e/qbi-hackathon-2023-tickets-633794304827?aff=oddtdtcreator","completed","14","","2023-11-04","2023-11-05","2023-10-06 21:22:51","2023-11-15 22:49:20" +"279","niddk-central-repository-data-centric-challenge","NIDDK Central Repository Data-Centric Challenge","Enhance NIDDK datasets for future Artificial Intelligence (AI) applications","The National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Central Repository (https://repository.niddk.nih.gov/home/) is conducting a Data Centric Challenge aimed at augmenting existing Repository data for future secondary research including data-driven discovery by artificial intelligence (AI) researchers. The NIDDK Central Repository (NIDDK-CR) program strives to increase the utilization and impact of the resources under its guardianship. However, lack of standardization and consistent metadata within and across studies limit the ability of secondary researchers to easily combine datasets from related studies to generate new insights using data science methods. In the fall of 2021, the NIDDK-CR began implementing approaches to augment data quality to improve AI-readiness by making research data FAIR (findable, accessible, interoperable, and reusable) via a small pilot project utilizing Natural Language Processing (NLP) to tag study variables. In 2022, the NIDD...","","https://www.challenge.gov/?challenge=niddk-central-repository-data-centric-challenge","completed","14","","2023-09-20","2023-11-03","2023-10-18 16:58:17","2023-11-15 22:49:26" +"280","stanford-ribonanza-rna-folding","Stanford Ribonanza RNA Folding","A path to programmable medicine and scientific breakthroughs","Ribonucleic acid (RNA) is essential for most biological functions. A better understanding of how to manipulate RNA could help usher in an age of programmable medicine, including first cures for pancreatic cancer and Alzheimer’s disease as well as much-needed antibiotics and new biotechnology approaches for climate change. But first, researchers must better understand each RNA molecule's structure, an ideal problem for data science.","","https://www.kaggle.com/competitions/stanford-ribonanza-rna-folding","completed","8","","2023-08-23","2023-11-24","2023-10-23 20:58:06","2023-11-15 22:49:31" +"281","uls23","Universal Lesion Segmentation Challenge '23","Advancements, challenges, and a universal solution emerges","Significant advancements have been made in AI-based automatic segmentation models for tumours. Medical challenges focusing on e.g. Liver, kidney, or lung tumours have resulted in large performance improvements for segmenting these types of lesions. However, in clinical practice there is a need for versatile and robust models capable of quickly segmenting the many possible lesions types in the thorax-abdomen area. Developing a universal lesion segmentation (uls) model that can handle this diversity of lesions types requires a well-curated and varied dataset. Whilst there has been previous work on uls [6-8], most research in this field has made extensive use of a single partially annotated dataset [9], containing only the long- and short-axis diameters on a single axial slice. Furthermore, a test set containing 3d segmentation masks used during evaluation on this dataset by previous publications is not publicly available.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/747/ULS23_logo_aoB8tlx.png","https://uls23.grand-challenge.org/","active","5","","2023-10-29","2024-03-17","2023-11-02 15:35:22","2023-11-17 21:29:35" +"282","vessel12","VESSEL12","Assess methods for blood vessels in lung CT images","The VESSEL12 challenge compares methods for automatic (and semi-automatic) segmentation of blood vessels in the lungs from CT images.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/1/logo.png","https://vessel12.grand-challenge.org/","completed","5","https://doi.org/10.1016/j.media.2014.07.003","2011-11-25","2012-04-01","2023-11-08 00:42:00","2023-11-17 21:30:05" +"283","crass","CRASS","Invites participants to submit clavicle segmentation results","Crass stands for chest radiograph anatomical structure segmentation. The challenge currently invites participants to send in results for clavicle segmentation algorithms.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/5/logo.png","https://crass.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:09:56" +"284","anode09","ANODE09","Automatic pulmonary nodule detection systems in chest CT scans","ANODE09 is an initiative to compare systems that perform automatic detection of pulmonary nodules in chest CT scans on a single common database, with a single evaluation protocol.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/7/logo.png","https://anode09.grand-challenge.org/","completed","5","https://doi.org/10.1016/j.media.2010.05.005","\N","\N","2023-11-08 00:42:00","2023-11-17 23:17:55" +"285","cause07","CAUSE07","Compares algorithms for caudate nucleus segmentation in brain MRI scans","The goal of CAUSE07 is to compare different algorithms to segment the caudate nucleaus from brain MRI scans.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/8/logo.png","https://cause07.grand-challenge.org/","completed","5","","2007-10-26","\N","2023-11-08 00:42:00","2023-11-17 21:34:10" +"286","subsolidnodules","Subsolid Nodules","We present results of our segmentation method for subsolid lung nodules","We are presenting results of our segmentation method for subsolid lung nodules.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/10/logo.png","https://subsolidnodules.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-08 21:24:01" +"287","caddementia","CADDementia","Classification in AD, MCI, and healthy controls using MRI data","We seek algorithms that perform multi-class classification of patients with Alzheimer's disease (AD), patients with mild cognitive impairment (MCI) and healthy controls (CN) using multi-center structural MRI data.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/17/logo3_100.png","https://caddementia.grand-challenge.org/","completed","5","https://doi.org/10.1016/j.neuroimage.2015.01.048","\N","\N","2023-11-08 00:42:00","2023-11-17 23:18:33" +"288","mitos-atypia-14","MITOS-ATYPIA-14","Mitosis detection and nuclear atypia on breast cancer H&E stained images","MITOS & ATYPIA 14 contest, hosted by conference ICPR 2014 - detection of mitosis and evaluation of nuclear atypia on breast cancer H&E stained images","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/20/logo_mitos_atypia.png","https://mitos-atypia-14.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:19:06" +"289","lola11","LOLA11","Segmentation of lungs and lobes in chest CT scans","The goal of LOLA11 (LObe and Lung Analysis 2011) is to compare methods for (semi-)automatic segmentation of the lungs and lobes from chest computed tomography scans. Any team, whether from academia or industry, can join.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/39/lola11_web_GVIrfhf.png","https://lola11.grand-challenge.org/","active","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:19:28" +"290","promise12","PROMISE12","Segmentation algorithms for MRI of the prostate","The goal of this challenge is to compare interactive and (semi)-automatic segmentation algorithms for MRI of the prostate.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/40/promise12.png","https://promise12.grand-challenge.org/","completed","5","https://doi.org/10.1016/j.media.2013.12.002","\N","\N","2023-11-08 00:42:00","2023-11-14 19:48:34" +"291","camelyon16","CAMELYON16","Evaluating algorithms for automated cancer metastasis detection","The goal of this challenge is to evaluate new and existing algorithms for automated detection of cancer metastasis in digitized lymph node tissue sections. Two large datasets from both the radboud university medical center and the university medical center utrecht are provided.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/65/logo.png","https://camelyon16.grand-challenge.org/","completed","5","https://doi.org/10.1001/jama.2017.14585","2015-11-25","2016-04-01","2023-11-08 00:42:00","2023-11-11 01:44:54" +"292","isbi-aida","ISBI-AIDA","The isbi challenge focuses on evaluating endoscopic image analysis methods","The aim of this challenge is to bring together the community of researchers working on the various types of optical endoscopy at its multiple scales and different needs, to provide reference databases and reference results both for the imaging community and those interested in the translation to the clinical practice.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/67/logo.png","https://isbi-aida.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:50:12" +"293","luna16","LUNA16","Nodule detection algorithms for chest CT in a large-scale setting","The LUNA16 challenge will focus on a large-scale evaluation of automatic nodule detection algorithms for chest CT.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/71/luna16_logo.png","https://luna16.grand-challenge.org/","completed","5","https://doi.org/10.1016/j.media.2017.06.015","\N","\N","2023-11-08 00:42:00","2023-11-17 23:19:48" +"294","camelyon17","CAMELYON17","Automated detection and classification of breast cancer metastases","Automated detection and classification of breast cancer metastases in whole-slide images of histological lymph node sections. This task has high clinical relevance and would normally require extensive microscopic assessment by pathologists.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/80/camelyon17_logo.png","https://camelyon17.grand-challenge.org/","active","5","https://doi.org/10.1109/tmi.2018.2867350","2016-11-16","\N","2023-11-08 00:42:00","2023-11-11 01:45:01" +"295","retouch","RETOUCH","Detecting retinal fluid in optical coherence tomography images","Retinal OCT fluid challenge (RETOUCH) compares automated algorithms that are able to detect and segment different types of retinal fluid in optical coherence tomography (OCT).","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/111/retouch-logo.png","https://retouch.grand-challenge.org/","completed","5","https://doi.org/10.1109/tmi.2019.2901398","2017-04-03","\N","2023-11-08 00:42:00","2023-11-17 23:20:14" +"296","cataracts","CATARACTS","Image-based tool detection algorithms for cataract surgery","The challenge on automatic tool annotation for cataract surgery aims at evaluating image-based tool detection algorithms in the context of the most common surgical procedure in the world.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/130/logo.png","https://cataracts.grand-challenge.org/","completed","5","https://doi.org/10.1016/j.media.2018.11.008","\N","\N","2023-11-08 00:42:00","2023-11-14 19:48:56" +"297","tadpole","TADPOLE","Assesses Alzheimer's disease prediction of longitudinal evolution","The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) challenge is brought to you by the europond consortium in collaboration with the Alzheimer's Disease Neuroimaging Initiative (ADNI).","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/141/logo_gC1i5c5.png","https://tadpole.grand-challenge.org/","completed","5","https://arxiv.org/abs/2002.03419","\N","\N","2023-11-08 00:42:00","2023-11-17 23:21:11" +"298","coronare","CoronARe","Methods in coronary artery reconstruction using C-arm angiography","Coronare ranks state-of-the-art methods in symbolic and tomographic coronary artery reconstruction from interventional c-arm rotational angiography. Specifically, we will benchmark the performance of the methods using accurately pre-processed data, and study the effects of imperfect pre-processing conditions (segmentation and background subtraction errors). The evaluation will be performed in a controlled environment using digital phantom images.","","https://coronare.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-14 19:49:15" +"299","iciar2018-challenge","ICIAR 2018","Automatic detection of cancerous regions in breast cancer histology images","Can you develop a method for automatic detection of cancerous regions in breast cancer histology images?","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/176/logo_small.png","https://iciar2018-challenge.grand-challenge.org/","active","5","https://doi.org/10.1016/j.media.2019.05.010","2023-01-09","\N","2023-11-08 00:42:00","2023-11-14 19:49:22" +"300","sliver07","SLIVER07","Liver segmentation in clinical 3D CT scans in this competition","The goal of this competition is to compare different algorithms to segment the liver from clinical 3d computed tomography (CT) scans.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/178/splash2.jpg","https://sliver07.grand-challenge.org/","completed","5","https://doi.org/10.1109/tmi.2009.2013851","\N","\N","2023-11-08 00:42:00","2023-11-17 23:21:37" +"301","rocc","ROCC","DR disease in retina OCT volumes","Retinal OCT Classification Challenge (ROCC) is organized as a one day challenge in conjunction with MVIP2017. The goal of this challenge is to call different automated algorithms that are able to detect DR disease from normal retina on a common dataset of OCT volumes, acquired with topcon SD-OCT devices.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/180/logo.jpg","https://rocc.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:22:17" +"302","idrid","IDRiD","Retinal lesion segmentation, optic disc/fovea detection, and DR grading","This challenge evaluates automated techniques for analysis of fundus photographs. We target segmentation of retinal lesions like exudates, microaneurysms, and hemorrhages and detection of the optic disc and fovea. Also, we seek grading of fundus images according to the severity level of DR and DME.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/183/g2385.png","https://idrid.grand-challenge.org/","completed","5","https://doi.org/10.1016/j.media.2019.101561","\N","\N","2023-11-08 00:42:00","2023-11-17 23:22:36" +"303","empire10","EMPIRE10","Chest CT images; assess the accuracy of algorithms","The EMPIRE10 challenge was launched in early 2010 with an initial set of 20 scan pairs to be registered by participants in their own facility. This was followed in September by a workshop at the MICCAI 2010 conference where participants registered a further 10 scan pairs live within a 3 hour timeframe. This process and the results obtained are described in detail in Murphy et al., ""Evaluation of registration methods on thoracic CT: the EMPIRE10 challenge."", IEEE Trans Med Imaging. 2011 Nov;30(11):1901-20. Please cite this publication if you wish to reference the EMPIRE10 challenge. From this point forward all participants will be judged based on the full set of 30 scan pairs. New participants and new submissions are always welcome - in this way we hope that the EMPIRE10 website will continue to reflect the state of the art in registration of pulmonary CT images.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/186/logo.png","https://empire10.grand-challenge.org/","completed","5","https://doi.org/10.1109/tmi.2011.2158349","\N","\N","2023-11-08 00:42:00","2023-11-15 22:51:00" +"304","lumic","LUMIC","CT chest images using an anthropomorphic digital phantom","The LUMIC challenge tests the accuracy in registration between pre- and post-contrast CT chest images for algorithms, using an anthropomophic digital phantom.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/203/lumiclogo.png","https://lumic.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:22:52" +"305","continuousregistration","Continuous Registration","Submit your lung and brain registration method","Submit your method for lung and brain registration on https://github.com/superelastix/superelastix! Your method is easily accessible to end-users and automatically compiled, tested, and benchmarked weekly on several different data sets.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/207/logo.png","https://continuousregistration.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-14 19:50:44" +"306","drive","DRIVE","Develop a system to automatically segment vessels in human retina fundus images","The DRIVE database has been established to enable comparative studies on segmentation of blood vessels in retinal images. Retinal vessel segmentation and delineation of morphological attributes of retinal blood vessels, such as length, width, tortuosity, branching patterns and angles are utilized for the diagnosis, screening, treatment, and evaluation of various cardiovascular and ophthalmologic diseases such as diabetes, hypertension, arteriosclerosis and chorodial neovascularization. Automatic detection and analysis of the vasculature can assist in the implementation of screening programs for diabetic retinopathy, can aid research on the relationship between vessel tortuosity and hypertensive retinopathy, vessel diameter measurement in relation with diagnosis of hypertension, and computer-assisted laser surgery. Automatic generation of retinal maps and extraction of branch points have been used for temporal or multimodal image registration and retinal image mosaic synthesis. Mor...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/210/logo_drive.PNG","https://drive.grand-challenge.org/","active","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:51:30" +"307","curious2018","CuRIOUS 2018","MICCAI Challenge 2018 for brainshift correction with intra-operative ultrasound","Early brain tumor resection can effectively improve the patient’s survival rate. However, resection quality and safety can often be heavily affected by intra-operative brain tissue shift due to factors, such as gravity, drug administration, intracranial pressure change, and tissue removal. Such tissue shift can displace the surgical target and vital structures (e.g., blood vessels) shown in pre-operative images while these displacements may not be directly visible in the surgeon’s field of view. Intra-operative ultrasound (iUS) is a robust and relatively inexpensive technique to track intra-operative tissue shift and surgical tools, but to help update pre-surgical plans with this information, accurate and robust image registration algorithms are needed to relate pre-surgical MRI to iUS images. Despite the great progress so far, medical image registration techniques still have not made into the surgical room to directly benefit the patients with brain tumors. This challege/worksh...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/221/curious2018_logo.png","https://curious2018.grand-challenge.org/","completed","5","https://doi.org/10.1109/tmi.2019.2935060","\N","\N","2023-11-08 00:42:00","2023-11-15 22:51:50" +"308","refuge","REFUGE","Algorithms for glaucoma detection and optic disc/cup segmentation","The goal of the REtinal FUndus Glaucoma Challenge (REFUGE) is to evaluate and compare automated algorithms for glaucoma detection and optic disc/cup segmentation on a common dataset of retinal fundus images.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/229/logo_refuge_200x200.png","https://refuge.grand-challenge.org/","active","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:23:34" +"309","monuseg","MoNuSeg","Segmenting nuclei from H&E stained histopathological images","This challenge will showcase the best nuclei segmentation techniques that will work on a diverse set of H&E stained histology images obtained from different hospitals spanning multiple patients and organs. This will enable the training and testing of readily usable (or generalized) nuclear segmentation softwares.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/238/monuseg_logo.png","https://monuseg.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:52:09" +"310","paves","PAVES","Mra images for lower limb arterial occlusive disease planning","Peripheral artery:vein enhanced segmentation (PAVES) is the challenge focussed on providing easily interpretable and relevant images that can be readily understood by clinicians (vascular interventional radiologists & vascular surgeons) from mra datasets where the venous and arterial vasculature may be equally enhanced. The setting is lower limb arterial occlusive disease where imaging of the below knee arterial vasculature is critical in planning limb salvage interventions. However, the competing demands of the high spatial resolution needed to image small vessels versus imaging time constraints where there is often a very short arteriovenous transit time for contrast passage form arterial to venous compartments makes imaging challenging. While dynamic mra techniques can usually allow arterial imaging without venous ‚äòcontamination‚äô these necessarily sacrifice spatial resolution.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/243/paveslogo.png","https://paves.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:23:47" +"311","prostatex","PROSTATEx","Clinical significance of prostate lesions using MRI data","This challenge is the live continuation of the offline PROSTATEx Challenge (""SPIE-AAPM-NCI Prostate MR Classification Challenge”) that was held in conjunction with the 2017 SPIE Medical Imaging Symposium. In this challenge, the task is to predict the clinical significance of prostate lesions found in MRI data.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/258/prostatex-logo.jpg","https://prostatex.grand-challenge.org/","completed","5","","\N","2022-04-30","2023-11-08 00:42:00","2023-11-15 22:52:25" +"312","hc18","HC18","Measuring fetal head circumference using 2D ultrasound images","Automated measurement of fetal head circumference using 2D ultrasound images","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/265/HC18_LogoV1.png","https://hc18.grand-challenge.org/","active","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:23:58" +"313","anhir","ANHIR","Aligning multi-stained histology tissue samples","The challenge focuses on comparing the accuracy (using manually annotated landmarks) and the approximate speed of automatic non-linear registration methods for aligning microscopy images of multi-stained histology tissue samples.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/285/logo_sq_OdYGo3e.png","https://anhir.grand-challenge.org/","active","5","https://doi.org/10.1109/tmi.2020.2986331","\N","\N","2023-11-08 00:42:00","2023-11-14 19:51:43" +"314","breastpathq","BreastPathQ: Cancer Cellularity Challenge 2019","Develop a method for analyzing histology patches","SPIE-AAPM-NCI BreastPathQ:Cancer Circularity Challenge 2019: Participants will be tasked to develop an automated method for analyzing histology patches extracted from whole slide images and assign a score reflecting cancer cellularity for tumor burden assessment in each.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/296/spie_with_overlays.png","https://breastpathq.grand-challenge.org/","active","5","https://doi.org/10.1117/1.jmi.8.3.034501","\N","\N","2023-11-08 00:42:00","2023-11-17 23:27:13" +"315","chaos","CHAOS","Segment liver in CT data and liver, spleen, and kidneys in MRI data","In this challenge, you segment the liver in CT data, and segment liver, spleen, and kidneys in MRI data.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/298/logo_8sv4fA4_SWcTFEs.png","https://chaos.grand-challenge.org/","active","5","https://doi.org/10.1016/j.media.2020.101950","\N","\N","2023-11-08 00:42:00","2023-11-17 21:31:53" +"316","ead2019","EAD2019","Address multi-class artefact detection, region segmentation, and detection","Endoscopic artefact detection (EAD) is a core problem and needed for realising robust computer-assisted tools. The EAD challenge has 3 tasks: 1) multi-class artefact detection, 2) region segmentation, 3) detection generalisation.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/302/1772_A_M62_00022_1.jpg","https://ead2019.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:25:06" +"317","acdc-lunghp","ACDC-LungHP","Methods for whole-slide lung histopathology images","Automatic cancer detection and classification in whole-slide lung histopathology","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/305/logo.png","https://acdc-lunghp.grand-challenge.org/","active","5","","\N","\N","2023-11-08 00:42:00","2023-11-14 19:52:50" +"318","palm","PALM","Pathological Myopia diagnosis and fundus lesion segmentation in patients","The pathologic myopia challenge (PALM) focuses on the investigation and development of algorithms associated with the diagnosis of pathological myopia (PM) and segmentation of lesions in fundus photos from PM patients.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/307/palm-logo.jpg","https://palm.grand-challenge.org/","active","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:25:23" +"319","ichallenges","iChallenges","Eye image modalities, including REFUGE, PALM, RETOUCH, among others","We organized a serial of challenges on different eye image modalities, such as REFUGE, PALM, RETOUCH, etc.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/345/ichallenge.png","https://ichallenges.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:25:37" +"320","decathlon-10","Decathlon","Test machine learning algorithm generalizability across 10 different tasks","The medical segmentation decathlon challenge tests the generalisability of machine learning algorithms when applied to 10 different semantic segmentation task.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/350/background_dark_logo.png","https://decathlon-10.grand-challenge.org/","completed","5","https://doi.org/10.1038/s41467-022-30695-9","2022-07-21","2023-08-20","2023-11-08 00:42:00","2023-11-14 19:53:19" +"321","lyon19","LYON19","Develop methods for automatic lymphocyte detection in IHC stained specimens","Automatic Lymphocyte detection in IHC stained specimens.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/355/ban2_kpuoTJg.png","https://lyon19.grand-challenge.org/","active","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:27:28" +"322","kits19","KiTS19","Participate in the segmentation challenge for kidneys and kidney tumors in 2019","2019 Kidney and Kidney Tumor Segmentation Challenge","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/360/Screenshot_from_2019-01-02_17-23-36.png","https://kits19.grand-challenge.org/","active","5","https://arxiv.org/abs/1912.01054","\N","\N","2023-11-08 00:42:00","2023-11-17 23:27:36" +"323","paip2019","PAIP 2019","Address liver cancer segmentation and viable tumor burden estimation","PAIP2019: Liver Cancer Segmentation Task 1: Liver Cancer Segmentation Task 2: Viable Tumor Burden Estimation","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/370/Untitled_design.png","https://paip2019.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:27:53" +"324","orcascore","orCaScore","Coronary artery calcium scoring in cardiac CT scans","The purpose of the orCaScore challenge is to compare methods for automatic and semi-automatic coronary artery calcium scoring in cardiac CT scans. This evaluation framework was launched at the MICCAI 2014 workshops in Boston, USA, where we organized the Challenge on Automatic Coronary Calcium Scoring.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/378/00b670348bfdf4464e00c44310ec259f.jpg","https://orcascore.grand-challenge.org/","active","5","https://doi.org/10.1118/1.4945696","\N","\N","2023-11-08 00:42:00","2023-11-17 23:28:02" +"325","curious2019","curious2019","MRI to intra-operative ultrasound (iUS) before and after tumor resection","MICCAI Challenge 2019 for Correction of Brainshift with Intra-Operative Ultrasound. Taks 1: Register pre-operative MRI to iUS before tumor resection;Taks 2: Register iUS after tumor resection to iUS before tumor resection","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/380/CuRIOUS.png","https://curious2019.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:28:13" +"326","patchcamelyon","PatchCamelyon","Detect breast cancer metastasis in lymph nodes","PatchCamelyon is a new and challenging image classification dataset of 327.680 color images (96 x 96px) extracted from histopathology images of the CAMELYON16 challenge. The goal is to detect breast cancer metastasis in lymph nodes.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/381/Screen_Shot_2019-05-05_at_21.43.25.png","https://patchcamelyon.grand-challenge.org/","active","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:28:22" +"327","endovissub2019-scared","Stereo Correspondence and Reconstruction of Endoscopic Data","Address stereo correspondence and reconstruction challenges in endoscopic data","Stereo correspondence and reconstruction of endoscopic data","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/385/c7714704.jpg","https://endovissub2019-scared.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-08 00:58:30" +"328","verse2019","VerSe`19","Vertebrae labelling and segmentation on 150 CT scans","Vertebrae labelling and segmentation on a spine dataset on an unprecedented 150 CT scans with voxel-level vertebral annotations.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/388/logo_border.png","https://verse2019.grand-challenge.org/","active","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 21:30:59" +"329","gleason2019","Gleason2019","Methods for prostate cancer from H&E-stained histopathology images","MICCAI 2019 automatic prostate gleason grading challenge: this challenge aims at the automatic gleason grading of prostate cancer from h&e-stained histopathology images. This task is of critical importance because gleason score is a strong prognostic predictor. On the other hand, it is very challenging because of the large degree of heterogeneity in the cellular and glandular patterns associated with each gleason grade, leading to significant inter-observer variability, even among expert pathologists.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/391/GLEASON2019.png","https://gleason2019.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-14 20:00:08" +"330","age","AGE","Assess automatic methods for angle closure glaucoma evaluation","Angle closure glaucoma evaluation challenge","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/394/icon.png","https://age.grand-challenge.org/","active","5","","\N","\N","2023-11-08 00:42:00","2023-11-11 01:48:53" +"331","amd","iChallenge-AMD","Tackle challenges in age-related macular degeneration diagnosis and analysis","Age-related macular degeneration challenge","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/395/%E6%BC%94%E7%A4%BA%E6%96%87%E7%A8%BF1-2.png","https://amd.grand-challenge.org/","active","5","","\N","\N","2023-11-08 00:42:00","2023-11-08 00:58:34" +"332","structseg2019","StructSeg2019","Automated structure segmentation for radiotherapy planning","Welcome to automatic structure segmentation for radiotherapy planning challenge 2019. This competition is part of the MICCAI 2019 challenge.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/398/logo_aAzg3xS.jpg","https://structseg2019.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-14 19:54:50" +"333","digestpath2019","DigestPath2019","Algorithms for signet ring cell detection and colonoscopy tissue screening","The challenge aims to evaluate algorithms for signet ring cell detection and colonoscopy tissue screening in digestive system pathological images. It introduces the first public dataset for these tasks, providing expert-level annotations to advance research on automatic pathological object detection and lesion segmentation.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/399/digestpath-logo2.png","https://digestpath2019.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 18:40:29" +"334","odir2019","ODIR-2019","Compete in recognizing ocular diseases using morphological features","Peking university international competition on ocular disease intelligent recognition","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/402/logo.jpg","https://odir2019.grand-challenge.org/","active","5","","\N","\N","2023-11-08 00:42:00","2023-11-14 20:27:41" +"335","lysto","Lymphocyte Assessment Hackathon","Workshop for lymphocyte assessment in computational pathology","Lymphocyte assessment hackathon in conjunction with the MICCAI compay 2019 workshop on computational pathology","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/421/lysto_square.png","https://lysto.grand-challenge.org/","active","5","","\N","\N","2023-11-08 00:42:00","2023-11-14 19:55:01" +"336","aasce19","AASCE","Develop accurate automated methods for estimating spinal curvature","Accurate automated spinal curvature estimation","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/424/logo.png","https://aasce19.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-08 00:58:39" +"337","ecdp2020","HEROHE","Identify HER2-positive from HER2-negative breast cancer specimens","Unlike previous challenges, this proposes to find an image analysis algorithm to identify her2-positive from her2-negative breast cancer specimens evaluating only the morphological features present on the he slide, without the staining patterns of ihc.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/433/ECDP2020_square.jpg","https://ecdp2020.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-14 19:55:07" +"338","monusac-2020","MoNuSAC 2020","Address segmentation and classification of nuclei in multi-organ images","Multi-organ nuclei segmentation and classification challenge","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/445/logo.PNG","https://monusac-2020.grand-challenge.org/","completed","5","https://doi.org/10.13140/rg.2.2.12290.02244/1","\N","\N","2023-11-08 00:42:00","2023-11-08 00:58:42" +"339","endocv","EndoCV2020","Focus on artefact detection and disease detection in endoscopic images","Endoscopy computer vision challenge (endocv2020) introduces two core sub-themes in endoscopy: 1) artefact detection and segmentation (ead2020) and 2) disease detection and segmentation (edd2020).","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/462/endoLogo.png","https://endocv.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-14 19:55:17" +"340","lndb","LNDb Challenge","Determine nodule detection and characterization for lung cancer screening","Lung cancer screening and fleischner follow-up determination in chest CT through nodule detection, segmentation and characterization","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/470/thumbnail_lndb.png","https://lndb.grand-challenge.org/","active","5","https://arxiv.org/abs/1911.08434","\N","\N","2023-11-08 00:42:00","2023-11-17 21:31:00" +"341","verse2020","VerSe'20","Label and segment vertebrae on a diverse CT dataset","Vertebrae labelling and segmentation on a multi-centre, multi-scanner, and anatomically-diverse CT dataset.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/473/logo_border.png","https://verse2020.grand-challenge.org/","active","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 21:31:02" +"342","paip2020","PAIP2020","Classify molecular subtypes in colorectal cancers, predict MSI","Built on the success of its predecessor, paip2020 is the second challenge organized by the pathology AI platform (paip) and the seoul national university hospital (snuh). Paip2020 will proceed to not only detect whole tumor areas in colorectal cancers but also to classify their molecular subtypes, which will lead to characterization of their heterogeneity with respect to prognoses and therapeutic responses. All participants should predict one of the molecular carcinogenesis pathways, i.e., microsatellite instability(msi) in colorectal cancer, by performing digital image analysis without clinical tests. This task has a high clinical relevance as the currently used procedure requires an extensive microscopic assessment by pathologists. Therefore, those automated algorithms would reduce the workload of pathologists as a diagnostic assistance.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/480/paip2020_thumb_640x640.jpg","https://paip2020.grand-challenge.org/","active","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 21:33:31" +"343","ribfrac","RibFrac","Benchmark rib fracture detection and classification on 660 CT scans","Rib fracture detection and classification challenge: a large-scale benchmark of 660 CT scans with ~5,000 rib fractures (around 80gb)","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/482/challenge-logo-white_b8a8xbr.jpg","https://ribfrac.grand-challenge.org/","active","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 21:31:05" +"344","tn-scui2020","Thyroid Nodule Segmentation and Classification","Develop algorithms for thyroid nodules using a diverse ultrasound dataset","The main topic of this tn-scui2020 challenge is finding automatic algorithms to accurately classify the thyroid nodules in ultrasound images. It will provide the biggest public dataset of thyroid nodule with over 4500 patient cases from different ages, genders, and were collected using different ultrasound machines. Each ultrasound image is provided with its ground truth class (benign or maglinant) and a detailed delineation of the nodule. This challenge will provide a unique opportunity for participants from different backgrounds (e.g. academia, industry, and government, etc.) To compare their algorithms in an impartial way.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/484/Capture8888.PNG","https://tn-scui2020.grand-challenge.org/","active","5","","2022-01-20","\N","2023-11-08 00:42:00","2023-11-14 19:56:07" +"345","learn2reg","Learn2Reg","Address challenges in learning from small datasets","Challenge on medical image registration addressing: learning from small datasets; estimating large deformations; dealing with multi-modal scans; and learning from noisy annotations","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/486/logo_warped.png","https://learn2reg.grand-challenge.org/","active","5","https://doi.org/10.1109/tmi.2022.3213983","\N","\N","2023-11-08 00:42:00","2023-11-14 19:56:18" +"346","asoca","Automated Segmentation Of Coronary Arteries","Develop automated methods for segmentation of coronary arteries","Automated segmentation of coronary arteries","","https://asoca.grand-challenge.org/","active","5","","\N","\N","2023-11-08 00:42:00","2023-11-08 17:59:56" +"347","knoap2020","KNOAP2020","Compare methods MRI, X-ray, and clinical risk factors for knee osteoarthritis","Knee osteoarthritis causes a large economic burden on the society and reduces life quality of an individual. Therefore, methods that are able to identify subjects who will develop the disease in the future are important. Usually the methods are optimized for specific datasets and it is unclear how the different methods would perform on previously unseen data. Therefore, we are organizing a challenge to objectively compare methods that use mri, x-ray image data, and clinical risk factors for prediction of incident symptomatic radiographic knee osteoarthritis.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/492/KNOAP_logo_640x640.png","https://knoap2020.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-14 19:58:04" +"348","humanactivitiyclassificationwithradar","Human Activity Classification with Radar","Benchmark classification algorithms on a publicly available radar dataset","The radar challenge is a new event hosted at 2020 iet international radar conference that enables participants to test their classification algorithms on a common, publicly available database of radar data in order to benchmark performances. Dataset download link: http://researchdata.gla.ac.uk/848/","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/493/logo.png","https://humanactivitiyclassificationwithradar.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-11 01:59:47" +"349","saras-esad","SARAS-ESAD","AI-based surgical scene for robotic assistants in minimally invasive surgery","This challenge is part of medical imaging with deep learning conference, 2020. The conference is held between 6 ‚äë 8 july 2020 in montr√©al. The saras (smart autonomous robotic assistant surgeon) eu consortium, www.saras-project.eu, is working towards replacing the assistant surgeon in mis with two assistive robotic arms. To accomplish that, an artificial intelligence based system is required which not only can understand the complete surgical scene but also detect the actions being performed by the main surgeon. This information can later be used infer the response required from the autonomous assistant surgeon.","","https://saras-esad.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-28 00:29:54" +"350","surgvisdom","SurgVisDom","VR simulations to overcome data privacy concerns in context-aware models","Exploring visual domain adaptation using vr simulations to overcome data privacy concerns in context-aware models.","","https://surgvisdom.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-22 19:40:08" +"351","cada","CADA","Cerebral aneurysm image analysis challenge","Cerebral aneurysms are local dilations of arterial blood vessels caused by a weakness of the vessel wall. Subarachnoid hemorrhage (sah) caused by the rupture of a cerebral aneurysm is a life-threatening condition associated with high mortality and morbidity. The mortality rate is above 40%, and even in case of survival cognitive impairment can affect patients for a long time. Major goals in image analysis are the detection and risk assessment of aneurysms. We, therefore, subdivided the challenge into three categories. The first task is finding the aneurysm; the second task is the accurate segmentation to allow for a longitudinal assessment of the development of suspicious aneurysms. The third task is the estimation of the rupture risk of the aneurysm.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/531/data-first-row-2.png","https://cada.grand-challenge.org/","completed","5","https://doi.org/10.1007/978-3-030-72862-5","\N","\N","2023-11-08 00:42:00","2023-11-11 01:54:15" +"352","dfu2020","Diabetic Foot Ulcer Challenge 2020","Diabetic foot ulcer challenge 2020","Diabetic foot ulcer challenge 2020","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/532/bb.png","https://dfu2020.grand-challenge.org/","active","5","https://doi.org/10.1016/j.compbiomed.2021.104596","\N","\N","2023-11-08 00:42:00","2023-11-08 22:47:03" +"353","covid-ct","CT diagnosis of COVID-19","COVID-19 CT Image Diagnosis Competition","Coronavirus disease 2019 (COVID-19) has infected more than 1.3 million individuals all over the world and caused more than 106,000 deaths. One major hurdle in controlling the spreading of this disease is the inefficiency and shortage of medical tests. To mitigate the inefficiency and shortage of existing tests for COVID-19, we propose this competition to encourage the development of effective deep learning techniques to diagnose COVID-19 based on CT images. The problem we want to solve is to classify each CT image into positive COVID-19 (the image has clinical findings of COVID-19) or negative COVID-19 ( the image does not have clinical findings of COVID-19). It‚äôs a binary classification problem based on CT images.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/537/covid-CT2.png","https://covid-ct.grand-challenge.org/","completed","5","","\N","\N","2023-11-14 20:25:11","2023-11-17 21:32:02" +"354","autoimplant","AutoImplant","MICCAI 2020 Cranial Implant Design","The MICCAI 2020 cranial implant design challenge","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/540/logos.PNG","https://autoimplant.grand-challenge.org/","completed","5","https://arxiv.org/abs/2006.12449","\N","\N","2023-11-14 20:25:44","2023-11-08 00:59:03" +"355","cada-rre","CADA - Rupture Risk Estimation","Cerebral aneurysm challenge: detect, segment, and assess rupture risk","Cerebral aneurysms are local dilations of arterial blood vessels caused by a weakness of the vessel wall. Subarachnoid hemorrhage (sah) caused by the rupture of a cerebral aneurysm is a life-threatening condition associated with high mortality and morbidity. The mortality rate is above 40%, and even in case of survival cognitive impairment can affect patients for a long time. Major goals in image analysis are the detection and risk assessment of aneurysms. We, therefore, subdivided the challenge into three categories. The first task is finding the aneurysm; the second task is the accurate segmentation to allow for a longitudinal assessment of the development of suspicious aneurysms. The third task is the estimation of the rupture risk of the aneurysm.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/541/data-first-row-2.png","https://cada-rre.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-11 01:59:43" +"356","cada-as","CADA - Aneurysm Segmentation","Cerebral aneurysm image analysis: detect, segment, assess risk","Cerebral aneurysms are local dilations of arterial blood vessels caused by a weakness of the vessel wall. Subarachnoid hemorrhage (sah) caused by the rupture of a cerebral aneurysm is a life-threatening condition associated with high mortality and morbidity. The mortality rate is above 40%, and even in case of survival cognitive impairment can affect patients for a long time. Major goals in image analysis are the detection and risk assessment of aneurysms. We, therefore, subdivided the challenge into three categories. The first task is finding the aneurysm; the second task is the accurate segmentation to allow for a longitudinal assessment of the development of suspicious aneurysms. The third task is the estimation of the rupture risk of the aneurysm.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/543/data-first-row-2.png","https://cada-as.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-08 00:59:10" +"357","panda","The PANDA challenge","PANDA Challenge: prostate cancer grading","The panda challenge: prostate cancer grade assessment using the gleason grading system","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/544/panda_logo_notext.png","https://panda.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-08 00:59:10" +"358","pathvqachallenge","Pathology Visual Question Answering","Pathology visual question answering","Pathology visual question answering","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/548/grand_challenge3.jpg","https://pathvqachallenge.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-11 01:50:06" +"359","qubiq","QUBIQ","Biomedical image segmentation uncertainties","Quantification of uncertainties in biomedical image segmentation challenge","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/552/brain.png","https://qubiq.grand-challenge.org/","active","5","","\N","\N","2023-11-08 00:42:00","2023-11-08 00:59:15" +"360","lodopab","LoDoPaB-CT","Low-dose CT reconstruction challenge","Low-dose CT reconstruction in the setting of the lodopab-ct dataset.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/555/logo_white_bg.png","https://lodopab.grand-challenge.org/","active","5","https://doi.org/10.1038/s41597-021-00893-z","\N","\N","2023-11-08 00:42:00","2023-11-17 21:31:13" +"361","apples-ct","Apples-CT","Ct reconstruction for apple defect detection","High-throughput CT image reconstruction and defect detection for apples","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/557/logo.png","https://apples-ct.grand-challenge.org/","active","5","","\N","\N","2023-11-08 00:42:00","2023-11-08 00:59:18" +"362","riadd","RIADD (ISBI-2021)","Retinal image analysis for disease detection","Retinal image analysis for multi-disease detection","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/562/Logo_ISBI_640_OO4Fuj9.png","https://riadd.grand-challenge.org/","active","5","","\N","\N","2023-11-08 00:42:00","2023-11-08 00:59:20" +"363","mitoem","MitoEM","3D mitochondria segmentation benchmark","Large-scale 3d mitochondria instance segmentation benchmark","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/566/logo2.png","https://mitoem.grand-challenge.org/","active","5","","\N","\N","2023-11-08 00:42:00","2023-11-08 00:59:22" +"364","a-afma","A-AFMA","Automated prenatal ultrasound measurement","Prenatal ultrasound (us) measurement of amniotic fluid is an important part of fetal surveillance as it provides a non-invasive way of assessing if there is oligohydramnios (insufficient amniotic fluid) and polyhydramnios (excess amniotic fluid), which are associated with numerous problems both during pregnancy and after birth. In this image analysis challenge, we aim to attract attention from the image analysis community to work on the problem of automated measurement of the mvp using the predefined ultrasound video clip based on a linear-sweep protocol [1]. We define two tasks. The first task is to automatically detect amniotic fluid and the maternal bladder. The second task is to identify the appropriate points for mvp measurement given the selected frame of the video clip, and calculate the length of the connected line between these points. The data was collected from women in the second trimester of pregnancy, as part of the pure study at the john radcliffe hospital in oxford, uk.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/567/Figure_3_MVP_example.png","https://a-afma.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-11 07:00:24" +"365","covid-segmentation","COVID-19 LUNG CT LESION SEGMENTATION CHALLENGE - 2020","SARS-CoV-2 lung lesion segmentation","This challenge will create the platform to evaluate emerging methods for the segmentation and quantification of lung lesions caused by SARS-CoV-2 infection from CT images.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/569/Challenge_Image.png","https://covid-segmentation.grand-challenge.org/","active","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:09:24" +"366","valdo","Where is VALDO?","Vascular lesion detection challenge 2021","This challenge aims at promoting the development of new solutions for the automated segmentation of such very sparse and small objects while leveraging weak and noisy labels. The central objective of this challenge is to facilitate quantification of CSVD in brain MRI scans.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/570/LogoVALDO.png","https://valdo.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:45:10" +"367","segpc-2021","SegPC-2021","Plasma cell cancer segmentation challenge","This challenge is positioned towards robust segmentation of cells which is the first stage to build such a tool for plasma cell cancer, namely, multiple myeloma (mm), which is a type of blood cancer.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/574/logo_fRPkhwS.png","https://segpc-2021.grand-challenge.org/","active","5","","\N","\N","2023-11-08 00:42:00","2023-11-08 00:59:29" +"368","endocv2021","EndoCV2021","Endoscopy Computer Vision Challenge 2021","Computer-aided detection, localization, and segmentation methods can help improve colonoscopy procedures. Even though many methods have been built to tackle automatic detection and segmentation of polyps, benchmarking and development of computer vision methods remains an open problem. This is mostly due to the lack of datasets or challenges that incorporate highly heterogeneous dataset appealing participants to test for generalisation abilities of the methods. We aim to build a comprehensive, well-curated, and defined dataset from 6 different centres worldwide and provide 5 datasets types that include: i) multi-centre train-test split from 5 centres ii) polyp size-based split (participants should do this by themselves if of interest), iii) data centre wise split, iv) modality split (only test) and v) one hidden centre test. Participants will be evaluated on all types to address strength and weaknesses of each participants’ method. Both detection bounding boxes and pixel-wise segme...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/575/endoLogo-2021_AdZmuvg.jpg","https://endocv2021.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:38:42" +"369","fusc","Foot Ulcer Segmentation Challenge","Foot ulcer segmentation challenge","The goal of this challenge is to segment the wound area from natural images photographed during clinical visits. In the dataset provided, over 1000 images are collected over 2 years from hundreds of patients. All images are completely de-identified by removing personal identifiers defined by hipaa.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/579/Logo.png","https://fusc.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:38:28" +"370","nucmm","NucMM","Millimeter-scale nucleus 3D segmentation","Segmenting 3D cell nuclei from microscopy image volumes is critical for biological and clinical analysis, enabling the study of cellular expression patterns and cell lineages. We pushed the task forward to the sub-cubic millimeter scale and curated the NucMM dataset with two fully annotated volumes: one 0.1 mm^3 electron microscopy (EM) volume containing nearly the entire zebrafish brain with around 170,000 nuclei; and one 0.25 mm^3 micro-CT (uCT) volume containing part of a mouse visual cortex with about 7,000 nuclei.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/580/NucMM_logo.png","https://nucmm.grand-challenge.org/","completed","5","https://doi.org/10.1007/978-3-030-87193-2_16","\N","\N","2023-11-08 00:42:00","2023-11-15 22:45:22" +"371","vessel-wall-segmentation","Carotid Artery Vessel Wall Segmentation Challenge","Carotid artery vessel wall segmentation","In this challenge, the task is to segment the vessel wall from 3D-MERGE image with high accuracy and robustness. While the challenges of segmentation in different body regions are different, all vessel wall segmentation requires the basic steps of identifying the artery (localization) and lumen and outer wall segmentation. Then the wall thickness (difference between the lumen and outer wall contours) can be measured. Other clinically usable measurements such as lumen area or percent stenosis can also be derived from the vessel wall segmentation. Therefore, this challenge focuses on the important first step of vessel wall segmentation.","","https://vessel-wall-segmentation.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:38:02" +"372","crossmoda","Cross-Modality Domain Adaptation Image Segmentation - 2021","Cross-modality domain adaptation 2021","This challenge proposes the first medical imaging benchmark of unsupervised cross-modality Domain Adaptation approaches (from contrast-enhanced T1 to high-resolution T2).","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/592/crossmoda_logo_black.png","https://crossmoda.grand-challenge.org/","active","5","https://doi.org/10.1016/j.media.2022.102628","\N","\N","2023-11-08 00:42:00","2023-11-15 22:37:49" +"373","brainptm-2021","BrainPTM 2021","Brain pre-surgical tractography mapping","In this challenge we ask the participants to perform direct white matter tracts mapping in clinical brain MRI scans we provide. The data that is provided consists of 75 cases (patients referred for brain tumor removal) that were acquired at Sheba Medical Center at Tel HaShomer, Israel [2]. Patient pathologies include oligodendrogliomas , astrocytomas, glioblastomas and cavernomas, on first occurrence or in a post-surgical recurrence. According to the neuro-radiologist's estimation, the tumor volumes ranged from 4 (cavernoma) to 60 [cm^3] (glioblastoma multiforme). Also, different levels of edema are present around the dataset tumors, from inexistent to very significant. Along with each case both T1 Structural and Diffusion Weighted modalities are provided. For 60 cases (training) semi-manual white matters tracts mapping is provided in the form of binary segmentation maps. For the rest 15 cases (test) no tracts annotations are provided as these will be used for participants algori...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/595/logo_square.jpg","https://brainptm-2021.grand-challenge.org/","active","5","","\N","\N","2023-11-08 00:42:00","2023-11-16 17:40:36" +"374","cholectriplet2021","CholecTriplet 2021","EndoVis sub-challenge for surgical action","This sub-challenge focuses on exploiting machine learning methods for the online automatic recognition of surgical actions as a series of triplets. Participants will develop and compete with algorithms to recognize action triplets directly from the provided surgical videos. This novel challenge investigates the state-of-the-art on surgical fine-grained activity recognition and will establish a new promising research direction in computer-assisted surgery.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/596/logo-challenge.png","https://cholectriplet2021.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:37:21" +"375","paip2021","PAIP2021","PAIP 2021 challenge: perineural invasion","PAIP 2021 challenge aims to promote the development of a common algorithm for automatic detection of perineural invasion in resected specimens of multi-organ cancers. PAIP 2021 challenge will have a technical impact in the following fields: detection of composite targets (nerve and tumor) and common modeling for target images in multiple backgrounds. This challenge will provide a good opportunity to overcome the limitations of current disease-organ-specific modeling and develop a technological approach to the universality of histology in multiple organs.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/598/640-640.png","https://paip2021.grand-challenge.org/","active","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:37:00" +"376","flare","FLARE21","Abdominal organ segmentation challenge","Abdominal organ segmentation plays an important role in clinical practice, and to some extent, it seems to be a solved problem because the state-of-the-art methods have achieved inter-observer performance in several benchmark datasets. However, most of the existing abdominal datasets only contain single-center, single-phase, single-vendor, or single-disease cases, and it is unclear whether the excellent performance can be generalized on more diverse datasets. Moreover, many SOTA methods use model ensembles to boost performance, but these solutions usually have a large model size and cost extensive computational resources, which are impractical to be deployed in clinical practice. To address these limitations, we organize the Fast and Low GPU Memory Abdominal Organ Segmentation challenge that has two main features: (1) the dataset is large and diverse, includes 511 cases from 11 medical centers. (2) we not only focus on segmentation accuracy but also segmentation efficiency, whi...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/599/logo_hDqJ8uG.gif","https://flare.grand-challenge.org/","active","5","https://doi.org/10.1016/j.media.2022.102616","\N","\N","2023-11-08 00:42:00","2023-11-15 22:36:39" +"377","nucls","NuCLS","Triple-negative breast cancer nuclei challenge","Classification, Localization and Segmentation of nuclei in scanned FFPE H&E stained slides of triple-negative breast cancer from The Cancer Genome Atlas. See: Amgad et al. 2021. arXiv:2102.09099 [cs.CV].","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/601/TCGA-AR-A0U4-DX1_id-5ea40a88ddda5f8398990ccf_left-42405_top-70784_bo_PgpXdUu.png","https://nucls.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:29:28" +"378","bcsegmentation","Breast Cancer Segmentation","Triple-negative breast cancer segmentation","Semantic segmentation of histologic regions in scanned FFPE H&E stained slides of triple-negative breast cancer from The Cancer Genome Atlas. See: Amgad M, Elfandy H, ..., Gutman DA, Cooper LAD. Structured crowdsourcing enables convolutional segmentation of histology images. Bioinformatics. 2019. doi: 10.1093/bioinformatics/btz083","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/602/BCSegmentationLogo.png","https://bcsegmentation.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:29:37" +"379","feta","FeTA - Fetal Tissue Annotation Challenge","Fetal tissue annotation challenge","The Fetal Tissue Annotation and Segmentation Challenge (FeTA) is a multi-class, multi-institution image segmentation challenge part of MICCAI 2022. The goal of FeTA is to develop generalizable automatic multi-class segmentation methods for the segmentation of developing human brain tissues that will work with data acquired at different hospitals. The challenge provides manually annotated, super-resolution reconstructed MRI data of human fetal brains which will be used for training and testing automated multi-class image segmentation algorithms. In FeTA 2021, we used the first publicly available dataset of fetal brain MRI to encourage teams to develop automatic brain tissue segmentation algorithms. This year, FeTA 2022 takes it to the next level by launching a multi-center challenge for the development of image segmentation algorithms that will be generalizable to different hospitals with unseen data. We will include data from two institutions in the training dataset, and there wi...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/604/FeTA_logo_640.png","https://feta.grand-challenge.org/","upcoming","5","","2024-03-21","2024-04-26","2023-11-08 00:42:00","2023-11-15 22:36:15" +"380","fastpet-ld","fastPET-LD","PET scan ""hot spots"" detection challenge","In this challenge, we provide 2 training datasets of 68 cases each: the first one was acquired at Sheba medical center (Israel) nuclear medicine department with a very-short exposure of 30s pbp, while the second is the same data followed by a denoising step implemented by a fully convolutional Dnn architecture trained under perceptual loss [1,2]. The purpose of this challenge is the detection of “hot spots”, that is locations that have an elevated standard uptake value (SUV) and potential clinical significance. Corresponding CT scans are also provided. The ground truth, common to both datasets, was generated by Dr. Liran Domachevsky, chair of nuclear medicine at Sheba medical center. It consists of a 3-D segmentation map of the hot spots as well as an Excel file containing the position and size of a 3D cuboid bounding box for each hot spot.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/605/IMG_19052021_144815_600_x_600_pixel.jpg","https://fastpet-ld.grand-challenge.org/","active","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:35:52" +"381","autoimplant2021","AutoImplant 2021","Automatic cranial implant design challenge","Please see our AutoImplant 2020 website for an overview of the cranial implant design topic. Our 2nd AutoImplant Challenge (referred to as AutoImplant 2021) sees the (not limited to) following three major improvements compared to the prior edition, besides a stronger team: Real craniotomy defective skulls will be provided in the evaluation phase. Task specific metrics (e.g., boundary Dice Score) that are optimally in agreement with the clinical criteria of cranial implant design will be implemented and used. Besides a metric-based scoring and ranking system, neurosurgeons will be invited to verify, score and rank the participants-submitted cranial implants based their clinical usability (for the real cases in Task 2).","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/607/AutoImplant_2021_Logo.png","https://autoimplant2021.grand-challenge.org/","completed","5","https://doi.org/10.1109/tmi.2021.3077047","\N","\N","2023-11-08 00:42:00","2023-11-16 17:41:01" +"382","dfu-2021","DFUC2021","Diabetic foot ulcer challenge 2021","We have received approval from the UK National Health Service (NHS) Re-search Ethics Committee (REC) to use these images for the purpose of research. The NHS REC reference number is 15/NW/0539. Foot images with DFU were collected from the Lancashire Teaching Hospital over the past few years. Three cameras were used for capturing the foot images, Kodak DX4530, Nikon D3300and Nikon COOLPIX P100. The images were acquired with close-ups of the full foot at a distance of around 30–40 cm with the parallel orientation to the plane of an ulcer. The use of flash as the primary light source was avoided, and instead, adequate room lights were used to get the consistent colours in images. Images were acquired by a podiatrist and a consultant physician with specialization in the diabetic foot, both with more than 5 years professional experience. As a pre-processing stage, we have discarded photographs with out of focus and blurry artefacts. The DFUC2021 consists of 15,683 DFU patche...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/608/footsnap_logo.png","https://dfu-2021.grand-challenge.org/","active","5","https://doi.org/10.1007/978-3-030-94907-5_7","\N","\N","2023-11-08 00:42:00","2023-11-16 17:41:08" +"383","saras-mesad","SARAS-MESAD","MICCAI 2021 multi-domain surgeon action detection","This challenge is organized under MICCAI 2021, the 24th International Conference on Medical Image Computing and Computer Assisted Intervention. The event will be held from September 27th to October 1st 2021 in Strasbourg, France. The challenge focuses on multi-domain surgeon action detection.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/609/Screenshot_3.png","https://saras-mesad.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:30:14" +"384","node21","NODE21","NODE21: nodule generation and detection","Among both men and women, lung cancer causes the greatest number of cancer deaths worldwide. Symptoms of lung cancer typically occur at an advanced stage of the disease, when treatment has a reduced chance of success. Early detection is therefore a key factor in reducing mortality rates from lung cancer. Pulmonary nodules, detected through imaging, are the initial manifestation of lung cancer, visible well before clinical symptoms or signs emerge. They can be visible on a chest radiograph (CXR), and chest radiography is by far the most common radiological exam in the world. Thus, CXR plays a critical role in the accurate identification of nodules in the drive towards early detection of lung cancer. Pulmonary nodules are frequently encountered as incidental findings in patients undergoing routine examination or CXR imaging for issues unrelated to lung cancer.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/612/node21logo.jpg","https://node21.grand-challenge.org/","active","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:34:20" +"385","wsss4luad","WSSS4LUAD","WSSS4LUAD semantic segmentation challenge","The WSSS4LUAD dataset contains over 10,000 patches of lung adenocarcinoma from whole slide images from Guangdong Provincial People's Hospital and TCGA with image-level annotations. The goal of this challenge is to perform semantic segmentation for differentiating three important types of tissues in the WSIs of lung adenocarcinoma, including cancerous epithelial region, cancerous stroma region and normal region. Paticipants have to use image-level annotations to give pixel-level prediction.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/621/%E6%88%AA%E5%B1%8F2021-07-05_%E4%B8%8A%E5%8D%8810.17.09.png","https://wsss4luad.grand-challenge.org/","active","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:30:23" +"386","ski10","SKI10","SKI10 cartilage and bone segmentation challenge","Welcome to the SKI10 website. The goal of SKI10 was to compare different algorithms for cartilage and bone segmentation from knee MRI data. Knee cartilage segmentation is a clinically relevant segmentation problem that has gained considerable importance in recent years. Among others, it is used to quantify cartilage deterioration for the diagnosis of Osteoarthritis and to optimize surgical planning of knee implants. See the SKI10 paper in the SKI10 Zenodo repository for further details. SKI10 started out as one of the three competitions of the Grand Challenge Workshop 2010, organized in conjunction with the MICCAI 2010 conference.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/624/ski10sq-big.png","https://ski10.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:31:16" +"387","emsig","EMSIG","EMSIG hackathon: radar-based activity recognition","Welcome to the EMSIG Hackathon 2021, organised by EMSIG (www.emsig.org.uk/), the University of Glasgow, Edinburgh Napier University, UCL, DSTL and BAE Systems plc. The goal of the challenge is to evaluate and compare algorithms for human activity recognition based on radar data. We invite the UK radar community to participate by developing and testing existing and novel automated classification methods.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/628/EMSIGgroup_nYL722C.png","https://emsig.grand-challenge.org/","active","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:30:58" +"388","qubiq21","QUBIQ2021","Quantification of uncertainties challenge 2021","The QUBIQ challenge deals with benchmarking algorithms that quantify uncertainties in biomedical image segmentation. Participants will work on binary segmentation tasks, all of which with multiple annotations from domain experts. To be segmented are various pathologies and anatomical structures, such as brain, kidney, or prostate, in MR or CT image data. A successful algorithm will segment these structures and reproduce the distribution of the experts’ annotations.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/629/brain.png","https://qubiq21.grand-challenge.org/","active","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:30:44" +"389","midog2021","MIDOG Challenge 2021","Mitosis domain generalization challenge 2021","Motivation: Mitosis detection is a key component of tumor prognostication for various tumors, including breast cancer. Scanning microscopy slides with different scanners leads to a significant visual difference, resulting in a domain shift. This domain shift prevents most deep learning models from generalizing to other scanners, leading to strongly reduced performance.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/633/midog_logo.png","https://midog2021.grand-challenge.org/","completed","5","https://doi.org/10.5281/zenodo.4573978","\N","\N","2023-11-08 00:42:00","2023-11-15 22:26:47" +"390","tiger","TIGER","Tumor infiltrating lymphocytes assessment","TIGER is the first challenge on fully automated assessment of tumor-infiltrating lymphocytes (TILs) in H&E breast cancer slides. It is organized by the Diagnostic Image Analysis Group (DIAG) of the Radboud University Medical Center (Radboudumc) in Nijmegen (The Netherlands), in close collaboration with the International Immuno-Oncology Biomarker working Group (www.tilsinbreastcancer.org). The goal of this challenge is to evaluate new computer algorithms for the automated assessment of tumor-infiltrating lymphocytes (TILs) in Her2 positive and Triple Negative breast cancer (BC) histopathology slides. In recent years, several studies have shown the predictive and prognostic value of visually scored TILs in BC as well as in other cancer types, making TILs a powerful biomarker that can potentially be used in the clinic. With TIGER, we aim at developing computer algorithms that can automatically generate a ""TIL score"" with a high prognostic value.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/636/tiger-logo_qr7B8JU.png","https://tiger.grand-challenge.org/","active","5","","2022-02-03","\N","2023-11-08 00:42:00","2023-11-15 22:26:17" +"391","stoic2021","STOIC2021 - COVID-19 AI Challenge","COVID-19 AI challenge: CT diagnosis and prognosis","We are launching an artificial intelligence challenge aimed at predicting the severe outcome of COVID-19, based on the largest dataset of Computed Tomography (CT) images of COVID-19 suspects and patients collected to date. Participants will have access to data from the STOIC project, recently published in Radiology. The STOIC project collected CT images of 10,735 individuals suspected of being infected with SARS-COV-2 during the first wave of the pandemic in France, from March to April 2020. The focus of the challenge is the prediction of severe COVID-19, defined as intubation or death within one month from the acquisition of the CT scan (AUC, primary metric). COVID19 positivity will be assessed as a secondary metric in the leaderboard.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/637/stoic2021logo_B3b4JM9.png","https://stoic2021.grand-challenge.org/","active","5","","2021-12-23","2028-01-01","2023-11-08 00:42:00","2023-11-15 22:24:32" +"392","cxr-covid19","Chest XR COVID-19 detection","AI models for COVID-19 detection in chest x-rays","The Coronavirus Disease 2019 (COVID-19) has spread globally and caused unprecedented damages worldwide. Technology, in particular AI, can play an important role in helping fight against this pandemic. In addition, lessons learned can be helpful in fighting and preventing future pandemics. Multiple hospitals and health professionals have shared COVID-19 images coming from multiple modalities to help advance the research in the field. This challenge aims to develop a multiclass classification algorithm capable of detecting COVID-19 in Chest X-ray images. The dataset contains 3 image classes: COVID-19, Pneumonia and Normal (healthy) (See example images below). With 20,000+ images, the participants can train their algorithms to solve this challenge. A test set will be released and will be used to benchmark the obtained results. This Challenge is part of the ‘Ethics and Explainability for Responsible Data Science (EE-RDS) conference’ which will be held virtually and in Johannesburg (So...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/638/CovidChallenge.png","https://cxr-covid19.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:13:57" +"393","pi-cai","The PI-CAI Challenge","AI and radiologists: prostate cancer detection","Prostate cancer (PCa) is one of the most prevalent cancers in men. One million men receive a diagnosis and 300,000 die from clinically significant PCa (csPCa) (defined as ISUP ≥ 2 cancer) each year, worldwide. Multiparametric magnetic resonance imaging (mpMRI) is playing an increasingly important role in the early diagnosis of prostate cancer, and has been recommended by the 2019 European Association of Urology (EAU) guidelines and the 2019 UK National Institute for Health and Care Excellence (NICE) guidelines, prior to biopsies (Mottet et al., 2021). However, current guidelines for reading prostate mpMRI (i.e. PI-RADS v2.1) follow a semi-quantitative assessment, mandating substantial expertise for proper usage. Moreover, prostate cancer can exhibit a broad range of clinical behavior and highly heterogeneous morphology in MRI. As such, assessments are susceptible to low inter-reader agreement (<50%), sub-optimal interpretation and overdiagnosis (Rosenkrantz et al., 2016, Westphale...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/642/square_logo_we441sa.jpg","https://pi-cai.grand-challenge.org/","active","5","https://doi.org/10.5281/zenodo.6667655","2022-06-12","\N","2023-11-08 00:42:00","2023-11-15 22:10:32" +"394","ultra-low-dose-pet","Ultra-low Dose PET Imaging Challenge","Low-dose PET scanner imaging recovery challenge","This challenge aims to develop computational algorithms capable of recovering high-quality imaging from low statistics corresponding to low dose scans, with the hope of reducing the radiation exposure to be equivalent to transatlantic flight.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/643/Ultra-low_Dose_PET-01.jpg","https://ultra-low-dose-pet.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-15 22:09:48" +"395","airogs","AIROGS","AI for robust glaucoma screening challenge","Early detection of glaucoma can avoid visual impairment, which could be facilitated through screening. Artificial intelligence (AI) could increase the cost-effectiveness of glaucoma screening, by reducing the need for manual labor. AI approaches for glaucoma detection from color fundus photography (CFP) have been proposed and promising at-the-lab performances have been reported. However, large performance drops often occur when AI solutions are applied in real-world settings. Unexpected out-of-distribution data and bad quality images are major causes for this performance drop. Aim: The development of solutions for glaucoma screening from CFP that are robust to real-world scenarios.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/644/logo2-01-logo.png","https://airogs.grand-challenge.org/","active","5","","2021-12-01","\N","2023-11-08 00:42:00","2023-11-15 22:03:44" +"396","conic-challenge","CoNIC 2022","Colon nuclei identification and counting 2022","The CoNIC challenge starts with the discovery phase where we share the training data, challenge goals, and the evaluation code. Participants should start experimenting with the dataset and train/validate their model on it. All challenge submissions are in the form of a docker container, which means that participants should submit their method to be evaluated on the test sets. In other words, only the training set will be released during the challenge and participants will not have access to any part of the test set. The test will be done in two phases. The first phase, the preliminary test, will give participants a chance to work on their submissions for two weeks, get familiar with the submission workflow, improve their code if needed, and make sure their method works fine in the challenge evaluation pipeline. We will release a template docker structure and tutorials on how participants should package their code using the template and submit it to the challenge website. During ...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/648/conic_logo_YbqWBDc.png","https://conic-challenge.grand-challenge.org/","active","5","https://arxiv.org/abs/2111.14485","2022-02-13","\N","2023-11-08 00:42:00","2023-11-15 22:03:23" +"397","cholectriplet2022","CholecTriplet2022: Surgical Action Triplet Detection","Dounding box localization of the regions of action triplets","Formalizing surgical activities as triplets of the used instruments, actions performed, and target anatomies acted upon provides a better, comprehensive and fine-grained modeling of surgical activities. Automatic recognition of these triplet activities directly from surgical videos would facilitate the development of intra-operative decision support systems that are more helpful, especially for safety, in the operating room (OR). Our previous EndoVIS challenge, CholecTriplet2021 (MICCAI 2021), and existing works on surgical action triplet recognition tackles this as a multi-label classification of all possible combinations. For better clinical utility, real-time modeling of tool-tissue interaction will go beyond determining the presence of these action triplets, to also include estimating their locations in each video frame. Hence, this challenge extends our previous challenge on action triplet recognition to also include bounding box localization of the...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/649/t50-logo-2022_kz11kSp.png","https://cholectriplet2022.grand-challenge.org/","completed","5","https://doi.org/10.1007/978-3-030-59716-0_35","\N","\N","2023-11-08 00:42:00","2023-11-27 20:45:26" +"398","endocv2022","EndoCV2022","Endoscopic video sequence detection and segmentation","Accurate detection of artefacts is a core challenge in a wide-range of endoscopic applications addressing multiple different disease areas. The importance of precise detection of these artefacts is essential for high-quality endoscopic video acquisition crucial for realising reliable computer assisted endoscopy tools for improved patient care. In particular, colonoscopy requires colon preparation and cleaning to obtain improved adenoma detection rate. Computer aided systems can help to guide both expert and trainee endoscopists to obtain consistent high quality surveillance and detect, localize and segment widely known cancer precursor lesion, “polyps”. While deep learning has been successfully applied in the medical imaging, generalization is still an open problem. Generalizability issue of deep learning models need to be clearly defined and tackled to build more reliable technology for clinical translation. Inspired by the enthusiasm of participants on our previous challenges, t...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/650/EndoCV2022-logo-v2.jpg","https://endocv2022.grand-challenge.org/","completed","5","https://doi.org/10.1016/j.media.2021.102002","2022-02-20","\N","2023-11-08 00:42:00","2023-11-15 21:56:32" +"399","mela","MELA2022","MICCAI 2022 MELA challenge: ct scan benchmark","The mediastinum is the common site of various lesions, including hyperplasia, cysts, tumors, and lymph nodes transferred from the lungs, which might cause serious problems due to their location. Therefore, the detection of mediastinal lesions has important indications for the early screening and diagnosis of related diseases. Computer-aided diagnosis methods have been developed to assist doctors in interpreting massive computed tomography (CT) scans. However, few prior studies investigate deep learning methods on this labor-intensive task. This challenge establishes a large-scale benchmark dataset to automatically detect mediastinal lesions from 1100 CT scans, consisting of 770 CTs for training, 110 CTs for validation, and 220 CTs for testing. Each annotation file includes coordinates of the bounding box of each mediastinal lesion region per CT scan for serving the task of detection. We hope this challenge could facilitate the research and application of automatic mediastinal lesi...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/651/LOGO-%E8%93%9D-900.png","https://mela.grand-challenge.org/","completed","5","","2022-07-02","2022-07-17","2023-11-08 00:42:00","2023-11-15 21:56:16" +"400","kipa22","KiPA22 (Regular Challenge)","Kidney and artery segmentation challenge","The challenge is aimed to segment kidney, renal tumors, arteries, and veins from computed tomography angiography (CTA) images in one inference.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/654/logo3_%E5%89%AF%E6%9C%AC.png","https://kipa22.grand-challenge.org/","active","5","https://doi.org/10.1016/j.media.2021.102055","2022-07-01","\N","2023-11-08 00:42:00","2023-11-17 23:31:41" +"401","parse2022","Parse2022","Pulmonary artery segmentation challenge 2022","It is of significant clinical interest to study pulmonary artery structures in the field of medical image analysis. One prerequisite step is to segment pulmonary artery structures from CT with high accuracy and low time-consuming. The segmentation of pulmonary artery structures benefits the quantification of its morphological changes for diagnosis of pulmonary hypertension and thoracic surgery. However, due to the complexity of pulmonary artery topology, automated segmentation of pulmonary artery topology is a challenging task. Besides, the open accessible large-scale CT data with well labeled pulmonary artery are scarce (The large variations of the topological structures from different patients make the annotation an extremely challenging process). The lack of well labeled pulmonary artery hinders the development of automatic pulmonary artery segmentation algorithm. Hence, we try to host the first Pulmonary ARtery SEgmentation challenge in MICCAI 2022 (Named Parse2022) to start a...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/658/logo.jpg","https://parse2022.grand-challenge.org/","active","5","","2023-06-30","\N","2023-11-08 00:42:00","2023-11-17 23:31:47" +"402","tdsc-abus2023","TDSC-ABUS2023","Automated 3D breast ultrasound tumor challenge","Tumor Detection, Segmentation And Classification Challenge On Automated 3D Breast Ultrasound","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/662/logo.png","https://tdsc-abus2023.grand-challenge.org/","completed","5","","2023-07-15","2023-08-20","2023-11-08 00:42:00","2023-11-08 01:00:36" +"403","instance","INSTANCE2022","Intracranial hemorrhage segmentation challenge 2022","Participants are required to segment Intracranial Hemorrhage region in Non-Contrast head CT (NCCT).","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/667/Logo_%E9%A1%B5%E9%9D%A2_2.png","https://instance.grand-challenge.org/","active","5","https://doi.org/10.1109/jbhi.2021.3103850","2022-07-14","\N","2023-11-08 00:42:00","2023-11-15 21:55:33" +"404","bcnb","BCNB","Early breast cancer core-needle biopsy dataset","Breast cancer (BC) has become the greatest threat to women’s health worldwide. Clinically, identification of axillary lymph node (ALN) metastasis and other tumor clinical characteristics such as ER, PR, and so on, are important for evaluating the prognosis and guiding the treatment for BC patients. Several studies intended to predict the ALN status and other tumor clinical characteristics by clinicopathological data and genetic testing score. However, due to the relatively poor predictive values and high genetic testing costs, these methods are often limited. Recently, deep learning (DL) has enabled rapid advances in computational pathology, DL can perform high-throughput feature extraction on medical images and analyze the correlation between primary tumor features and above status. So far, there is no relevant research on preoperatively predicting ALN metastasis and other tumor clinical characteristics based on WSIs of primary BC samples.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/668/BCNB-logo_CUGMa0V.png","https://bcnb.grand-challenge.org/","completed","5","https://doi.org/10.3389/fonc.2021.759007","\N","\N","2023-11-08 00:42:00","2023-11-16 17:41:33" +"405","ravir","RAVIR","Retinal arteries and veins segmentation dataset","The retinal vasculature provides important clues in the diagnosis and monitoring of systemic diseases including hypertension and diabetes. The microvascular system is of primary involvement in such conditions, and the retina is the only anatomical site where the microvasculature can be directly observed. The objective assessment of retinal vessels has long been considered a surrogate biomarker for systemic vascular diseases, and with recent advancements in retinal imaging and computer vision technologies, this topic has become the subject of renewed attention. In this paper, we present a novel dataset, dubbed RAVIR, for the semantic segmentation of Retinal Arteries and Veins in Infrared Reflectance (IR) imaging. It enables the creation of deep learning-based models that distinguish extracted vessel type without extensive post-processing.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/673/IR_Case_022.png","https://ravir.grand-challenge.org/","active","5","https://doi.org/10.1109/jbhi.2022.3163352","2022-07-18","\N","2023-11-08 00:42:00","2023-11-16 17:41:34" +"406","dfuc2022","DFUC 2022","Diabetic foot ulcer (DFU) segmentation challenge","Diabetes is a global epidemic affecting around 425 million people and expected to rise to 629 million by 2045. Diabetic Foot Ulcer (DFU) is a severe condition that can result from the disease. The rise of the condition over the last decades is a challenge for healthcare systems. Cases of DFU usually lead to severe conditions that greatly prolongs treatment and result in limb amputation or death. Recent research focuses on creating detection algorithms to monitor their condition to improve patient care and reduce strain on healthcare systems. Work between Manchester Metropolitan University, Lancashire Teaching Hospitals and Manchester University NHS Foundation Trust has created an international repository of up to 11,000 DFU images. Analysis of ulcer regions is a key for DFU management. Delineation of ulcers is time-consuming. With effort from the lead scientists of the UK, US, India and New Zealand, this challenge promotes novel work in DFU segmentation and promote interdisciplina...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/674/footsnap_logo.png","https://dfuc2022.grand-challenge.org/","active","5","https://arxiv.org/abs/2204.11618","2022-06-20","\N","2023-11-08 00:42:00","2023-11-17 23:32:01" +"407","atlas","ATLAS R2.0 - Stroke Lesion Segmentation","Anatomical tracings of lesions after stroke","Accurate lesion segmentation is critical in stroke rehabilitation research for the quantification of lesion burden and accurate image processing. Current automated lesion segmentation methods for T1-weighted (T1w) MRIs, commonly used in rehabilitation research, lack accuracy and reliability. Manual segmentation remains the gold standard, but it is time-consuming, subjective, and requires significant neuroanatomical expertise. However, many methods developed with ATLAS v1.2 report low accuracy, are not publicly accessible or are improperly validated, limiting their utility to the field. Here we present ATLAS v2.0 (N=1271), a larger dataset of T1w stroke MRIs and manually segmented lesion masks that includes training (public. n=655), test (masks hidden, n=300), and generalizability (completely hidden, n=316) data. Algorithm development using this larger sample should lead to more robust solutions, and the hidden test and generalizability datasets allow for unbiased performance eval...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/676/ATLAS_Logo_square.png","https://atlas.grand-challenge.org/","active","5","https://doi.org/10.1101/2021.12.09.21267554","2022-09-18","\N","2023-11-08 00:42:00","2023-11-15 21:54:33" +"408","3dteethseg","3D Teeth Scan Segmentation and Labeling Challenge MICCAI2022","Teeth segmentation in orthodontic CAD systems","Computer-aided design (CAD) tools have become increasingly popular in modern dentistry for highly accurate treatment planning. In particular, in orthodontic CAD systems, advanced intraoral scanners (IOSs) are now widely used as they provide precise digital surface models of the dentition. Such models can dramatically help dentists simulate teeth extraction, move, deletion, and rearrangement and therefore ease the prediction of treatment outcomes. Although IOSs are becoming widespread in clinical dental practice, there are only few contributions on teeth segmentation/labeling available in the literature and no publicly available database. A fundamental issue that appears with IOS data is the ability to reliably segment and identify teeth in scanned observations. Teeth segmentation and labelling is difficult as a result of the inherent similarities between teeth shapes as well as their ambiguous positions on jaws.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/680/Grand-Challenge-Logo_2.jpg","https://3dteethseg.grand-challenge.org/","completed","5","","2022-07-01","2022-08-15","2023-11-08 00:42:00","2023-11-17 23:32:08" +"409","flare22","MICCAI FLARE 2022","Fast and low-resource abdominal organ segmentation","We extend the FLARE 2021 Challenge from fully supervised settings to a semi-supervised setting that focuses on how to use unlabeled data. Specifically, we provide a small number of labeled cases (50) and a large number of unlabeled cases (2000) in the training set, 50 visible cases for validation, and 200 hidden cases for testing. The segmentation targets include 13 organs: liver, spleen, pancreas, right kidney, left kidney, stomach, gallbladder, esophagus, aorta, inferior vena cava, right adrenal gland, left adrenal gland, and duodenum. In addition to the typical Dice Similarity Coefficient (DSC) and Normalized Surface Dice (NSD), our evaluation metrics also focus on the inference speed and resources (GPU, CPU) consumption. Compare to the FLARE 2021 challenge, the dataset is 4x larger and the segmentations targets are increased to 13 organs. Moreover, the resource-related metrics are changed to the area under GPU memory-time curve and the area under CPU utilization-time curve rat...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/683/challenge-logo_xJtvQKE.png","https://flare22.grand-challenge.org/","active","5","https://doi.org/10.1109/tpami.2021.3100536","2023-01-01","\N","2023-11-08 00:42:00","2023-11-15 21:54:18" +"410","aggc22","AGGC22","Segment the Circle of Willis vessel components for both CTA and MRA","Driving innovation in computational pathology for prostate cancer diagnosis. Develop algorithms to identify Gleason Patterns in H&E-stained whole slide images.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/684/logo_yEwrCqI.PNG","https://aggc22.grand-challenge.org/","active","5","","2022-06-29","\N","2023-11-08 00:42:00","2023-11-17 23:32:15" +"411","autopet","autoPET","Whole-body FDG-PET/CT lesion segmentation","Automatic tumor lesion segmentation in whole-body FDG-PET/CT on large-scale database of 1014 studies of 900 patients (training database) acquired on a single site: accurate and fast lesion segmentation avoidance of false positives (brain, bladder, etc.) Testing will be performed on 200 150 studies (held-out test database) with 100 studies originating from the same hospital as the training database and 100 50 are drawn from a different hospital with similar acquisition protocol to assess algorithm robustness and generalizabilit","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/686/autopet-5.png","https://autopet.grand-challenge.org/","completed","5","","2022-05-02","2022-09-04","2023-11-08 00:42:00","2023-11-15 21:53:42" +"412","acrobat","ACROBAT 2023","Acrobat challenge: WSI registration in breast cancer","The ACROBAT challenge aims to advance the development of WSI registration algorithms that can align WSIs of IHC-stained breast cancer tissue sections to corresponding tissue regions that were stained with H&E. All WSIs originate from routine diagnostic workflows.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/687/final_logo_1280x1280_qgi9ILO.png","https://acrobat.grand-challenge.org/","active","5","","2022-06-15","\N","2023-11-08 00:42:00","2023-11-17 23:32:30" +"413","surgt","SurgT: Surgical Tracking","Surgical video tracking for trajectory estimation","This challenge consists of surgical videos with a target bounding box and the participants are expected to develop visual tracking algorithms to estimate the trajectory of the bounding box throughout the video-sequence.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/688/Screenshot_from_2022-06-27_09-41-30.png","https://surgt.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:32:36" +"414","slcn","Surface Learning for Clinical Neuroimaging","Developmental phenotypes prediction from cortical imaging","The goal of this challenge will therefore be to elicit submissions of novel methods for registration-free or registration-robust cortical phenotype regression, with emphasis on interpretable or explainable machine learning methods which deliver biomarkers predictive of risk for neurodevelopmental impairment. These will be benchmarked on the tasks of regression of gestational age at birth (seen as a correlate of prematurity) on both registered and native space cortical surface data.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/689/SLCN_Logo.png","https://slcn.grand-challenge.org/","completed","5","https://doi.org/10.1016/j.neuroimage.2018.01.054","2022-04-24","2022-07-15","2023-11-08 00:42:00","2023-11-15 21:53:02" +"415","p2ilf","Preoperative to Intraoperative Laparoscopy Fusion","Preoperative to intraoperative laparoscopy fusion","Augmented reality (AR) in laparoscopic liver surgery needs key landmark detection in intraoperative 2D laparoscopic images and its registration with the preoperative 3D model from CT/MRI data. Such AR techniques are vital to surgeons as they enable precise tumor localisation for surgical removal. A full resection of targeted tumor minimises the risk of recurrence. However, the task of automatic anatomical curve segmentation (considered as landmarks), and its registration to 3D models is a non-trivial and complex task. Most developed methods in this domain are built around traditional methodologies in computer vision. This challenge is designed to challenge participants to deploy machine learning methods for two tasks - Task I: segmentation of five key anatomical curves from laparoscopic video images and 3D model, including ridge (L, R), ligament, silhouettes, liver boundary; Task 2: matching these segmented curves to the 3D liver model from volumetric data (CT/MR).","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/690/logo_V3.png","https://p2ilf.grand-challenge.org/","completed","5","","2022-09-02","2022-09-14","2023-11-08 00:42:00","2023-11-15 21:52:39" +"416","hecktor","MICCAI HECKTOR 2022","Head and neck tumor segmentation in PET/CT","Following the success of the first two editions of the HECKTOR challenge in 2020 and 2021, this challenge will be presented at the 25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2022. Two tasks are proposed this year (participants can choose to participate in either or both tasks): Task 1: The automatic segmentation of Head and Neck (H&N) primary tumors and lymph nodes (new!) in FDG-PET/CT images; Task 2: The prediction of patient outcomes, namely Recurrence-Free Survival (RFS) from the FDG-PET/CT images and available clinical data.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/691/grandchallenge_logo_d8JNqKz.png","https://hecktor.grand-challenge.org/","active","5","https://doi.org/10.1007/978-3-030-98253-9","2022-08-26","2024-05-01","2023-11-08 00:42:00","2023-11-15 21:52:24" +"417","k2s","K2S: from undersampled K-space To automatic Segmentation","K2s: undersampled k-space to segmentation","Magnetic resonance imaging (MRI) is the modality of choice for evaluating knee joint degeneration, but it can be susceptible to long acquisition times, tedious post processing, and lack of standardization. One of the most compelling applications of deep learning, therefore, is accelerated analysis of knee MRI. In addition to faster MRI acquisition, deep learning has enhanced image post-processing applications such as tissue segmentation. While fast, undersampled MRI acquisition may not have qualitative, visual acuity that comes from fully-sampled data, the underlying embedding space may be adequate for some applications. The implications for down-stream tasks such as tissue segmentation using convolutional neural networks are not well-characterized. Efficient segmentation of key anatomical structures from undersampled data is an open question that has clinical relevance, e.g., patient triage. The goal of this challenge, therefore, is to train segmentation models from 8x undersamp...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/692/K2S_gradient_5AE5wa5.png","https://k2s.grand-challenge.org/","completed","5","https://doi.org/10.1148/ryai.2021200165","2022-05-16","2022-06-16","2023-11-08 00:42:00","2023-11-15 21:51:47" +"418","drac22","Diabetic Retinopathy Analysis Challenge MICCAI2022","DR lesions segmentation in UW-OCTA-M images","Diabetic retinopathy is one of the leading causes of blindness and affects approximately 78% people, with a history of diabetes of 15 years or longer [1]. DR often causes gradual changes in vasculature structure and resulting abnormalities. DR is diagnosed by visually inspecting retinal fundus images for the presence of retinal lesions, such as microaneurysms (MAs), intraretinal microvascular abnormalities (IRMAs), nonperfusion areas and neovascularization. The detection of these lesions is critical to the diagnosis of DR. There have been some works using fundus images for DR diagnosis [2]. With rising popularity, OCT angiography (OCTA) has the capability of visualizing the retinal and choroidal vasculature at a microvascular level in great detail [3]. Specially, swept-source (SS)-OCTA allows additionally the individual assessment of the choroidal vasculature. There are already some works using SS-OCTA to grade for qualitative features of diabetic retinopathy [4-6]. Further, ultra...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/694/logo_kT1YYna.png","https://drac22.grand-challenge.org/","active","5","","2022-08-07","\N","2023-11-08 00:42:00","2023-11-15 21:50:58" +"419","amos22","Multi-Modality Abdominal Multi-Organ Segmentation Challenge 2022","Multi-modality abdominal multi-organ segmentation","Abdominal multi-organ segmentation is one of the most attractive topics in the field of medical image analysis, which plays an important role in supporting clinical workflows such as disease diagnosis and treatment planning. The recent success of deep learning methods applied for abdominal multi-organ segmentation exposes the lack of large-scale comprehensive benchmarks for developing and comparing such methods. While several benchmark datasets for abdominal organ segmentation are available, the limited number of organs of interest and training samples still limits the power of modern deep models and makes it difficult to provide a fully comprehensive and fair estimate of different methods. And, most research in medical image analysis today focuses on building bespoke systems to handle stereotypical inputs and outputs associated with a single task, the complexity of systems like this can grow dramatically as the inputs or outputs grow more diverse. If a single algorithm could h...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/695/AMOS_2022.png","https://amos22.grand-challenge.org/","active","5","","2022-10-09","2060-12-31","2023-11-08 00:42:00","2023-11-15 21:50:34" +"420","surgtoolloc","Surgical Tool Localization in endoscopic videos","Surgical tool localization in endoscopic videos","The ability to automatically detect and track surgical instruments in endoscopic video will enable many transformational interventions. Assessing surgical performance and efficiency, identifying skilled tool use and choreography, and planning operational and logistical aspects of OR resources are just some of the applications that would benefit. Unfortunately obtaining the annotations needed to train machine learning models to identify and localize surgical tools is a difficult task. Annotating bounding boxes frame-by-frame in video is tedious and time consuming, yet a wide variety of surgical tools and surgeries must be captured for robust training. Moreover, ongoing annotator training is needed to stay up to date with surgical instrument innovation. In robot-assisted surgery however, potentially informative data like timestamps of instrument installation and removal can be programmatically harvested. The ability to use only tool presence labels to localize tools would significan...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/698/grand-challenge_logo.png","https://surgtoolloc.grand-challenge.org/","completed","5","","2022-08-29","2022-09-08","2023-11-08 00:42:00","2023-11-15 21:50:20" +"421","curious2022","Brain shift with Intraoperative Ultrasound - Segmentation tasks","Brain shift with intraoperative ultrasound segmentation","Early brain tumor resection can effectively improve the patient’s survival rate. However, resection quality and safety can often be heavily affected by intra-operative brain tissue shift due to factors, such as gravity, drug administration, intracranial pressure change, and tissue removal. Such tissue shift can displace the surgical target and vital structures (e.g., blood vessels) shown in pre-operative images while these displacements may not be directly visible in the surgeon’s field of view. Intra-operative ultrasound (iUS) is a robust and relatively inexpensive technique to track intra-operative tissue shift and surgical tools. Automatic algorithms for brain tissue segmentation in iUS, especially brain tumors and resection cavity can greatly facilitate the robustness and accuracy of brain shift correction through image registration, and allow easy interpretation of the iUS. This has the potential to improve surgical outcomes and patient survival rate. The challenge is an ex...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/699/CuRIOUS_logo.png","https://curious2022.grand-challenge.org/","completed","5","","2022-08-15","2022-09-13","2023-11-08 00:42:00","2023-11-15 21:50:06" +"422","vessel-wall-segmentation-2022","Carotid Vessel Wall Segmentation and Atherosclerosis Diagnosis","Carotid vessel wall segmentation and diagnosis","In this challenge, the task is to segment the vessel wall from 3D-VISTA images and diagnose the atherosclerotic lesions with high accuracy and robustness. And then the clinical usable measurements such as wall thickness (difference between the lumen and outer wall contours), lumen area or stenosis percent can be derived from the vessel wall segmentation. In addition, the identification of the lumen and outer wall boundary of the vessel wall is also critical for the diagnosis of lesions. In summary, this challenge focuses on carotid vessel wall segmentation and atherosclerotic lesion diagnosis.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/700/%E5%9B%BE%E7%89%871.png","https://vessel-wall-segmentation-2022.grand-challenge.org/","completed","5","","2022-07-08","2022-08-01","2023-11-08 00:42:00","2023-11-16 17:41:55" +"423","crossmoda2022","Cross-Modality Domain Adaptation: Segmentation & Classification","CrossMoDA 2022: unsupervised domain adaptation","The CrossMoDA 2022 challenge is the second edition of the first large and multi-class medical dataset for unsupervised cross-modality Domain Adaptation.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/701/squarelogo_2022.png","https://crossmoda2022.grand-challenge.org/","active","5","","2022-05-11","\N","2023-11-08 00:42:00","2023-11-17 23:32:53" +"424","atm22","Multi-site, Multi-Domain Airway Tree Modeling (ATM'22)","Airway segmentation in x-ray CT for pulmonary diseases","Airway segmentation is a crucial step for the analysis of pulmonary diseases including asthma, bronchiectasis, and emphysema. The accurate segmentation based on X-Ray computed tomography (CT) enables the quantitative measurements of airway dimensions and wall thickness, which can reveal the abnormality of patients with chronic obstructive pulmonary disease (COPD). Besides, the extraction of patient-specific airway models from CT images is required for navigatiisted surgery.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/702/logo_xqf7twK.png","https://atm22.grand-challenge.org/","active","5","https://doi.org/10.1007/978-3-031-16431-6_48","2022-08-17","\N","2023-11-08 00:42:00","2023-11-21 17:16:40" +"425","ps-fh-aop-2023","FH-PS-AOP challenge","Fetal head and pubic symphysis segmentation","The task of the FH-PS-AOP grand challenge is to automatically segment 700 FH-PSs from transperineal ultrasound images in the devised Set 2 (test set), given the availability of Set 1, consisting of 401 images. Set 2 is held private and therefore not released to the potential participants to prevent algorithm tuning, but instead the algorithms have to be submitted in the form of Docker containers that will be run by organizers on Set 2. The challenge is organized by taking into account the current guidelines for biomedical image analysis competitions, in particular the recommendations of the Biomedical Image Analysis Challenges (BIAS) initiative for transparent challenge reporting.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/703/F2_WDBTbsq.tif","https://ps-fh-aop-2023.grand-challenge.org/","completed","5","https://doi.org/10.1007/s11517-022-02747-1","2023-03-27","2023-09-20","2023-11-08 00:42:00","2023-11-16 17:41:56" +"426","shifts","Shifts Challenge 2022","Shifts challenge 2022: distributional shift and uncertainty","The goal of the Shifts Challenge 2022 is to raise awareness among the research community about the problems of distributional shift, robustness, and uncertainty estimation, and to identify new solutions to address them. The competition will consist of two new tracks: White Matter Multiple Sclerosis (MS) lesion segmentation in 3D Magnetic Resonance Imaging (MRI) of the brain and Marine cargo vessel power estimation.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/704/logo_1200.png","https://shifts.grand-challenge.org/","active","5","https://arxiv.org/abs/2206.15407","2022-09-15","2024-04-08","2023-11-08 00:42:00","2023-11-17 23:33:07" +"427","megc2022","ACMMM MEGC2022: Facial Micro-Expression Grand Challenge","Facial macro- and micro-expressions spotting","The unseen testing set (MEGC2022-testSet) contains 10 long video, including 5 long videos from SAMM (SAMM Challenge dataset) and 5 clips cropped from different videos in CAS(ME)3. The frame rate for SAMM Challenge dataset is 200fps and the frame rate for CAS(ME)3 is 30 fps. The participants should test on this unseen dataset.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/705/acmmm2022_logo.png","https://megc2022.grand-challenge.org/","active","5","https://doi.org/10.1109/fg47880.2020.00029","2022-05-23","\N","2023-11-08 00:42:00","2023-11-16 17:39:17" +"428","midog2022","MItosis DOmain Generalization Challenge 2022","Mitosis domain generalization challenge 2022","Motivation: Mitosis detection is a key component of tumor prognostication for various tumors. Modern deep learning architectures provide detection accuracies for mitosis that are on the level of human experts. Mitosis is known to be relevant for many tumor types, yet, when trained on one tumor / tissue type, the performance will typically drop significantly on another. Scope: Detect mitotic figures (cells undergoing cell division) from histopathology images (object detection). You will be provided with images from 6 different tumor types, 5 out of which are labeled. In total the set consists of 405 cases and includes 9501 mitotic figure annotations in the training set. Evaluation will be done on ten different tumor types with the F1 score as main metric.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/706/midog_compact.png","https://midog2022.grand-challenge.org/","completed","5","https://doi.org/10.5281/zenodo.6362337","2022-08-04","2022-08-30","2023-11-08 00:42:00","2023-11-16 17:39:11" +"429","isles22","Ischemic Stroke Lesion Segmentation Challenge","Ischemic stroke lesion segmentation challenge","The goal of this challenge is to evaluate automated methods of stroke lesion segmentation in MR images. Participants are tasked with automatically generating lesion segmentation masks from DWI, ADC and FLAIR MR modalities. The task consist on a single phase of algorithms evaluation. Participants will submit their segmentation model (""algorithm"") via a Docker container which will then be used to generate predictions on a hidden dataset.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/707/Slide1_N1qHO1K.png","https://isles22.grand-challenge.org/","active","5","","2022-07-15","2030-12-06","2023-11-08 00:42:00","2023-11-15 21:48:03" +"430","neurips22-cellseg","Cell Segmentation in Multi-modality Microscopy Images","Weakly supervised cell segmentation in high-res microscopy","Cell segmentation is usually the first step for downstream single-cell analysis in microscopy image-based biology and biomedical research. Deep learning has been widely used for image segmentation, but it is hard to collect a large number of labeled cell images to train models because manually annotating cells is extremely time-consuming and costly. Furthermore, datasets used are often limited to one modality and lacking in diversity, leading to poor generalization of trained models. This competition aims to benchmark cell segmentation methods that could be applied to various microscopy images across multiple imaging platforms and tissue types. We frame the cell segmentation problem as a weakly supervised learning task to encourage models that use limited labeled and many unlabeled images for cell segmentation as unlabeled images are relatively easy to obtain in practice.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/708/logo_EOVfhip.PNG","https://neurips22-cellseg.grand-challenge.org/","active","5","","2023-08-01","\N","2023-11-08 00:42:00","2023-11-16 17:39:21" +"431","bci","Breast Cancer Immunohistochemical Image Generation Challenge","Breast cancer immunohistochemical image generation","This is an image-to-image translation task that builds a mapping between two domains (HE and IHC). Given an HE image, the algorithm should predict the corresponding IHC image.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/711/logo.png","https://bci.grand-challenge.org/","active","5","","2022-08-24","\N","2023-11-08 00:42:00","2023-11-16 17:39:23" +"432","auto-rtp","Fully Automated Radiotherapy Treatment Planning Challenge","Automated radiotherapy treatment planning in prostate cancer","Participants will be provided with simulation CTs for ten prostate cancer patients, together with a treatment intent/prescription (in a machine readable format). The cases will be a mix of prostate only and prostate + nodes. Participants are asked to generate a treatment plan in an as-automated-as-possible way, including contouring and plan generation. No manual intervention on contouring or planning should be performed, but manual steps to transfer data between systems are permitted if required. Freedom is given to participants with respect to the ""treatment machine"" the plan is designed for. However, it is expected that all participants produce a plan that is deliverable in clinically reasonable time frame.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/713/AUTO-RTP_Logo.png","https://auto-rtp.grand-challenge.org/","active","5","","2023-06-05","\N","2023-11-08 00:42:00","2023-11-16 17:39:25" +"433","2023paip","PAIP 2023: TC prediction in pancreatic and colon cancer","Tumor cellularity prediction in pancreatic and colon cancer","Tumor cellularity (TC) is used to compute the residual tumor burden in several organs, such as the breast and colon. The TC is measured based on semantic cell segmentation, which accurately classifies and delineates individual cells. However, manual analysis of TC is impractical in clinics because of the large volumes of pathological images and is unreliable owing to inconsistent TC values among pathologists. Essentially, tumor cellularity should be calculated by individual cell counting; however, manual counting is impossible, and human pathologists cannot avoid individual differences in diagnostic performance. Automatic image analysis is the ideal method for solving this problem, and it can efficiently reduce the workload of pathologists.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/716/PAIP2023-640.png","https://2023paip.grand-challenge.org/","active","5","","2023-02-15","\N","2023-11-08 00:42:00","2023-11-16 17:39:26" +"434","snemi3d","SNEMI3D: 3D Segmentation of neurites in EM images","IEEE ISBI 2013 challenge: multimodal segmentation","In this challenge, a full stack of electron microscopy (EM) slices will be used to train machine-learning algorithms for the purpose of automatic segmentation of neurites in 3D. This imaging technique visualizes the resulting volumes in a highly anisotropic way, i.e., the x- and y-directions have a high resolution, whereas the z-direction has a low resolution, primarily dependent on the precision of serial cutting. EM produces the images as a projection of the whole section, so some of the neural membranes that are not orthogonal to a cutting plane can appear very blurred. None of these problems led to major difficulties in the manual labeling of each neurite in the image stack by an expert human neuro-anatomist.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/717/logo.png","https://snemi3d.grand-challenge.org/","active","5","","2013-01-15","\N","2023-11-08 00:42:00","2023-11-16 17:39:27" +"435","han-seg2023","The Head and Neck Organ-at-Risk CT & MR Segmentation Challenge","Endometrial carcinoma prediction on whole-slide images","Cancer in the region of the head and neck (HaN) is one of the most prominent cancers, for which radiotherapy represents an important treatment modality that aims to deliver a high radiation dose to the targeted cancerous cells while sparing the nearby healthy organs-at-risk (OARs). A precise three-dimensional spatial description, i.e. segmentation, of the target volumes as well as OARs is required for optimal radiation dose distribution calculation, which is primarily performed using computed tomography (CT) images. However, the HaN region contains many OARs that are poorly visible in CT, but better visible in magnetic resonance (MR) images. Although attempts have been made towards the segmentation of OARs from MR images, so far there has been no evaluation of the impact the combined analysis of CT and MR images has on the segmentation of OARs in the HaN region. The Head and Neck Organ-at-Risk Multi-Modal Segmentation Challenge aims to promote the development of new and applicatio...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/718/logo.jpg","https://han-seg2023.grand-challenge.org/","active","5","","2023-03-26","2023-12-15","2023-11-08 00:42:00","2023-11-16 17:39:30" +"436","endo-aid","Endometrial Carcinoma Detection in Pipelle biopsies","Non-rigid registration challenge for expansion microscopy","Evaluation platform as reference benchmark for algorithms that can predict endometrial carcinoma on whole-slide images of Pipelle sampled endometrial slides stained in H&E, based on the test data set used in our project.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/719/logo-challenge.png","https://endo-aid.grand-challenge.org/","active","5","","\N","\N","2023-11-08 00:42:00","2023-11-17 23:33:27" +"437","rnr-exm","Robust Non-rigid Registration Challenge for Expansion Microscopy","Xray projectomic reconstruction with skeleton segmentation","Despite the wide adoption of ExM, there are few public benchmarks to evaluate the registration pipeline, which limits the development of robust methods for real-world deployment. To address this issue, we have launched RnR-ExM, a challenge that releases 24 pairs of 3D image volumes from three different species. Participants are asked to align these pairs and submit dense deformation fields for assessment. Half of the volume pairs (the validation and test set) have annotated cell structures (nuclei, blood vessels) as registration landmarks.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/720/RnR-ExM_Logo.png","https://rnr-exm.grand-challenge.org/","active","5","","2023-02-17","2028-03-16","2023-11-08 00:42:00","2023-11-16 17:39:32" +"438","xpress","Xray Projectomic Reconstruction Extracting Segment with Skeleton","Automated lesion segmentation in PET/CT - domain generalization","In this task, we provide volumetric XNH images of cortical white matter axons from the mouse brain at 100 nm per voxel isotropic resolution. Additionally, we provide ground truth annotations for axon trajectories. Manual voxel-wise annotation of ground truth is a time-consuming bottleneck for training segmentation networks. On the other hand, skeleton-based ground truth is much faster to annotate, and sufficient to determine connectivity. Therefore, we encourage participants to develop methods to leverage skeleton-based training. To this end, we provide two types of training (validation) sets: a small volume of voxel-wise annotations and a larger volume with skeleton-based annotations. The participants will have the flexibility to use either or both of the provided annotations to train their models, and are challenged to submit an accurate voxel-wise prediction on the test volume. Entries will be evaluated on how accurately the submitted segmentations agree with the ground-truth s...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/721/XPRESS_logo_sq2-01.png","https://xpress.grand-challenge.org/","active","5","","2023-02-06","\N","2023-11-08 00:42:00","2023-11-16 17:39:34" +"439","autopet-ii","autoPET-II","Automated lesion segmentation in PET/CT - domain generalization challenge","Positron Emission Tomography / Computed Tomography (PET/CT) is an integral part of the diagnostic workup for various malignant solid tumor entities. Due to its wide applicability, Fluorodeoxyglucose (FDG) is the most widely used PET tracer in an oncological setting reflecting glucose consumption of tissues, e.g. typically increased glucose consumption of tumor lesions. As part of the clinical routine analysis, PET/CT is mostly analyzed in a qualitative way by experienced medical imaging experts. Additional quantitative evaluation of PET information would potentially allow for more precise and individualized diagnostic decisions. A crucial initial processing step for quantitative PET/CT analysis is segmentation of tumor lesions enabling accurate feature extraction, tumor characterization, oncologic staging and image-based therapy response assessment. Manual lesion segmentation is however associated with enormous effort and cost and is thus infeasible in clinical routine. Automatio...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/722/autopet-5.png","https://autopet-ii.grand-challenge.org/","completed","5","","2023-02-28","2023-09-24","2023-11-08 00:42:00","2023-11-15 21:45:49" +"440","toothfairy","ToothFairy: Cone-Beam Computed Tomography Segmentation Challenge","Toothfairy challenge: inferior alveolar canal segmentation","This is the first edition of the ToothFairy challenge organized by the University of Modena and Reggio Emilia with the collaboration of Raudboud University. This challenge aims at pushing the development of deep learning frameworks to segment the Inferior Alveolar Canal (IAC) by incrementally extending the amount of publicly available 3D-annotated Cone Beam Computed Tomography (CBCT) scans. CBCT modality is becoming increasingly important for treatment planning and diagnosis in implant dentistry and maxillofacial surgery. The three-dimensional information acquired with CBCT can be crucial to plan a vast number of surgical interventions with the aim of preserving noble anatomical structures such as the Inferior Alveolar Canal (IAC), which contains the homonymous nerve (Inferior Alveolar Nerve, IAN). Deep learning models can support medical personnel in surgical planning procedures by providing a voxel-level segmentation of the IAN automatically extracted from CBCT scans.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/723/logo.jpg","https://toothfairy.grand-challenge.org/","active","5","","2023-06-30","\N","2023-11-08 00:42:00","2023-11-17 23:33:47" +"441","spider","SPIDER","Lumbar SPIDER challenge: MRI segmentation of spinal structures","The Lumbar SPIDER Challenge focuses on the segmentation of three anatomical structures in lumbar spine MRI: vertebrae, intervertebral discs (IVDs), and spinal canal. The segmentation task requires participants to produce separate masks for each vertebra, IVD, and the spinal canal in the lumbar spine MRI volume. The numbering of the vertebrae and IVDs is not specific and may vary across different cases.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/724/SPIDER_logo_square_jsl2NDu.png","https://spider.grand-challenge.org/","active","5","","2023-07-26","2024-04-30","2023-11-08 00:42:00","2023-11-17 23:34:08" +"442","lnq2023","LNQ2023","3D lymph node segmentation for comprehensive disease evaluation","Accurate lymph node size estimation is critical for staging cancer patients, initial therapeutic management, and in longitudinal scans, assessing response to therapy. Current standard practice for quantifying lymph node size is based on a variety of criteria that use unidirectional or bidirectional measurements on just one or a few nodes, typically on just one axial slice. But humans have hundreds of lymph nodes, any number of which may be enlarged to various degrees due to disease or immune response. While a normal lymph node may be approximately 5mm in diameter, a diseased lymph node may be several cm in diameter. The mediastinum, the anatomical area between the lungs and around the heart, may contain ten or more lymph nodes, often with three or more enlarged greater than 1cm. Accurate segmentation in 3D would provide more information to evaluate lymph node disease.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/725/LNQ-square.png","https://lnq2023.grand-challenge.org/","completed","5","","2023-05-01","2023-09-30","2023-11-08 00:42:00","2023-11-17 23:34:13" +"443","arcade","ARCADE-MICCAI2023","ARCADE 2023: automatic region-based coronary artery disease diagnostics","Coronary artery disease (CAD) is a condition that affects blood supply of heart, due to buildup of atherosclerotic plaque in the coronary arteries. CAD is one of the leading death causes around the world. The most common diagnosis procedure for CAD is coronary angiography, which uses contrast material and X-rays for observation of lesions in arteries, this type of procedure showing blood flow in coronary arteries in real time what allows precise detection of stenosis and control of intraventricular interventions and stent insertions. Coronary angiography is useful diagnostic method for planning necessary revascularization procedures based on calculated occlusion and affected segment of coronary arteries. The development of automated analytical tool for lesion detection and localization is a promising strategy for increasing effectiveness of detection and treatment strategies for CAD.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/726/aRCADE__1.jpg","https://arcade.grand-challenge.org/","completed","5","","2023-06-07","2023-09-20","2023-11-08 00:42:00","2023-11-15 21:45:02" +"444","ultrasoundenhance2023","Ultrasound Image Enhancement challenge 2023","Ultrasound image enhancement challenge 2023","Ultrasound imaging is commonly used for aiding disease diagnosis and treatment, with advantages in noninvasive. Lately, medical ultrasound shows prospects revolving from expensive big-size machines in hospitals to economical hand-held devices in wider use. The barrier is that ultrasound examination with a handheld device has the drawback of low imaging quality due to hardware limitations. Toward this, ultrasound image enhancement provides a potential low-cost solution. Restoring high-quality images from low-quality ones using computer algorithms would exempt requirements for hardware improvements and promote ultrasound device revolutions and wider applications. We propose to hold the challenge of enhancement for ultrasound images in conjunction with MICCAI 2023. We will provide various ultrasound data of five organs, including the thyroid, carotid artery, liver, breast, and kidney. The challenging task is reconstructing high-quality ultrasound images from low-quality ones. A tota...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/727/logo.png","https://ultrasoundenhance2023.grand-challenge.org/","completed","5","","2023-07-10","2023-08-31","2023-11-08 00:42:00","2023-11-15 21:44:45" +"445","multicenteraorta","SEG.A. - Segmentation of the Aorta","Aortic vessel tree segmentation challenge in CT images","Segmentation, modeling and visualization of the arterial tree are still a challenge in medical image analysis. The main track of this challenge deals with the fully automatic segmentation of the aortic vessel tree in computed tomography images. Optionally, teams can submit tailored solutions for meshing and visualization of the vessel tree.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/729/logo_final_miccai.jpg","https://multicenteraorta.grand-challenge.org/","completed","5","https://arxiv.org/abs/2108.02998","2023-06-15","2023-08-15","2023-11-08 00:42:00","2023-11-17 23:34:24" +"446","sppin","Surgical Planning in Pediatric Neuroblastoma","Pediatric neuroblastoma surgical planning challenge","Neuroblastoma: Neuroblastoma is one of the most common cancers in children, accounting for 15% of pediatric cancer related deaths. This tumor originates from the symphatic nervous system, and is often located in the abdomen. Treatment of neuroblastoma includes surgical resection of the tumor, but complete resection of the tumor is often challenging. Surgical planning in Neuroblastoma: Surgical procedures can be complicated due to the neuroblastoma often being in proximity or even encasing organs and vessels in the affected area. These structures can include abdominal organs such as kidneys, liver, pancreas and spleen or big abdominal vessels such as the aorta and renal veins. During surgical planning it is essential to have a clear understanding of the neuroblastoma in relation to the relevant anatomy. Currently, magnetic resonance imaging (MRI) is used as pre-operative imaging. Studying 3D models of the tumor and relevant structures guides surgeons in the pre-operative understan...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/730/SPINN_Logo_SB_2023_03_11-09_TnwZJgK.png","https://sppin.grand-challenge.org/","completed","5","","2023-08-10","2023-09-01","2023-11-08 00:42:00","2023-11-11 01:52:06" +"447","medfm2023","Foundation Model Prompting for Medical Image Classification","Model adaptation for medical image classification challenge","In the past few years, deep learning foundation models have been trendy, especially in computer vision and natural language processing. As a result, many milestone works have been proposed, such as Vision Transformers (ViT), Generative Pretrained Transformer (GPT), and Contrastive Language-Image Pretraining (CLIP). They aim to solve many downstream tasks by utilizing the robust representation learning and generalization abilities of foundation models.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/731/logo640.png","https://medfm2023.grand-challenge.org/","active","5","","2023-07-14","2033-10-15","2023-11-08 00:42:00","2023-11-16 17:39:48" +"448","dentex","DENTEX - MICCAI23","Dental enumeration and diagnosis on panoramic x-rays","Panoramic X-rays are widely used in dental practice to provide a comprehensive view of the oral cavity and aid in treatment planning for various dental conditions. However, interpreting these images can be a time-consuming process that can distract clinicians from essential clinical activities. Moreover, misdiagnosis is a significant concern, as general practitioners may lack specialized training in radiology, and communication errors can occur due to work exhaustion.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/732/logo_diseased.png","https://dentex.grand-challenge.org/","completed","5","https://arxiv.org/abs/2303.06500","2023-04-30","2023-09-01","2023-11-08 00:42:00","2023-11-16 17:39:45" +"449","segrap2023","SegRap 2023","Multi-modal CT image segmentation challenge with 45 OARs","Radiotherapy is one of the most important cancer treatments for killing cancer cells with external beam radiation. Treatment planning is vital for radiotherapy, which sets up the radiation dose distribution for tumors and ordinary organs. The goal of planning is to ensure the cancer cells receive enough radiation and to prevent normal cells in organs-at-risk (OARs) from being damaged too much. For instance, optical nerves and chiasma in the head cannot receive too much radiation. Otherwise, the patient risks losing his/her vision. Gross Target Volume (GTV) is the position and extent of gross tumor imaged by CT scans, i.e., what can be seen. A critical step in radiation treatment planning is to delineate the boundaries of GTV and tens of OARs. However, manual delineation slice-by-slice in CT scans is tedious and time-consuming for radiation oncologists. Automatic delineation of GTV and OARs would substantially reduce the treatment planning time and therefore improve the efficiency ...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/734/segrap-logo_cLCSrpZ.png","https://segrap2023.grand-challenge.org/","completed","5","","2023-07-09","2023-09-13","2023-11-08 00:42:00","2023-11-16 17:39:47" +"450","ldctiqac2023","Low-dose Computed Tomography Perceptual Image Quality Assessment","Low-dose CT perceptual image quality assessment challenge","Image quality assessment (IQA) is extremely important in computed tomography (CT) imaging, since it facilitates the optimization of radiation dose and the development of novel algorithms in medical imaging, such as restoration. In addition, since an excessive dose of radiation can cause harmful effects in patients, generating high-quality images from low-dose images is a popular topic in the medical domain. However, even though peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) are the most widely used evaluation metrics for these algorithms, their correlation with radiologists’ opinion of the image quality has been proven to be insufficient in previous studies, since they calculate the image score based on numeric pixel values (1-3). In addition, the need for pristine reference images to calculate these metrics makes them ineffective in real clinical environments, considering that pristine, high-quality images are often impossible to obtain due to th...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/735/IQA_logo_3io1BcW.png","https://ldctiqac2023.grand-challenge.org/","completed","5","","2023-04-19","2023-07-28","2023-11-08 00:42:00","2023-11-16 17:39:58" +"451","cl-detection2023","CL-Detection 2023","Cephalometric landmark detection in lateral x-ray images","We invite you to participate in the CL-Detection 2023 cephalometric landmark detection challenge, which is held with 2023 MICCAI conference. Prof Wang is also hosting another challenge in MICCAI 2023. If you are seeking more publication opportunities, feel free to check the challenge website (Automated prediction of treatment effectiveness in ovarian cancer using histopathological images)","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/737/logo.png","https://cl-detection2023.grand-challenge.org/","completed","5","https://doi.org/10.1109/tmi.2015.2412951","2023-05-31","2023-08-15","2023-11-08 00:42:00","2023-11-16 17:39:52" +"452","surgtoolloc23","Endoscopic surgical tool localization using tool presence labels","Endoscopic surgical tool localization challenge","The ability to automatically detect and track surgical instruments in endoscopic video will enable many transformational interventions. Assessing surgical performance and efficiency, identifying skilled tool use and choreography, and planning operational and logistical aspects of OR resources are just some of the applications that would benefit. The annotations needed to train machine learning models to robustly identify and localize surgical tools, however, are difficult to obtain. Annotating bounding boxes frame-by-frame in video is tedious and time consuming, yet a wide variety of surgical tools and surgeries must be captured for robust training. Moreover, ongoing annotator training is needed to stay up to date with surgical instrument innovation. In robot-assisted surgery, potentially informative data like timestamps of instrument installation and removal, can be programmatically harvested. The ability to use only tool presence labels to localize tools would significantly redu...","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/738/grand-challenge_logo_2023.png","https://surgtoolloc23.grand-challenge.org/","completed","5","","2023-06-29","2023-09-20","2023-11-08 00:42:00","2023-11-16 17:39:53" +"453","ocelot2023","OCELOT 2023: Cell Detection from Cell-Tissue Interaction","Cell detection from cell-tissue interaction","Cell detection in histology images is one of the most important tasks in computational pathology. Recently, the OCELOT dataset was released in [1] which provides overlapping cell and tissue annotations on images acquired from multiple organs stained with H&E. [1] showed that understanding the relationship between the surrounding tissue structures and individual cells can boost cell detection performance.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/739/gc_loco_XeBK92j.png","https://ocelot2023.grand-challenge.org/","completed","5","https://arxiv.org/abs/2303.13110","2023-06-04","2023-08-04","2023-11-08 00:42:00","2023-11-16 17:39:56" +"454","thompson-challenge","The Trauma THOMPSON Challenge","Trauma thompson challenge: trauma image analysis","The primary goal of The Trauma THOMPSON Challenge is to find the best algorithms for automatic action recognition and prediction using computer vision from first-person view in the medical domain (refer to egocentric datasets of medical procedures). We offer the first egocentric view dataset of life-saving intervention (LSI) procedures with detailed annotations by medical professionals. We have collected over 200 procedure videos with environment, simulator, and type variability. Based on this dataset, the challenge we propose involves multiple tasks to encourage participants across the globe to design impactful algorithms with applications to medicine. The envisioned algorithms include action recognition, action anticipation, procedure recognition, and visual question answering (VQA).","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/742/ttlog_black_-_Copy.png","https://thompson-challenge.grand-challenge.org/","active","5","","2023-09-01","\N","2023-11-08 00:42:00","2023-11-16 17:39:57" +"455","bonbid-hie2023","Hypoxic Ischemic Encephalopathy Lesion Segmentation Challenge","Hypoxic ischemic encephalopathy lesion segmentation","Hypoxic ischemic encephalopathy (HIE) is a brain injury that occurs in 1 ~ 5/1000 term-born neonates. HIE affects around 200,000 term-born neonates every year worldwide, costing about $2 billion/year in the US alone, let alone family burdens. Although therapeutic hypothermia can reduce mortality and morbidity, yet around 60% of patients still die or develop neurocognitive deficits by 2 years of age. HIE lesion segmentation is a crucial step in clinical care of HIE. It will lead to a more accurate estimation of prognosis, a better understanding of neurological symptoms, and a timely prediction of response to therapy.","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/743/hie.png","https://bonbid-hie2023.grand-challenge.org/","completed","5","","2023-07-01","2023-09-21","2023-11-08 00:42:00","2023-11-16 17:40:00" +"456","panorama","PANORAMA","AI and radiologists at pancreatic cancer diagnosis","The PANORAMA (Pancreatic cancer diagnosis: Radiologists meet AI) study is a new prospectively designed multi-center study with over 1500 cases, established in conjunction with an international, multi-disciplinary scientific advisory board (11 experts in pancreas radiology, AI and pancreatic cancer survivor representative) ⁠—to unify and standardize present-day guidelines and to ensure meaningful validation of pancreas-AI towards clinical translation (Reinke et al., 2022).","https://rumc-gcorg-p-public.s3.amazonaws.com/logos/challenge/746/panorama_logo_square.png","https://panorama.grand-challenge.org/","completed","5","","\N","\N","2023-11-08 00:42:00","2023-11-16 17:40:02" +"457","cameo-3d","CAMEO-3D","Protein structure prediction quality assessment","Cameo Continuously Applies Quality Assessment Criteria Established By The Protein Structure Prediction Community. Since The Accuracy Requirements For Different Scientific Applications Vary, There Is No ""One Fits All"" Score. Cameo Therefore Offers A Variety Of Scores - Assessing Different Aspects Of A Prediction (Coverage, Local Accuracy, Completeness, Etc.) To Reflect These Requirements.","","https://www.cameo3d.org/modeling/3-months/","active","18","","2023-11-04","\N","2023-11-11 01:29:20","2023-11-16 22:41:57" +"458","cameo-qe-model-quality-estimation","CAMEO-QE: Model Quality Estimation","Protein structure prediction quality assessment","Cameo Continuously Applies Quality Assessment Criteria Established By The Protein Structure Prediction Community. Since The Accuracy Requirements For Different Scientific Applications Vary, There Is No ""One Fits All"" Score. Cameo Therefore Offers A Variety Of Scores - Assessing Different Aspects Of A Prediction (Coverage, Local Accuracy, Completeness, Etc.) To Reflect These Requirements.","","https://www.cameo3d.org/quality-estimation/","active","18","","2023-11-04","\N","2023-11-11 01:29:20","2023-11-16 22:41:57" +"459","cameo-3d-modeling-of-structures-and-complexes-beta","CAMEO-3D: Modeling of Structures & Complexes - BETA","Protein structure prediction quality assessment","Cameo Continuously Applies Quality Assessment Criteria Established By The Protein Structure Prediction Community. Since The Accuracy Requirements For Different Scientific Applications Vary, There Is No ""One Fits All"" Score. Cameo Therefore Offers A Variety Of Scores - Assessing Different Aspects Of A Prediction (Coverage, Local Accuracy, Completeness, Etc.) To Reflect These Requirements.","","https://beta.cameo3d.org/complete-modeling/","active","18","","2023-11-04","\N","2023-11-11 01:29:20","2023-11-16 22:41:58" +"460","pegs-dream-challenge","PEGS DREAM Challenge","","","","https://www.synapse.org/pegs","upcoming","1","","\N","\N","2023-11-13 22:48:02","2023-11-16 16:20:18" +"461","fda-data-centric-challenge","FDA Data-Centric Challenge","","","","https://www.synapse.org/fda_data_centric","upcoming","1","","\N","\N","2023-11-13 22:49:41","2023-11-16 16:18:38" +"462","ai-institute-for-dynamic-systems","AI Institute for Dynamic Systems","","","","https://www.synapse.org/#!Synapse:syn52052735","upcoming","1","","\N","\N","2023-11-13 22:51:53","2023-11-17 0:13:33" +"463","competition-nih-alzheimers-adrd-1","PREPARE Phase 1 - Find IT!","Help NIH break new ground in early Alzheimer's prediction and related dementias","The goal of the PREPARE Challenge (Pioneering Research for Early Prediction of Alzheimer's and Related Dementias EUREKA Challenge) is to inform novel approaches to early detection that might ultimately lead to more accurate tests, tools, and methodologies for clinical and research purposes. Advances in artificial intelligence (AI), machine learning (ML), and computing ecosystems increase possibilities of intelligent data collection and analysis, including better algorithms and methods that could be leveraged for the prediction of biological, psychological (cognitive), socio-behavioral, functional, and clinical changes related to AD/ADRD. This first phase, Find IT!: Data for Early Prediction, is focused on finding, curating, or contributing data to create representative and open datasets that can be used for the early prediction of AD/ADRD.","","https://www.drivendata.org/competitions/253/competition-nih-alzheimers-adrd-1/","active","18","","2023-09-01","2024-01-31","2023-11-16 21:57:03","2023-12-06 7:15:18" +"464","prepare-phase-2-build-it","PREPARE Phase 2 - Build IT!","Help NIH break new ground in early Alzheimer's prediction and related dementias","The goal of the PREPARE Challenge (Pioneering Research for Early Prediction of Alzheimer's and Related Dementias EUREKA Challenge) is to inform novel approaches to early detection that might ultimately lead to more accurate tests, tools, and methodologies for clinical and research purposes. Advances in artificial intelligence (AI), machine learning (ML), and computing ecosystems increase possibilities of intelligent data collection and analysis, including better algorithms and methods that could be leveraged for the prediction of biological, psychological (cognitive), socio-behavioral, functional, and clinical changes related to AD/ADRD. This second phase, Build IT!: Algorithms and Approaches, is focused on advancing algorithms and analytic approaches for early prediction of AD/ADRD, with an emphasis on explainability of predictions.","","","upcoming","18","","2024-09-01","\N","2023-11-17 00:09:25","2023-12-06 7:18:18" +"465","prepare-phase-3-put-it-all-together","PREPARE Phase 3 - Put IT All Together!","Help NIH break new ground in early Alzheimer's prediction and related dementias","The goal of the PREPARE Challenge (Pioneering Research for Early Prediction of Alzheimer's and Related Dementias EUREKA Challenge) is to inform novel approaches to early detection that might ultimately lead to more accurate tests, tools, and methodologies for clinical and research purposes. Advances in artificial intelligence (AI), machine learning (ML), and computing ecosystems increase possibilities of intelligent data collection and analysis, including better algorithms and methods that could be leveraged for the prediction of biological, psychological (cognitive), socio-behavioral, functional, and clinical changes related to AD/ADRD. This third phase, Put IT All Together!: Proof of Principle Demonstration, is for the top solvers from Phase 2 demonstrate algorithmic approaches on diverse datasets and share their results at an innovation event.","","","upcoming","18","","2025-03-01","\N","2023-11-17 00:09:26","2023-12-06 7:18:08" +"466","cdc-fall-narratives","Unsupervised Wisdom: Explore Medical Narratives on Older Adult Falls","Extract insights about older adult falls from emergency department narratives","Falls among adults 65 and older is the leading cause of injury-related deaths. Falls can also result in serious injuries to the head and/or broken bones. Some risk factors associated with falls can be reduced through appropriate interventions like treating vision problems, exercising for strength and balance, and removing tripping hazards in your home. Medical record narratives are a rich yet under-explored source of potential insights about how, when, and why people fall. However, narrative data sources can be difficult to work with, often requiring carefully designed, time-intensive manual coding procedures. Modern machine learning approaches to working with narrative data have the potential to effectively extract insights about older adult falls from narrative medical record data at scale. The goal in this challenge is to identify effective methods of using unsupervised machine learning to extract insights about older adult falls from emergency department narratives. Insights...","https://drivendata-public-assets.s3.amazonaws.com/cdc-banner-hands.png","https://www.drivendata.org/competitions/217/cdc-fall-narratives/","completed","18","","\N","2023-10-06","2023-12-06 06:56:06","2023-12-06 7:21:14" +"467","visiomel-melanoma","VisioMel Challenge: Predicting Melanoma Relapse","Use digitized microscopic slides to predict the likelihood of melanoma relapse","Melanoma is a cancer of the skin which develops from cells responsible for skin pigmentation. In 2020, over 325,000 people were diagnosed with skin melanoma, with 57,000 deaths in the same year.1 Melanomas represent 10% of all skin cancers and are the most dangerous due to high likelihood of metastasizing (spreading). Patients are initially diagnosed with melanoma after a pathologist examines a portion of the cancerous tissue under a microscope. At this stage, the pathologist assesses the risk of relapse—a return of cancerous cells after the melanoma has been treated—based on information such as the thickness of the tumor and the presence of an ulceration. Combined with factors such as age, sex, and medical history of the patient, these microscopic observations can help a dermatologist assess the severity of the disease and determine appropriate surgical and medical treatment. Preventative treatments can be administered to patients with high likelihood for relapse. However, these...","https://drivendata-public-assets.s3.amazonaws.com/visiomel_banner_img.jpeg","https://www.drivendata.org/competitions/1481/visiomel-melanoma/","completed","18","","\N","2023-05-11","2023-12-06 07:35:00","2023-12-06 7:52:55" +"468","competition-cervical-biopsy","TissueNet: Detect Lesions in Cervical Biopsies","Detect the most severe epithelial lesions of the uterine cervix","A biopsy is a sample of tissue examined at a microscopic level to diagnose cancer or signs of pre-cancer. While most diagnoses are still made with photonic microscopes, digital pathology has developed considerably over the past decade as it has become possible to digitize slides into ""virtual slides"" or ""whole slide images"" (WSIs). These heavy image files contain all the information required to diagnose lesions as malignant or benign. Making this diagnosis is no easy task. It requires specialized training and careful examination of microscopic tissue. Approaches in machine learning are already able to help analyze WSIs by measuring or counting areas of the image under a pathologist's supervision. In addition, computer vision has shown some potential to classify tumor subtypes, and in time may offer a powerful tool to aid pathologists in making the most accurate diagnoses. This challenge focuses on epithelial lesions of the uterine cervix, and features a unique collection of thou...","https://s3.amazonaws.com/drivendata-public-assets/sfp_comp_image.jpg","https://www.drivendata.org/competitions/67/competition-cervical-biopsy/","completed","18","","\N","2020-10-29","2023-12-06 07:52:34","2023-12-06 7:58:21" +"469","clog-loss-alzheimers-research","Clog Loss: Advance Alzheimer’s Research with Stall Catchers","Automatically classify which blood vessels are flowing and which are stalled","5.8 million Americans live with Alzheimer’s dementia, including 10% of all seniors 65 and older. Scientists at Cornell have discovered links between “stalls,” or clogged blood vessels in the brain, and Alzheimer’s. Stalls can reduce overall blood flow in the brain by 30%. The ability to prevent or remove stalls may transform how Alzheimer’s disease is treated. Stall Catchers is a citizen science project that crowdsources the analysis of Alzheimer’s disease research data provided by Cornell University’s Department of Biomedical Engineering. It resolves a pressing analytic bottleneck: for each hour of data collection it would take an entire week to analyze the results in the lab, which means an entire experimental dataset would take 6-12 months to analyze. Today, the Stall Catchers players are collectively analyzing data 5x faster than the lab while exceeding data quality requirements. The research team has realized there are aspects of this task that are best suited to uniquely h...","","https://www.drivendata.org/competitions/65/clog-loss-alzheimers-research/","completed","18","","\N","2020-08-03","2023-12-06 08:04:52","2023-12-06 8:07:15" +"470","flu-shot-learning","Flu Shot Learning: Predict H1N1 and Seasonal Flu Vaccines","Predict whether people got H1N1 and flu vaccines using information they shared","In this challenge, we will take a look at vaccination, a key public health measure used to fight infectious diseases. Vaccines provide immunization for individuals, and enough immunization in a community can further reduce the spread of diseases through ""herd immunity."" As of the launch of this competition, vaccines for the COVID-19 virus are still under development and not yet available. The competition will instead revisit the public health response to a different recent major respiratory disease pandemic. Beginning in spring 2009, a pandemic caused by the H1N1 influenza virus, colloquially named ""swine flu,"" swept across the world. Researchers estimate that in the first year, it was responsible for between 151,000 to 575,000 deaths globally. A vaccine for the H1N1 flu virus became publicly available in October 2009. In late 2009 and early 2010, the United States conducted the National 2009 H1N1 Flu Survey. This phone survey asked respondents whether they had received the H1N1...","https://drivendata-public-assets.s3.amazonaws.com/flu-vaccine.jpg","https://www.drivendata.org/competitions/66/flu-shot-learning/","active","18","","\N","2024-07-30","2023-12-06 08:10:49","2023-12-06 8:14:49" +"471","machine-learning-with-a-heart","Warm Up: Machine Learning with a Heart","Predict the presence or absence of heart disease in patients","We've all got to start somewhere. This is one of the smallest datasets on DrivenData. That makes it a great place to dive into the world of data science competitions. Get your heart thumping and try your hand at predicting heart disease.","","https://www.drivendata.org/competitions/54/machine-learning-with-a-heart/","completed","18","","\N","2019-10-30","2023-12-06 08:19:47","2023-12-06 8:21:53" +"472","dengai-predicting-disease-spread","DengAI: Predicting Disease Spread","Predict the number of dengue fever cases reported each week in 2 regions","Using environmental data collected by various U.S. Federal Government agencies—from the Centers for Disease Control and Prevention to the National Oceanic and Atmospheric Administration in the U.S. Department of Commerce—can you predict the number of dengue fever cases reported each week in San Juan, Puerto Rico and Iquitos, Peru? This is an intermediate-level practice competition. Your task is to predict the number of dengue cases each week (in each location) based on environmental variables describing changes in temperature, precipitation, vegetation, and more. An understanding of the relationship between climate and dengue dynamics can improve research initiatives and resource allocation to help fight life-threatening pandemics.","","https://www.drivendata.org/competitions/44/dengai-predicting-disease-spread/","active","18","","\N","2024-10-05","2023-12-06 08:28:42","2023-12-06 8:30:39" +"473","senior-data-science-safe-aging-with-sphere","Senior Data Science: Safe Aging with SPHERE","Predict actual activity from sensor data in seniors","This challenge is part of a large research project which centers around using sensors and algorithms to help older people live safely at home while maintaining their privacy and independence. Using passive, automated monitoring, the ultimate goal is to look out for a person's well-being without being burdensome or intrusive. To gather data, researchers in the SPHERE Inter-disciplinary Research Collaboration (IRC) equipped volunteers with accelerometers similar to those found in cell phones or fitness wearables, and then had the subjects go about normal activities of daily living in a home-like environment that was also equipped with motion detectors. After gathering a robust set of sensor data, they had multiple annotators use camera footage to establish the ground truth, labeling chunks of sensor data as one of twenty specifically chosen activities (e.g. walk, sit, stand-to-bend, ascend stairs, descend stairs, etc). Your challenge: help push forward the state of the art by pred...","","https://www.drivendata.org/competitions/42/senior-data-science-safe-aging-with-sphere/","completed","18","","\N","2016-07-31","2023-12-06 08:35:31","2023-12-06 8:44:36" +"474","countable-care-modeling-womens-health-care-decisions","Countable Care: Modeling Women's Health Care Decisions","Predict what drives women’s health care decisions in America","Recent literature suggests that the demand for women’s health care will grow over 6% by 2020. Given how rapidly the health landscape has been changing over the last 15 years, it’s increasingly important that we understand how these changes affect what care people receive, where they go for it, and how they pay. Through the National Survey of Family Growth, the CDC provides one of the few nationally representative datasets that dives deep into the questions that women face when thinking about their health. Can you predict what drives women’s health care decisions in America?","","https://www.drivendata.org/competitions/6/countable-care-modeling-womens-health-care-decisions/","completed","18","","\N","2015-04-14","2023-12-06 08:45:12","2023-12-06 8:46:00" +"475","warm-up-predict-blood-donations","Warm Up: Predict Blood Donations","Predict whether a donor will return to donate blood given their donation history","We've all got to start somewhere. This is the smallest, least complex dataset on DrivenData. That makes it a great place to dive into the world of data science competitions. Get your blood pumping and try your hand at predicting donations.","","https://www.drivendata.org/competitions/2/warm-up-predict-blood-donations/","completed","18","","\N","2019-03-21","2023-12-06 08:52:21","2023-12-06 8:53:13" +"476","genetic-engineering-attribution","Genetic Engineering Attribution Challenge","Identify the lab-of-origin for genetically engineered DNA","our goal is to create an algorithm that identifies the most likely lab-of-origin for genetically engineered DNA. Applications for genetic engineering are rapidly diversifying. Researchers across the world are using powerful new techniques in synthetic biology to solve some of the world’s most pressing challenges in medicine, agriculture, manufacturing and more. At the same time, increasingly powerful genetically engineered systems could yield unintended consequences for people, food crops, livestock, and industry. These incredible advances in capability demand tools that support accountable innovation. Genetic engineering attribution is the process of identifying the source of a genetically engineered piece of DNA. This ability ensures that scientists who have spent countless hours developing breakthrough technology get their due credit, intellectual property is protected, and responsible innovation is promoted. By connecting a genetically engineered system with its designers, s...","https://s3.amazonaws.com/drivendata-public-assets/al-green-homepage.jpg","https://www.drivendata.org/competitions/63/genetic-engineering-attribution/","completed","18","","\N","2020-10-19","2023-12-06 08:54:24","2023-12-06 8:56:29" diff --git a/apps/openchallenges/challenge-service/src/main/resources/db/migration/V1.0.0__create_tables.sql b/apps/openchallenges/challenge-service/src/main/resources/db/migration/V1.0.0__create_tables.sql index fb88dc8ce3..9a42333ec3 100644 --- a/apps/openchallenges/challenge-service/src/main/resources/db/migration/V1.0.0__create_tables.sql +++ b/apps/openchallenges/challenge-service/src/main/resources/db/migration/V1.0.0__create_tables.sql @@ -1,19 +1,18 @@ -- challenge_platform definition - CREATE TABLE `challenge_platform` ( `id` int NOT NULL AUTO_INCREMENT, `slug` varchar(255) NOT NULL UNIQUE, `name` varchar(255) NOT NULL UNIQUE, - `avatar_key` varchar(255) NOT NULL, - `website_url` varchar(255) NOT NULL, + `avatar_key` varchar(255), + `website_url` varchar(500) NOT NULL, `created_at` DATETIME DEFAULT CURRENT_TIMESTAMP, `updated_at` DATETIME DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP, PRIMARY KEY (`id`) ); --- challenge_input_data_type definition +-- challenge_input_data_type definition CREATE TABLE `challenge_input_data_type` ( `id` int NOT NULL AUTO_INCREMENT, @@ -24,36 +23,31 @@ CREATE TABLE `challenge_input_data_type` PRIMARY KEY (`id`) ); --- challenge definition +-- challenge definition CREATE TABLE `challenge` ( `id` bigint(20) NOT NULL AUTO_INCREMENT, - `slug` varchar(255) NOT NULL, - `name` varchar(255) DEFAULT NULL, + `slug` varchar(255) NOT NULL UNIQUE, + `name` varchar(255) NOT NULL, `headline` varchar(80), `description` varchar(1000) NOT NULL, - `avatar_url` varchar(255), - `website_url` varchar(255) NOT NULL, + `avatar_url` varchar(500), + `website_url` varchar(500), `status` ENUM('upcoming', 'active', 'completed'), - `difficulty` ENUM('good_for_beginners', 'intermediate', 'advanced'), `platform_id` int, - `doi` varchar(80), + `doi` varchar(120), `start_date` DATE, `end_date` DATE, - -- `email` varchar(255) DEFAULT NULL, - -- `login` varchar(255) UNIQUE, `created_at` DATETIME DEFAULT CURRENT_TIMESTAMP, `updated_at` DATETIME DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP, PRIMARY KEY (`id`), - FOREIGN KEY (`platform_id`) REFERENCES challenge_platform(`id`) + FOREIGN KEY (`platform_id`) REFERENCES challenge_platform(`id`), + CONSTRAINT slug_check CHECK (char_length(`slug`) >= 3 and `slug` REGEXP '^[a-z0-9]+(?:-[a-z0-9]+)*$') ); --- KEY `FKk9w2ogq595jbe8r2due7vv3xr` (`account_id`), --- CONSTRAINT `FKk9w2ogq595jbe8r2due7vv3xr` FOREIGN KEY (`account_id`) REFERENCES `banking_core_account` (`id`) -- challenge_organization_role definition - CREATE TABLE `challenge_contribution` ( `id` int NOT NULL AUTO_INCREMENT, @@ -62,11 +56,11 @@ CREATE TABLE `challenge_contribution` `role` ENUM('challenge_organizer', 'data_contributor', 'sponsor'), PRIMARY KEY (`id`), FOREIGN KEY (`challenge_id`) REFERENCES challenge(`id`), - CONSTRAINT unique_item UNIQUE (`id`) + CONSTRAINT unique_item UNIQUE (`challenge_id`, `organization_id`, `role`) ); --- challenge_incentive definition +-- challenge_incentive definition CREATE TABLE `challenge_incentive` ( `id` int NOT NULL AUTO_INCREMENT, @@ -78,8 +72,8 @@ CREATE TABLE `challenge_incentive` CONSTRAINT unique_item UNIQUE (`name`, `challenge_id`) ); --- challenge_submission_type definition +-- challenge_submission_type definition CREATE TABLE `challenge_submission_type` ( `id` int NOT NULL AUTO_INCREMENT, @@ -91,8 +85,8 @@ CREATE TABLE `challenge_submission_type` CONSTRAINT unique_item UNIQUE (`name`, `challenge_id`) ); --- challenge_x_challenge_input_data_type definition +-- challenge_x_challenge_input_data_type definition CREATE TABLE `challenge_x_challenge_input_data_type` ( `id` int NOT NULL AUTO_INCREMENT, @@ -105,8 +99,8 @@ CREATE TABLE `challenge_x_challenge_input_data_type` CONSTRAINT unique_item UNIQUE (`challenge_id`, `challenge_input_data_type_id`) ); --- challenge_star definition +-- challenge_star definition CREATE TABLE `challenge_star` ( `id` int NOT NULL AUTO_INCREMENT, @@ -118,14 +112,13 @@ CREATE TABLE `challenge_star` CONSTRAINT unique_item UNIQUE (`challenge_id`, `user_id`) ); --- challenge_category definition +-- challenge_category definition CREATE TABLE `challenge_category` ( `id` int NOT NULL AUTO_INCREMENT, `challenge_id` bigint(20) NOT NULL, `category` ENUM('featured'), PRIMARY KEY (`id`), - FOREIGN KEY (`challenge_id`) REFERENCES challenge(`id`), - CONSTRAINT unique_item UNIQUE (`id`) + FOREIGN KEY (`challenge_id`) REFERENCES challenge(`id`) ); diff --git a/apps/openchallenges/challenge-service/src/main/resources/openapi.yaml b/apps/openchallenges/challenge-service/src/main/resources/openapi.yaml index 7d0979b530..e89a3690f3 100644 --- a/apps/openchallenges/challenge-service/src/main/resources/openapi.yaml +++ b/apps/openchallenges/challenge-service/src/main/resources/openapi.yaml @@ -365,14 +365,6 @@ components: - desc nullable: true type: string - ChallengeDifficulty: - description: The difficulty level of a challenge. - enum: - - good_for_beginners - - intermediate - - advanced - example: intermediate - type: string ChallengeIncentive: description: The incentive type of the challenge. enum: @@ -454,12 +446,6 @@ components: type: integer direction: $ref: '#/components/schemas/ChallengeDirection' - difficulties: - description: An array of challenge difficulty levels used to filter the - results. - items: - $ref: '#/components/schemas/ChallengeDifficulty' - type: array incentives: description: An array of challenge incentive types used to filter the results. items: @@ -558,7 +544,7 @@ components: format: int64 type: integer ChallengeSlug: - description: The slug of the challenge. + description: The unique slug of the challenge. example: awesome-challenge maxLength: 255 minLength: 3 @@ -574,6 +560,7 @@ components: example: Example challenge headline maxLength: 80 minLength: 0 + nullable: true type: string ChallengeDescription: description: The description of the challenge. @@ -581,6 +568,13 @@ components: maxLength: 1000 minLength: 0 type: string + ChallengeDoi: + description: The DOI of the challenge. + example: https://doi.org/123/abc + format: url + maxLength: 120 + nullable: true + type: string ChallengePlatformId: description: The unique identifier of a challenge platform. example: 1 @@ -621,6 +615,13 @@ components: - name - slug type: object + Url: + description: A URL to the website or image. + example: https://openchallenges.io + format: url + maxLength: 500 + nullable: true + type: string ChallengeInputDataTypeId: description: The unique identifier of a challenge input data type. example: 1 @@ -678,18 +679,27 @@ components: format: date nullable: true type: string + CreatedDatetime: + description: Datetime when metadata was added to the OC database. + example: 2022-07-04T22:19:11Z + format: date-time + type: string + ModifiedDatetime: + description: Datetime when metadata was last modified in the OC database. + example: 2022-07-04T22:19:11Z + format: date-time + type: string Challenge: description: A challenge example: - avatarUrl: http://example.com/aeiou + avatarUrl: https://openchallenges.io endDate: 2017-07-21T00:00:00.000+00:00 description: This is an example description of the challenge. platform: name: name id: 1 slug: example-challenge-platform - starredCount: 0 - difficulty: intermediate + starredCount: 100 createdAt: 2022-07-04T22:19:11Z incentives: - publication @@ -697,13 +707,13 @@ components: submissionTypes: - container_image - container_image - websiteUrl: http://example.com/aeiou + websiteUrl: https://openchallenges.io name: name id: 1 headline: Example challenge headline slug: awesome-challenge startDate: 2017-07-21T00:00:00.000+00:00 - doi: doi + doi: https://doi.org/123/abc status: active inputDataTypes: - name: gene expression @@ -720,7 +730,7 @@ components: format: int64 type: integer slug: - description: The slug of the challenge. + description: The unique slug of the challenge. example: awesome-challenge maxLength: 255 minLength: 3 @@ -736,6 +746,7 @@ components: example: Example challenge headline maxLength: 80 minLength: 0 + nullable: true type: string description: description: The description of the challenge. @@ -744,18 +755,29 @@ components: minLength: 0 type: string doi: + description: The DOI of the challenge. + example: https://doi.org/123/abc + format: url + maxLength: 120 + nullable: true type: string status: $ref: '#/components/schemas/ChallengeStatus' - difficulty: - $ref: '#/components/schemas/ChallengeDifficulty' platform: $ref: '#/components/schemas/SimpleChallengePlatform' websiteUrl: + description: A URL to the website or image. + example: https://openchallenges.io format: url + maxLength: 500 + nullable: true type: string avatarUrl: + description: A URL to the website or image. + example: https://openchallenges.io format: url + maxLength: 500 + nullable: true type: string incentives: items: @@ -784,19 +806,22 @@ components: starredCount: default: 0 description: The number of times the challenge has been starred by users. + example: 100 + minimum: 0 type: integer createdAt: + description: Datetime when metadata was added to the OC database. example: 2022-07-04T22:19:11Z format: date-time type: string updatedAt: + description: Datetime when metadata was last modified in the OC database. example: 2022-07-04T22:19:11Z format: date-time type: string required: - createdAt - description - - difficulty - id - incentives - name diff --git a/apps/openchallenges/organization-service/src/main/java/org/sagebionetworks/openchallenges/organization/service/api/OrganizationApiDelegate.java b/apps/openchallenges/organization-service/src/main/java/org/sagebionetworks/openchallenges/organization/service/api/OrganizationApiDelegate.java index 892ba2ef69..861e97f63b 100644 --- a/apps/openchallenges/organization-service/src/main/java/org/sagebionetworks/openchallenges/organization/service/api/OrganizationApiDelegate.java +++ b/apps/openchallenges/organization-service/src/main/java/org/sagebionetworks/openchallenges/organization/service/api/OrganizationApiDelegate.java @@ -36,7 +36,7 @@ default ResponseEntity getOrganization(String org) { for (MediaType mediaType : MediaType.parseMediaTypes(request.getHeader("Accept"))) { if (mediaType.isCompatibleWith(MediaType.valueOf("application/json"))) { String exampleString = - "{ \"createdAt\" : \"2022-07-04T22:19:11Z\", \"avatarKey\" : \"logo/dream.png\", \"websiteUrl\" : \"https://example.com\", \"acronym\" : \"OC\", \"name\" : \"Example organization\", \"description\" : \"A description of the organization.\", \"id\" : 1, \"challengeCount\" : 10, \"login\" : \"example-org\", \"email\" : \"john.smith@example.com\", \"updatedAt\" : \"2022-07-04T22:19:11Z\" }"; + "{ \"createdAt\" : \"2022-07-04T22:19:11Z\", \"avatarKey\" : \"logo/dream.png\", \"websiteUrl\" : \"https://openchallenges.io\", \"acronym\" : \"OC\", \"name\" : \"Example organization\", \"description\" : \"A description of the organization.\", \"id\" : 1, \"challengeCount\" : 10, \"login\" : \"example-org\", \"updatedAt\" : \"2022-07-04T22:19:11Z\" }"; ApiUtil.setExampleResponse(request, "application/json", exampleString); break; } diff --git a/apps/openchallenges/organization-service/src/main/java/org/sagebionetworks/openchallenges/organization/service/model/dto/OrganizationDto.java b/apps/openchallenges/organization-service/src/main/java/org/sagebionetworks/openchallenges/organization/service/model/dto/OrganizationDto.java index ff905c5e39..48b31f2e27 100644 --- a/apps/openchallenges/organization-service/src/main/java/org/sagebionetworks/openchallenges/organization/service/model/dto/OrganizationDto.java +++ b/apps/openchallenges/organization-service/src/main/java/org/sagebionetworks/openchallenges/organization/service/model/dto/OrganizationDto.java @@ -24,23 +24,20 @@ public class OrganizationDto { @JsonProperty("name") private String name; - @JsonProperty("email") - private String email; - @JsonProperty("login") private String login; @JsonProperty("description") - private String description; + private String description = null; @JsonProperty("avatarKey") private String avatarKey; @JsonProperty("websiteUrl") - private String websiteUrl; + private String websiteUrl = null; @JsonProperty("challengeCount") - private Integer challengeCount; + private Integer challengeCount = 0; @JsonProperty("createdAt") @DateTimeFormat(iso = DateTimeFormat.ISO.DATE_TIME) @@ -83,12 +80,16 @@ public OrganizationDto name(String name) { } /** - * Get name + * The name of the organization. * * @return name */ @NotNull - @Schema(name = "name", example = "Example organization", required = true) + @Schema( + name = "name", + example = "Example organization", + description = "The name of the organization.", + required = true) public String getName() { return name; } @@ -97,38 +98,13 @@ public void setName(String name) { this.name = name; } - public OrganizationDto email(String email) { - this.email = email; - return this; - } - - /** - * An email address. - * - * @return email - */ - @NotNull - @Email - @Schema( - name = "email", - example = "john.smith@example.com", - description = "An email address.", - required = true) - public String getEmail() { - return email; - } - - public void setEmail(String email) { - this.email = email; - } - public OrganizationDto login(String login) { this.login = login; return this; } /** - * The login of an organization + * The unique login of an organization. * * @return login */ @@ -138,7 +114,7 @@ public OrganizationDto login(String login) { @Schema( name = "login", example = "example-org", - description = "The login of an organization", + description = "The unique login of an organization.", required = true) public String getLogin() { return login; @@ -154,12 +130,15 @@ public OrganizationDto description(String description) { } /** - * Get description + * A description of the organization. * * @return description */ - @NotNull - @Schema(name = "description", example = "A description of the organization.", required = true) + @Schema( + name = "description", + example = "A description of the organization.", + description = "A description of the organization.", + required = false) public String getDescription() { return description; } @@ -193,12 +172,16 @@ public OrganizationDto websiteUrl(String websiteUrl) { } /** - * Get websiteUrl + * A URL to the website or image. * * @return websiteUrl */ - @NotNull - @Schema(name = "websiteUrl", example = "https://example.com", required = true) + @Size(max = 500) + @Schema( + name = "websiteUrl", + example = "https://openchallenges.io", + description = "A URL to the website or image.", + required = false) public String getWebsiteUrl() { return websiteUrl; } @@ -213,12 +196,16 @@ public OrganizationDto challengeCount(Integer challengeCount) { } /** - * Get challengeCount minimum: 0 + * The number of challenges involving this organization. minimum: 0 * * @return challengeCount */ @Min(0) - @Schema(name = "challengeCount", example = "10", required = false) + @Schema( + name = "challengeCount", + example = "10", + description = "The number of challenges involving this organization.", + required = false) public Integer getChallengeCount() { return challengeCount; } @@ -233,13 +220,17 @@ public OrganizationDto createdAt(OffsetDateTime createdAt) { } /** - * Get createdAt + * Datetime when metadata was added to the OC database. * * @return createdAt */ @NotNull @Valid - @Schema(name = "createdAt", example = "2022-07-04T22:19:11Z", required = true) + @Schema( + name = "createdAt", + example = "2022-07-04T22:19:11Z", + description = "Datetime when metadata was added to the OC database.", + required = true) public OffsetDateTime getCreatedAt() { return createdAt; } @@ -254,13 +245,17 @@ public OrganizationDto updatedAt(OffsetDateTime updatedAt) { } /** - * Get updatedAt + * Datetime when metadata was last modified in the OC database. * * @return updatedAt */ @NotNull @Valid - @Schema(name = "updatedAt", example = "2022-07-04T22:19:11Z", required = true) + @Schema( + name = "updatedAt", + example = "2022-07-04T22:19:11Z", + description = "Datetime when metadata was last modified in the OC database.", + required = true) public OffsetDateTime getUpdatedAt() { return updatedAt; } @@ -275,11 +270,16 @@ public OrganizationDto acronym(String acronym) { } /** - * Get acronym + * An acronym of the organization. * * @return acronym */ - @Schema(name = "acronym", example = "OC", required = false) + @Size(max = 10) + @Schema( + name = "acronym", + example = "OC", + description = "An acronym of the organization.", + required = false) public String getAcronym() { return acronym; } @@ -299,7 +299,6 @@ public boolean equals(Object o) { OrganizationDto organization = (OrganizationDto) o; return Objects.equals(this.id, organization.id) && Objects.equals(this.name, organization.name) - && Objects.equals(this.email, organization.email) && Objects.equals(this.login, organization.login) && Objects.equals(this.description, organization.description) && Objects.equals(this.avatarKey, organization.avatarKey) @@ -315,7 +314,6 @@ public int hashCode() { return Objects.hash( id, name, - email, login, description, avatarKey, @@ -332,7 +330,6 @@ public String toString() { sb.append("class OrganizationDto {\n"); sb.append(" id: ").append(toIndentedString(id)).append("\n"); sb.append(" name: ").append(toIndentedString(name)).append("\n"); - sb.append(" email: ").append(toIndentedString(email)).append("\n"); sb.append(" login: ").append(toIndentedString(login)).append("\n"); sb.append(" description: ").append(toIndentedString(description)).append("\n"); sb.append(" avatarKey: ").append(toIndentedString(avatarKey)).append("\n"); diff --git a/apps/openchallenges/organization-service/src/main/java/org/sagebionetworks/openchallenges/organization/service/model/entity/OrganizationEntity.java b/apps/openchallenges/organization-service/src/main/java/org/sagebionetworks/openchallenges/organization/service/model/entity/OrganizationEntity.java index 9bb7649fa8..9315c765e9 100644 --- a/apps/openchallenges/organization-service/src/main/java/org/sagebionetworks/openchallenges/organization/service/model/entity/OrganizationEntity.java +++ b/apps/openchallenges/organization-service/src/main/java/org/sagebionetworks/openchallenges/organization/service/model/entity/OrganizationEntity.java @@ -45,9 +45,6 @@ public class OrganizationEntity { sortable = Sortable.YES) private String name; - @Column(nullable = false) - private String email; - @NaturalId(mutable = true) @Column(nullable = false, unique = true) private String login; diff --git a/apps/openchallenges/organization-service/src/main/resources/db/migration/V1.0.0__create_tables.sql b/apps/openchallenges/organization-service/src/main/resources/db/migration/V1.0.0__create_tables.sql index 972b942cb5..9546f7daa6 100644 --- a/apps/openchallenges/organization-service/src/main/resources/db/migration/V1.0.0__create_tables.sql +++ b/apps/openchallenges/organization-service/src/main/resources/db/migration/V1.0.0__create_tables.sql @@ -1,35 +1,33 @@ -- organization definition CREATE TABLE `organization` ( - `id` bigint(20) NOT NULL AUTO_INCREMENT, - `name` varchar(255) NOT NULL, - `email` varchar(255) NOT NULL, - `login` varchar(64) NOT NULL UNIQUE, - `avatar_key` varchar(255) DEFAULT NULL, - `website_url` varchar(255) DEFAULT NULL, - `description` varchar(1000) DEFAULT NULL, - `challenge_count` int, - `created_at` DATETIME DEFAULT CURRENT_TIMESTAMP, - `updated_at` DATETIME DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP, - `acronym` varchar(255) DEFAULT NULL, + `id` bigint(20) NOT NULL AUTO_INCREMENT, + `name` varchar(255) NOT NULL, + `login` varchar(64) NOT NULL UNIQUE, + `avatar_key` varchar(255) DEFAULT NULL, + `website_url` varchar(500) DEFAULT NULL, + `description` varchar(1000) DEFAULT NULL, + `challenge_count` int DEFAULT 0, + `created_at` DATETIME DEFAULT CURRENT_TIMESTAMP, + `updated_at` DATETIME DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP, + `acronym` varchar(10) DEFAULT NULL, PRIMARY KEY (`id`), - CONSTRAINT login_check CHECK (char_length(`login`) >= 2 and `login` regexp '^[a-z]') + CONSTRAINT login_check CHECK (char_length(`login`) >= 2 and `login` REGEXP '^[a-z0-9]+(?:-[a-z0-9]+)*$') ); --- organization_category definition +-- organization_category definition CREATE TABLE `organization_category` ( `id` int NOT NULL AUTO_INCREMENT, `organization_id` bigint(20) NOT NULL, `category` ENUM('featured'), PRIMARY KEY (`id`), - FOREIGN KEY (`organization_id`) REFERENCES organization(`id`), - CONSTRAINT unique_item UNIQUE (`id`) + FOREIGN KEY (`organization_id`) REFERENCES organization(`id`) ); --- contributor_roles definition +-- contributor_roles definition CREATE TABLE `challenge_contribution` ( `id` int NOT NULL AUTO_INCREMENT, @@ -38,5 +36,5 @@ CREATE TABLE `challenge_contribution` `role` ENUM('challenge_organizer', 'data_contributor', 'sponsor'), PRIMARY KEY (`id`), FOREIGN KEY (`organization_id`) REFERENCES organization(`id`), - CONSTRAINT unique_item UNIQUE (`id`) + CONSTRAINT unique_item UNIQUE (`challenge_id`, `organization_id`, `role`) ); \ No newline at end of file diff --git a/apps/openchallenges/organization-service/src/main/resources/db/organizations.csv b/apps/openchallenges/organization-service/src/main/resources/db/organizations.csv index c26ce29356..994866db84 100644 --- a/apps/openchallenges/organization-service/src/main/resources/db/organizations.csv +++ b/apps/openchallenges/organization-service/src/main/resources/db/organizations.csv @@ -1,406 +1,406 @@ -"id","name","email","login","avatar_url","website_url","description","challenge_count","created_at","updated_at","acronym" -"1","Dialogue on Reverse Engineering Assessment and Methods","dream@sagebionetworks.org","dream","logo/dream.png","https://dreamchallenges.org","DREAM Challenges use crowd-sourcing to solve complex biomedical research questions. Together, we share a vision to enable individuals and groups to collaborate openly so that the “wisdom of the crowd” provides the greatest impact on science and human health.","71","2023-08-04 07:33:09","2023-11-21 01:18:41","DREAM" -"3","Critical Assessment of protein Function Annotation","","cafa","logo/cafa.png","https://www.biofunctionprediction.org/cafa/","The Critical Assessment of protein Function Annotation algorithms (CAFA) is an experiment designed to assess the performance of computational methods dedicated to predicting protein function, often using a time challenge. Briefly, CAFA organizers provide a large number of unannotated or incompletely annotated protein sequences. The predictors then predict the function of these proteins by associating them with Gene Ontology terms or Human Phenoytpe Ontology terms. Following the prediction deadline, there is a wait period of several months during which some proteins whose functions were unknown will receive experimental verification. Those proteins constitute the benchmark set, against which the methods are tested. Other data sources include experiments by wet lab collaborators and biocuration dedicated to CAFA.","2","2023-06-23 00:00:00","2023-10-20 18:39:12","CAFA" -"4","Critical Assessment of Genome Interpretation","CAGI@genomeinterpretation.org","cagi","logo/cagi.png","https://genomeinterpretation.org/challenges.html","The Critical Assessment of Genome Interpretation (CAGI) is a community experiment to objectively assess computational methods for predicting the phenotypic impacts of genomic variation. CAGI participants are provided genetic variants and make predictions of resulting phenotypes. These predictions are evaluated against experimental data by independent assessors.","26","2023-06-23 00:00:00","2023-11-18 03:49:35","CAGI" -"7","Critical Assessment of Metagenome Interpretation","","cami","logo/cami.png","https://data.cami-challenge.org/","CAMI, the initiative for the “Critical Assessment of Metagenome Interpretation” aims to evaluate methods in metagenomics independently, comprehensively and without bias. The initiative supplies users with exhaustive quantitative data about the performance of methods in all relevant scenarios. It therefore guides users in the selection and application of methods and in their proper interpretation. Furthermore it provides valuable information to developers, allowing them to identify promising directions for their future work. CAMI organized in 2015 the first community driven benchmarking challenge in metagenomics. For the second CAMI challenge (starting on January 16th, 2019) visit https://data.cami-challenge.org","2","2023-06-23 00:00:00","2023-07-26 20:13:21","CAMI" -"9","Critical Assessment of protein Structure Prediction","casp@predictioncenter.org","casp","logo/casp.png","https://predictioncenter.org/","Our goal is to help advance the methods of identifying protein structure from sequence. The Center has been organized to provide the means of objective testing of these methods via the process of blind prediction. The Critical Assessment of protein Structure Prediction (CASP) experiments aim at establishing the current state of the art in protein structure prediction, identifying what progress has been made, and highlighting where future effort may be most productively focused.","3","2023-06-23 00:00:00","2023-10-20 18:39:35","CASP" -"12","Medical Image Computing and Computer Assisted Intervention Society","","miccai","logo/miccai.png","http://www.miccai.org/special-interest-groups/challenges/miccai-registered-challenges/","The Medical Image Computing and Computer Assisted Intervention Society (the MICCAI Society) is dedicated to the promotion, preservation and facilitation of research, education and practice in the field of medical image computing and computer assisted medical interventions including biomedical imaging and medical robotics. The Society achieves this aim through the organization and operation of annual high quality international conferences, workshops, tutorials and publications that promote and foster the exchange and dissemination of advanced knowledge, expertise and experience in the field produced by leading institutions and outstanding scientists, physicians and educators around the world. The MICCAI Society is committed to maintaining high academic standards and independence from any personal, political or commercial interests.","15","2023-06-23 00:00:00","2023-07-26 20:13:24","MICCAI" -"13","precisionFDA","PrecisionFDA@fda.hhs.gov","pfda","logo/precisionfda.png","https://precision.fda.gov/challenges","A secure, collaborative, high-performance computing platform that builds a community of experts around the analysis of biological datasets in order to advance precision medicine.","18","2023-06-23 00:00:00","2023-07-26 20:13:25","pFDA" -"15","National Institutes of Health","","nih","logo/nih.png","https://www.nih.gov/","The National Institutes of Health (NIH), a part of the U.S. Department of Health and Human Services, is the nation's medical research agency — making important discoveries that improve health and save lives.","11","2023-06-23 00:00:00","2023-10-14 06:44:12","NIH" -"16","Allen Institute","","allen-institute","logo/allen-institute.svg","https://alleninstitute.org/","The Allen Institute is an independent nonprofit bioscience research institute aimed at unlocking the mysteries of human biology through foundational science that fuels the discovery of new treatments and cures.","2","2023-06-23 00:00:00","2023-07-26 20:13:27","" -"17","ALS Therapy Alliance","Staff@lstherapyalliance.org","ata","logo/als-therapy-alliance.png","https://alstherapyalliance.org/","For over a decade, researchers and scientists have been relying on the ALS Therapy Alliance's expertise and funding to advance their studies of amyotrophic lateral sclerosis (ALS), or Lou Gehrig's disease. 2015 marks the 14th year of our annual Breakthrough ALS fundraising campaign (formerly known as Researching a Cure). The ALS Therapy Alliance's ongoing grant award process is overseen by the organization's board of award-winning researchers and scientists, as well as corporate executives and individuals who strive to learn more about the neurodegenerative disease, its cause and possible cure.","1","2023-06-23 00:00:00","2023-07-26 20:13:28","ATA" -"18","Alzheimer's Disease Neuroimaging Initiative","","adni","logo/adni.jpg","http://adni.loni.usc.edu/","The Alzheimer's Disease Neuroimaging Initiative (ADNI) unites researchers with study data as they work to define the progression of Alzheimer's disease (AD). ADNI researchers collect, validate and utilize data, including MRI and PET images, genetics, cognitive tests, CSF and blood biomarkers as predictors of the disease. Study resources and data from the North American ADNI study are available through this website, including Alzheimer's disease patients, mild cognitive impairment subjects, and elderly controls.","2","2023-06-23 00:00:00","2023-07-26 20:13:29","ADNI" -"19","Alzheimer's Research UK","","alzheimers-research-uk","logo/alzheimers-research-uk.jpg","https://www.alzheimersresearchuk.org/","Without effective treatments, one in three children born today will die with dementia. Today, there are no dementia survivors but research can change this. Alzheimer's Research UK is the UK's leading dementia research charity, dedicated to causes, diagnosis, prevention, treatment and cure. Backed by our passionate scientists and supporters, we're challenging the way people think about dementia, uniting the big thinkers in the field and funding the innovative science that will deliver a cure.","2","2023-06-23 00:00:00","2023-07-26 20:13:31","" -"20","Amazon Web Services","","aws","logo/aws.svg","https://aws.amazon.com/","Whether you're looking for compute power, database storage, content delivery, or other functionality, AWS has the services to help you build sophisticated applications with increased flexibility, scalability and reliability","1","2023-06-23 00:00:00","2023-07-26 20:13:31","AWS" -"21","American Joint Committee on Cancer","","ajcc","","https://www.facs.org/quality-programs/cancer/ajcc","Validating science, improving patient care.","1","2023-06-23 00:00:00","2023-07-26 20:13:32","AJCC" -"22","APOLLO network","cancer.proteomics@mail.nih.gov","apollo","logo/apollo.png","https://proteomics.cancer.gov/programs/apollo-network","The Applied Proteogenomics OrganizationaL Learning and Outcomes (APOLLO) network is a collaboration between NCI, the Department of Defense (DoD), and the Department of Veterans Affairs (VA) to incorporate proteogenomics into patient care as a way of looking beyond the genome, to the activity and expression of the proteins that the genome encodes. The emerging field of proteogenomics aims to better predict how patients will respond to therapy by screening their tumors for both genetic abnormalities and protein information, an approach that has been made possible in recent years due to advances in proteomic technology.","1","2023-06-23 00:00:00","2023-07-26 20:13:33","" -"23","Apple Health","","apple-health","logo/wa-healthcare-authority.jpg","https://www.hca.wa.gov/","HCA is the largest purchaser of health care in the state. We lead the effort on transforming health care through programs and initiatives that range from the administration of Apple Health (Medicaid) and behavioral health activities to developing models for value-based purchasing and health technology assessments. We use data to inform our decisions and work in collaboration with local communities to ensure that Washington residents have access to better health care at a lower cost.","14","2023-06-23 00:00:00","2023-07-26 20:13:33","" -"24","Arthritis Foundation","","arthritis-foundation","logo/arthritis-foundation.png","https://www.arthritis.org/","Live your best life with the help of a compassionate and caring community. Get empowering information and make meaningful connections. Online and in person, we are all working together to promote life-changing resources and research, push for change and create community connections that welcome, inform and uplift. This is what makes our community of millions thrive — and why we are all Champions of Yes.","1","2023-06-23 00:00:00","2023-07-26 20:13:35","" -"25","Arthritis Internet Registry","","arthritis-internet-registry","","","This organization may no longer exist, has rebranded, or has been merged under another organization.","1","2023-06-23 00:00:00","2023-11-20 18:43:42","" -"26","AstraZeneca","","astrazeneca","logo/astrazeneca.png","https://www.astrazeneca.com/","We are a global, science-led, patient-focused pharmaceutical company. We are dedicated to transforming the future of healthcare by unlocking the power of what science can do for people, society and the planet.","2","2023-06-23 00:00:00","2023-07-26 20:13:36","" -"27","Autodesk Research","autodesk.research@autodesk.com","autodesk","logo/autodesk-research.png","https://www.research.autodesk.com/","Autodesk is changing how the world is designed and made. At Autodesk Research, we advance this mission by exploring new possibilities where others see roadblocks. With a diverse team of scientists and industry experts, we conduct industrial research that helps customers design and make a better world for all.","1","2023-06-23 00:00:00","2023-07-26 20:13:36","" -"28","BC Cancer Research Centre","","bccrc","logo/bccrc.jpg","https://www.bccrc.ca/","BC Cancer Research strives to improve the lives of patients through the integration of basic biomedical research, genomics, clinical trials, health services research, cancer surveillance, population health, and the development of innovative new technology, programs, and interventions. Organized through departments and programs with various themes, BC Cancer supports groundbreaking cancer research and personalized care approaches through world-class facilities and platforms including genomics, bioinformatics, imaging, drug development and tissue banking.","1","2023-06-23 00:00:00","2023-07-26 20:13:36","BCCRC" -"29","Bellvitge Institute for Biomedical Research","info@idibell.cat","idibell","logo/idibell.jpg","https://idibell.cat/en/the-institute/","The Bellvitge Biomedical Research Institute (IDIBELL) is a research center in biomedicine promoted by the Bellvitge University Hospital and the Viladecans Hospital, both from the Catalan Health Institute, the Catalan Institute of Oncology, University of Barcelona and L'Hospitalet de Llobregat city council. In 2017, the Center for Regenerative Medicine of Barcelona (CMR[B]), now part of IDIBELL, launched the Program for Advancing the Clinical Translation of Regenerative Medicine of Catalonia (P-CMR[C]) together with IDIBELL.","1","2023-06-23 00:00:00","2023-07-26 20:13:37","IDIBELL" -"30","Berlin Institute of Health","info@bih-charite.de","bih","logo/bih.jpg","https://www.bihealth.org/en/","The mission of the BIH is medical translation: The BIH aims to translate findings from biomedical research into new approaches for personalised prediction, prevention and therapy and, conversely, to develop new research approaches from clinical observations.","1","2023-06-23 00:00:00","2023-10-14 06:42:38","BIH" -"31","Bill and Melinda Gates Foundation","","gates-foundation","logo/gates-foundation.jpg","https://www.gatesfoundation.org/","Our mission is to create a world where every person has the opportunity to live a healthy, productive life.","1","2023-06-23 00:00:00","2023-07-26 20:13:40","" -"32","Biogen","","biogen","logo/biogen.png","https://www.biogen.com/en_us/home.html","Biogen is a leading global biotechnology company that pioneers science and drives innovations for complex and devastating diseases. Biogen is advancing a pipeline of potential therapies across neurology, neuropsychiatry, specialized immunology and rare disease and remains acutely focused on its purpose of serving humanity through science while advancing a healthier, more sustainable and equitable world. Founded in 1978, Biogen has pioneered multiple breakthrough innovations including a broad portfolio of medicines to treat multiple sclerosis, the first approved treatment for spinal muscular atrophy, and two co-developed treatments to address a defining pathology of Alzheimer's disease.","1","2023-06-23 00:00:00","2023-07-26 20:13:42","" -"33","BioMarin Pharmaceutical Inc.","","biomarin","logo/biomarin.jpg","https://www.biomarin.com/","Over two decades ago when we first opened our doors, we focused on giving much-needed attention to the underserved communities of those with rare diseases. These rare disease communities mostly affected children and were often ignored. At the time, BioMarin developed the only treatments for these life-altering conditions, giving hope to patients and families. Throughout our history, we've worked tirelessly to make a difference by pursuing bold science while respecting, educating, and connecting with patients. Through our expertise in genetics and molecular biology, we have been able to develop targeted therapies that address the root cause of the exact conditions we seek to treat. Our discoveries have led us to countless breakthroughs, best-in-class treatments and many ‘firsts' in the category. We are grateful to able to better the lives of those struggling with genetic diseases.","3","2023-06-23 00:00:00","2023-07-26 20:13:44","" -"34","Booz Allen Hamilton","","booz-allen","logo/booz-allen.jpg","https://www.boozallen.com/","Booz Allen Hamilton has been at the forefront of strategy and technology for more than 100 years. Today, the firm provides management and technology consulting and engineering services to leading Fortune 500 corporations, governments, and not-for-profits across the globe. Booz Allen partners with public and private sector clients to solve their most difficult challenges through a combination of consulting, analytics, mission operations, technology, systems delivery, cybersecurity, engineering, and innovation expertise. \n\nWith international headquarters in McLean, Virginia, the firm employs more than 22,600 people globally and had revenue of $5.41 billion for the 12 months ended March 31, 2016.\n\nBooz Allen brings its pioneering work in advanced analytics—and the industry-leading expertise of its more than 600-member data science team—to transform our clients' data into actions that keep them competitive in today's data-driven economy. To learn about Booz Allen's data science ca...","13","2023-06-23 00:00:00","2023-07-26 20:13:45","" -"36","Breast Cancer Surveillance Consortium","KPWA.scc@kp.org","bcsc","logo/bcsc.jpeg","https://www.bcsc-research.org/","The Breast Cancer Surveillance Consortium (BCSC) is a collaborative network of six active breast imaging registries and two historic registries focused on research to assess and improve the delivery and quality of breast cancer screening and related outcomes in the United States. The registries perform annual linkages to tumor and pathology registries in their geographic region and are supported by a central Statistical Coordinating Center.","1","2023-06-23 00:00:00","2023-07-26 20:13:47","BCSC" -"37","Brigham and Women's Hospital","","bwh","logo/bwh.png","https://www.brighamandwomens.org/","Brigham and Women's Hospital is a world-class academic medical center based in Boston, Massachusetts. The Brigham serves patients from New England, across the United States and from 120 countries around the world. A major teaching hospital of Harvard Medical School, Brigham and Women's Hospital has a legacy of clinical excellence that continues to grow year after year.","1","2023-06-23 00:00:00","2023-07-26 20:13:47","BWH" -"38","Brigham Young University","byu-info@byu.edu","byu","logo/byu.jpg","https://www.byu.edu/","At BYU, helping students to develop their full divine potential is central to both our teaching and our scholarship. As the flagship higher education institution of The Church of Jesus Christ of Latter-day Saints, BYU strives to emit a unique light for the benefit of the world—a light that will enable BYU to be counted among the exceptional universities in the world and an essential example for the world.","1","2023-06-23 00:00:00","2023-07-26 20:13:48","BYU" -"39","BrightFocus Foundation","info@brightfocus.org","brightfocus-foundation","logo/bright-focus.jpg","https://www.brightfocus.org/","BrightFocus funds exceptional scientific research worldwide to defeat Alzheimer's disease, macular degeneration, and glaucoma and provides expert information on these heartbreaking diseases.","1","2023-06-23 00:00:00","2023-07-26 20:13:49","" -"40","Bristol Myers Squibb","","bms","logo/bms.jpg","https://www.bms.com/","At Bristol Myers Squibb, we work every day to transform patients' lives through science. We combine the agility of a biotech with the reach and resources of an established pharmaceutical company to create a global leading biopharma company powered by talented individuals who drive scientific innovation. We have the brightest people in the industry and believe that their diverse experiences and perspectives help to bring out our best ideas, drive innovation and achieve transformative business results.","2","2023-06-23 00:00:00","2023-07-26 20:13:50","BMS" -"41","Broad Institute","","broad","logo/broad.jpg","https://www.broadinstitute.org/","We seek to better understand the roots of disease and narrow the gap between new biological insights and impact for patients.","5","2023-06-23 00:00:00","2023-07-26 20:13:51","" -"42","Brown University","","brown","logo/brown.jpg","https://www.brown.edu/","Founded in 1764, Brown is a nonprofit leading research university, home to world-renowned faculty, and also an innovative educational institution where the curiosity, creativity and intellectual joy of students drives academic excellence. The spirit of the undergraduate Open Curriculum infuses every aspect of the University. Brown is a place where rigorous scholarship, complex problem-solving and service to the public good are defined by intense collaboration, intellectual discovery and working in ways that transcend traditional boundaries. As a private, nonprofit institution, the University advances its mission through support from a community invested in Brown's commitment to advance knowledge and make a positive difference locally and globally.","1","2023-06-23 00:00:00","2023-07-26 20:13:52","" -"43","California Institute of Technology","","caltech","logo/caltech.jpg","https://www.caltech.edu/","Caltech is a world-renowned science and engineering institute that marshals some of the world's brightest minds and most innovative tools to address fundamental scientific questions and pressing societal challenges.","2","2023-06-23 00:00:00","2023-07-26 20:13:52","" -"44","Cancer Imaging Archive","","tcia","logo/tcia.jpeg","https://www.cancerimagingarchive.net/","The Cancer Imaging Archive (TCIA) is a service which de-identifies and hosts a large publicly available archive of medical images of cancer. TCIA is funded by the Cancer Imaging Program (CIP), a part of the United States National Cancer Institute (NCI), and is managed by the Frederick National Laboratory for Cancer Research (FNLCR).","1","2023-06-23 00:00:00","2023-07-26 20:13:53","TCIA" -"45","Cancer Research UK","","cancer-research-uk","logo/cancer-research-uk.jpg","https://www.cancerresearchuk.org/","Cancer Research UK was formed 20 years ago, in 2002. However, our history goes back much further, to 1902, with the founding of the Imperial Cancer Research Fund. Thanks to supporters like you, our pioneering work into how to prevent, diagnose and treat cancer has benefitted millions of lives over the past 120 years. Find out more about how our research has already made a difference to patients and what we are funding right now.","1","2023-06-23 00:00:00","2023-07-26 20:13:54","" -"46","Cancer Target Discovery and Development","","ctd2","logo/ctd2.png","https://ocg.cancer.gov/programs/ctd2","The Cancer Target Discovery and Development (CTD2) Network, also known as C-T-D-Squared, is a functional genomics initiative that bridges the gap between genomics and development of effective therapeutics. The Network aims to understand tumor development, heterogeneity, drug resistance, and metastasis to develop optimal combinations of chemotherapy with immunotherapy.","4","2023-06-23 00:00:00","2023-07-26 20:13:55","CTD2" -"47","Celgene","","celgene","logo/celgene.jpg","https://www.celgene.com","This organization may no longer exist, has rebranded, or has been merged under another organization.","3","2023-06-23 00:00:00","2023-08-08 17:58:26","" -"48","Center for Research Computing","CRCSupport@nd.edu","crc","logo/crc.jpeg","https://crc.nd.edu/","The Center for Research Computing (CRC) at University of Notre Dame is an innovative and multidisciplinary research environment that supports collaboration to facilitate multidisciplinary discoveries through advanced computation, software engineering, artificial intelligence, and other digital research tools. The Center enhances the University's innovative applications of cyberinfrastructure, provides support for interdisciplinary research and education, and conducts computational research.","1","2023-06-23 00:00:00","2023-07-26 20:13:57","CRC" -"49","Cincinnati Children's Hospital Medical Center","","cchmc","logo/cchmc.jpg","https://www.cincinnatichildrens.org/","Cincinnati Children's, a nonprofit academic medical center established in 1883, is one of the oldest and most distinguished pediatric hospitals in the United States.","2","2023-06-23 00:00:00","2023-07-26 20:13:57","CCHMC" -"50","Climb 4 Kidney Cancer","","c4kc","logo/c4kc.jpg","https://climb4kc.org/","Climb 4 Kidney Cancer is a nonprofit organization that aims to raise money for kidney cancer research while bringing people together through climbing. We are physicians, scientists, survivors, and loved ones who share a passion for climbing and a passion for improving the lives of those affected by kidney cancer.","1","2023-06-23 00:00:00","2023-07-26 20:13:58","C4KC" -"51","Clinical Proteomic Tumor Analysis Consortium","","cptac","logo/cptac.png","https://proteomics.cancer.gov/programs/cptac","The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) is a national effort to accelerate the understanding of the molecular basis of cancer through the application of large-scale proteome and genome analysis, or proteogenomics.","1","2023-06-23 00:00:00","2023-07-26 20:13:58","CPTAC" -"52","Columbia University","askcuit@columbia.edu","columbia","logo/columbia.jpg","https://www.columbia.edu/","Columbia University is one of the world's most important centers of research and at the same time a distinctive and distinguished learning environment for undergraduates and graduate students in many scholarly and professional fields. The University recognizes the importance of its location in New York City and seeks to link its research and teaching to the vast resources of a great metropolis. It seeks to attract a diverse and international faculty, staff, and student body, to support research and teaching on global issues, and to create academic relationships with many countries and regions. It expects all areas of the University to advance knowledge and learning at the highest level and to convey the products of its efforts to the world.","5","2023-06-23 00:00:00","2023-07-26 20:13:59","" -"53","Conceptant","connect@conceptant.com","conceptant","logo/conceptant.webp","https://www.conceptant.com/","We want to improve humanity and the world through technology, plain and simple. Tech has so much promise to improve lives, but we felt it was constantly overshadowed by stuffy boardrooms and corporate red tape. Which is why Conceptant takes a different path, one we created. We go against the grain using creative techniques to develop cutting edge solutions while avoiding the pot holes of slow stuffy suits.","1","2023-06-23 00:00:00","2023-07-26 20:14:00","" -"54","Consejo Superior de Investigaciones Cientificas","","csic","logo/csic.jpg","https://www.csic.es/","The Higher Council for Scientific Research (CSIC) is a State Agency for scientific research and technological development, with differentiated legal personality, its own assets and treasury, functional and management autonomy, full legal capacity to act and of indefinite duration (art. 1 Statute).","1","2023-06-23 00:00:00","2023-07-26 20:14:00","CSIC" -"55","CorEvitas","info@corevitas.com","corevitas","logo/corevitas.jpeg","https://www.corevitas.com/","CorEvitas is a science-led, data intelligence company that provides the life sciences industry with the objective data and clinical insights needed to demonstrate the real-world safety, effectiveness, and patient experience of therapeutics in the post-approval setting","1","2023-06-23 00:00:00","2023-07-26 20:14:02","" -"56","Corrona","","corrona","logo/corrona.jpeg","https://www.corrona.org","This organization may no longer exist, has re-branded, or has been merged under another organization.","1","2023-06-23 00:00:00","2023-11-20 22:08:22","" -"57","Covert Lab","covert.lab@gmail.com","covert-lab","","https://www.covert.stanford.edu/","We're a scrappy bunch of scientists who like to do cutting-edge research with the latest technology (often home-made)! Our primary biological focus is in host-pathogen interactions, most particularly in terms of the innate immune system, and our technological foci are whole-cell modeling and live-cell imaging, as shown above. We're always looking for top talent - if you're a budding, intellectually ambidextrous scientist with a creative streak and an aptitude for team play, this could be the place for you!","1","2023-06-23 00:00:00","2023-10-16 21:26:03","" -"58","Dana-Farber Cancer Institute","","dfci","logo/dfci.png","https://www.dana-farber.org/","Since its founding in 1947, Dana-Farber Cancer Institute in Boston, Massachusetts has been committed to providing adults and children with cancer with the best treatment available today while developing tomorrow's cures through cutting-edge research. Read about our history, our breakthroughs, and the resources that help us support the health of our neighborhoods and communities.","5","2023-06-23 00:00:00","2023-07-26 20:14:04","DFCI" -"59","Defense Advanced Research Projects Agency","","darpa","logo/darpa.jpg","https://www.darpa.mil/","For sixty years, DARPA has held to a singular and enduring mission: to make pivotal investments in breakthrough technologies for national security. The genesis of that mission and of DARPA itself dates to the launch of Sputnik in 1957, and a commitment by the United States that, from that time forward, it would be the initiator and not the victim of strategic technological surprises. Working with innovators inside and outside of government, DARPA has repeatedly delivered on that mission, transforming revolutionary concepts and even seeming impossibilities into practical capabilities. The ultimate results have included not only game-changing military capabilities such as precision weapons and stealth technology, but also such icons of modern civilian society such as the Internet, automated voice recognition and language translation, and Global Positioning System receivers small enough to embed in myriad consumer devices.","2","2023-06-23 00:00:00","2023-10-16 21:26:51","DARPA" -"60","Department of Energy","","doe","logo/doe.jpg","https://www.energy.gov/","The mission of the Energy Department is to ensure America's security and prosperity by addressing its energy, environmental and nuclear challenges through transformative science and technology solutions.","1","2023-06-23 00:00:00","2023-07-26 20:14:06","DOE" -"61","Diagnosticos da America SA","","dasa","logo/dasa.jpeg","https://dasa.com.br/","We are Dasa. A new model that expands and integrates health care throughout life. We have brought together the largest diagnostic medicine network, a robust hospital group and the best care management company, so that nothing is missing and full care is provided. We connect spaces, technologies, knowledge, multiply specialties and become a complete company, alive and moving, always evolving. We develop the most innovative technology and health with new digital solutions that we seek in the market, via open innovation and in Dasa startups. Today we are more than 40,000 professionals ready to meet‌ ‌all‌ ‌‌‌your‌ health needs. We are for you. A comprehensive health network with a ‌grand purpose, which is to make sure you experience the best of your health every day.","1","2023-06-23 00:00:00","2023-07-26 20:14:06","DASA" -"62","DNAnexus","","dnanexus","logo/dnanexus.png","https://www.dnanexus.com/","DNAnexus(R) has built the world's most secure cloud platform and global network for scientific collaboration and accelerated discovery. We embrace challenges and partnership to tackle the world's most exciting opportunities in human health.","11","2023-06-23 00:00:00","2023-07-26 20:14:08","" -"63","Dockstore","","dockstore","logo/dockstore.jpg","https://dockstore.org/","Dockstore is a free and open source platform for sharing reusable and scalable analytical tools and workflows. It's developed by the Cancer Genome Collaboratory and used by the GA4GH.","1","2023-06-23 00:00:00","2023-07-26 20:14:08","" -"64","Duke University","","duke","logo/duke.jpg","https://duke.edu/","The mission of Duke University is to provide a superior liberal education to undergraduate students, attending not only to their intellectual growth but also to their development as adults committed to high ethical standards and full participation as leaders in their communities; to prepare future members of the learned professions for lives of skilled and ethical service by providing excellent graduate and professional education; to advance the frontiers of knowledge and contribute boldly to the international community of scholarship; to promote an intellectual environment built on a commitment to free and open inquiry; to help those who suffer, cure disease, and promote health, through sophisticated medical research and thoughtful patient care; to provide wide ranging educational opportunities, on and beyond our campuses, for traditional students, active professionals and life-long learners using the power of information technologies; and to promote a deep appreciation for the r...","3","2023-06-23 00:00:00","2023-07-26 20:14:09","" -"65","Early Signal, LLC","","easi","","http://www.earlysignal.org","This organization may no longer exist, has rebranded, or has been merged under another organization.","1","2023-06-23 00:00:00","2023-11-20 18:47:19","EaSi" -"66","Eck Institute for Global Health","","eigh","logo/eigh.jpg","https://globalhealth.nd.edu/","The University of Notre Dame's Eck Institute for Global Health (EIGH) serves as a university-wide enterprise that recognizes health as a fundamental human right and works to promote research, training, and service to advance health standards and reduce health disparities for all. The EIGH brings together multidisciplinary teams to understand and address health challenges that disproportionately affect the poor and to train the next generation of global health leaders.","1","2023-06-23 00:00:00","2023-07-26 20:14:10","EIGH" -"67","Eli Lilly and Company","","lilly","logo/lilly.png","https://www.lilly.com/","Lilly was founded in 1876 by Colonel Eli Lilly, a man committed to creating high-quality medicines that met real needs in an era of unreliable elixirs peddled by questionable characters. His charge to the generations of employees who have followed was this: ""Take what you find here and make it better and better."" More than 145 years later, we remain committed to his vision through every aspect of our business and the people we serve starting with those who take our medicines, and extending to health care professionals, employees and the communities in which we live.","3","2023-06-23 00:00:00","2023-10-16 21:27:12","" -"68","Elixir","","elixir","logo/elixir.jpg","https://www.elixirsolutions.com/","Elixir is a pharmacy benefits and services company with the scale, flexibility and expertise to help our clients achieve their unique business goals. We have been purposely built and own all the assets needed to optimize the full pharmacy care experience, including: a) An industry leading adjudication platform, offering flexibility, efficiency and data privacy protection; b) Accredited mail and specialty pharmacies, creating an exceptional member experience, waste reduction and cost savings; c) Population health services through our sister company, Health Dialog; and d) Prescription discount programs for uninsured and under-insured and Medicare Part D plans for individuals, associations and groups.","1","2023-06-23 00:00:00","2023-10-16 21:27:25","" -"69","Encyclopedia of DNA Elements Data Coordinating Center","encode-help@lists.stanford.edu","encode","logo/encode.png","https://www.encodeproject.org/","The ENCODE Data Coordination Center (DCC)'s primary task is to curate, uniformly process and validate the data generated and submitted by ENCODE Consortium members in preparation for release to the scientific community.","1","2023-06-23 00:00:00","2023-07-26 20:14:13","ENCODE" -"70","ENIGMA Consortium","enigma@ini.usc.edu","enigma","logo/enigma.jpg","http://enigma.ini.usc.edu/","The ENIGMA Consortium brings together researchers in imaging genomics to understand brain structure, function, and disease, based on brain imaging and genetic data. We welcome brain researchers, imagers, geneticists, methods developers, and others interested in cracking the neuro-genetic code!","1","2023-06-23 00:00:00","2023-07-26 20:14:13","ENIGMA" -"71","ETH Zurich","","eth","logo/eth.jpg","https://ethz.ch/en.html","Freedom and individual responsibility, entrepreneurial spirit and open-​​mindedness: ETH Zurich stands on a bedrock of true Swiss values.","2","2023-06-23 00:00:00","2023-10-16 21:27:44","ETH" -"72","Eunice Kennedy Shriver National Institute","NICHDInformationResourceCenter@mail.nih.gov","nichd","logo/nichd.jpg","https://www.nichd.nih.gov/","NICHD was founded in 1962 to investigate human development throughout the entire life process, with a focus on understanding disabilities and important events that occur during pregnancy. Since then, research conducted and funded by NICHD has helped save lives, improve wellbeing, and reduce societal costs associated with illness and disability. NICHD's mission is to lead research and training to understand human development, improve reproductive health, enhance the lives of children and adolescents, and optimize abilities for all.","1","2023-06-23 00:00:00","2023-07-26 20:14:15","NICHD" -"73","European Bioinformatics Institute","","embl-ebi","logo/embl-ebi.jpg","https://www.ebi.ac.uk/","At EMBL's European Bioinformatics Institute (EMBL-EBI), we help scientists realise the potential of big data in biology, exploiting complex information to make discoveries that benefit humankind.","8","2023-06-23 00:00:00","2023-07-26 20:14:15","EMBL-EBI" -"74","European Medicines Agency","","ema","logo/ema.jpg","https://www.ema.europa.eu/en","The mission of the European Medicines Agency (EMA) is to foster scientific excellence in the evaluation and supervision of medicines, for the benefit of public and animal health in the European Union (EU).","1","2023-06-23 00:00:00","2023-07-26 20:14:16","EMA" -"75","European Union","","eu","logo/eu.png","https://europa.eu/european-union/index_en","The common principles and values that underlie life in the EU: freedom, democracy, equality and the rule of law, promoting peace and stability.","2","2023-06-23 00:00:00","2023-10-16 21:27:57","EU" -"76","Evidation Health","","evidation","logo/evidation.png","https://evidation.com/","We believe everyday health data is the most compelling force in medicine—because under rigorous study, it's proving to be a new and exceptionally powerful lens on health. These novel discoveries—emanating from data generated and controlled by individuals—can be turned into tools they use to take control of their health. By connecting our member community to research and innovation partners across the health ecosystem, we're creating a new platform for medical advancements and innovation.","1","2023-06-23 00:00:00","2023-07-26 20:14:17","" -"77","Fehling Instruments","","fehling-instruments","logo/fehling-instruments.jpeg","https://www.fehling-instruments.de/en/","Fehling Instruments is a traditional family owned and family run company with more than thirty years of experience in the medical business. Fehling Instruments is constantly striving for excellence in function and economy of products. This objective is achieved by continuous innovation in materials, mechanics and design. Customer satisfaction is the prevailing goal of our business. Therefore, Fehling Instruments provides outstanding service in addition to quality products. Fehling Instruments develops, manufactures, and distributes surgical instruments, implants and single use products for use mainly in the OR. FI also provides all corresponding repair service. The most important target markets for Fehling Instruments are neuro surgery (spine and brain) and thoracic, cardiac and vascular surgery.","1","2023-06-23 00:00:00","2023-07-26 20:14:18","" -"78","Feinstein Institutes for Medical Research","","feinstein-institute","logo/feinstein-institute.png","https://feinstein.northwell.edu/","The Feinstein Institutes for Medical Research is the home of research at Northwell Health. In conjunction with our partners in government, academia, industry and philanthropy, we strive to advance knowledge and make innovative therapies a reality. Our researchers work to transform the treatment of conditions like lupus, arthritis, sepsis, cancer, psychiatric illness and Alzheimer's disease. As the global headquarters of bioelectronic medicine, we're exploring ways to raise the standard of medical innovation and are using electronic medical devices to signal the body to heal itself.","1","2023-06-23 00:00:00","2023-07-26 20:14:19","" -"79","Francis Crick Institute","info@crick.ac.uk","francis-crick-institute","logo/francis-crick-institute.jpeg","https://www.crick.ac.uk/","The Francis Crick Institute is a biomedical research institute working with organisations across academia, medicine and industry to make discoveries about how life works.","1","2023-06-23 00:00:00","2023-07-26 20:14:20","" -"80","Fred Hutchinson Cancer Research Center","","fred-hutch","logo/fred-hutch.jpg","https://www.fredhutch.org/","Fred Hutchinson Cancer Center unites innovative research and compassionate care to prevent and eliminate cancer and infectious disease. We're driven by the urgency of our patients, the hope of our community and our passion for discovery to pursue scientific breakthroughs and healthier lives for every person in every community.","1","2023-06-23 00:00:00","2023-07-26 20:14:21","" -"81","Genome Canada","info@genomecanada.ca","genome-canada","logo/genome-canada.png","https://www.genomecanada.ca/","Genome Canada is an independent, federally funded not-for-profit organization and a national leader for Canada's genomics ecosystem. Working in partnership, and across sectors, we invest in, and coordinate, genomics research, innovation, data and talent to generate solutions to today's biggest challenges.","3","2023-06-23 00:00:00","2023-07-26 20:14:21","" -"82","George Washington University","","gwu","logo/gwu.jpg","https://www.gwu.edu/","Since our capital city's first days, people have traveled here for many reasons. They come to explore the past and to chart new futures. They come to ask questions and to seek expert answers. They come to start discourse and to remember in silence. They come to demand change and to be that change. They come to grow. They come to learn. They come to make history and join the ranks alongside many monumental GW alumni.","2","2023-06-23 00:00:00","2023-07-26 20:14:23","GWU" -"83","Georgetown University","","georgetown","logo/georgetown.png","https://www.georgetown.edu/","We're a leading research university with a heart. Founded in the decade that the U.S. Constitution was signed, we're the nation's oldest Catholic and Jesuit university. Today we're a forward-looking, diverse community devoted to social justice, restless inquiry and respect for each person's individual needs and talents.","1","2023-06-23 00:00:00","2023-07-26 20:14:23","" -"84","German Cancer Research Center","","dkfz","logo/dkfz.jpg","https://www.dkfz.de/en/index.html","More than 450,000 people are diagnosed with cancer each year in Germany. Cancer is a disease that poses enormous challenges to research, because every cancer is different and its course can vary immensely even from one patient to the next. To perform research into cancer is the task of the German Cancer Research Center (Deutsches Krebsforschungszentrum, DKFZ) according to its statutes. DKFZ is the largest biomedical research institute in Germany and a member of the Helmholtz Association of National Research Centers. In more than 100 divisions and research groups, our more than 3,000 employees, of which more than 1,200 are scientists, are investigating the mechanisms of cancer, are identifying cancer risk factors and are trying to find strategies to prevent people from getting cancer.They are developing novel approaches to make tumor diagnosis more precise and treatment of cancer patients more successful.","2","2023-06-23 00:00:00","2023-07-26 20:14:24","DKFZ" -"85","Global Alliance for Genomics and Health","info@ga4gh.org","ga4gh","logo/ga4gh.png","https://www.ga4gh.org/","The Global Alliance for Genomics and Health (GA4GH) is an international, nonprofit alliance formed in 2013 to accelerate the potential of research and medicine to advance human health. Bringing together 600+ leading organizations working in healthcare, research, patient advocacy, life science, and information technology, the GA4GH community is working together to create frameworks and standards to enable the responsible, voluntary, and secure sharing of genomic and health-related data. All of our work builds upon the Framework for Responsible Sharing of Genomic and Health-Related Data.","1","2023-06-23 00:00:00","2023-07-26 20:14:24","GA4GH" -"86","H. Lee Moffitt Cancer Center and Research Institute","","moffitt","logo/moffitt.png","https://moffitt.org/","At Moffitt Cancer Center, we are working tirelessly in the areas of patient care, research and education to advance one step further in fighting this disease. We are committed to the health and safety of our patients and dedicated to providing expert cancer care.","1","2023-06-23 00:00:00","2023-07-26 20:14:25","" -"87","H3ABioNet","info@h3abionet.org","h3abionet","logo/h3abionet.png","https://h3abionet.org/","H3ABioNet is a Pan African Bioinformatics network comprising 28 Nodes distributed amongst 17 countries, 16 of which are African. H3ABioNet was developed to support H3Africa research projects through the development of bioinformatics capacity on the continent. Specifically H3ABioNet aims to: a) Implement a Pan African informatics infrastructure; b) Develop an H3Africa data coordinating center; c) Provide high quality informatics support to H3Africa; d) Enable and enhance innovative translational research; and e) Address outreach, development and sustainability.","1","2023-06-23 00:00:00","2023-10-16 21:28:28","" -"88","Harvard University","","harvard","logo/harvard.jpg","https://www.harvard.edu/","As a research university and nonprofit institution, Harvard is focused on creating educational opportunities for people from many lived experiences.","3","2023-06-23 00:00:00","2023-07-26 20:14:26","" -"89","Heidelberg University","","heidelberg-university","logo/heidelberg-university.jpg","https://www.heidelberg.edu/","A day at Heidelberg University is filled with connection. Whether it's walking to class, receiving one-on-one instruction from excellent faculty, or perfecting new skills at practice, students are uplifted every moment. Each time a Student Prince makes their own success, they know they have a dedicated community standing behind them.","10","2023-06-23 00:00:00","2023-07-26 20:14:27","" -"90","HistoSonics Inc.","","histosonics","logo/histosonics.jpg","https://histosonics.com/","Minimally invasive isn't minimal enough. HistoSonics(R) is developing a non-invasive, sonic beam therapy platform capable of destroying tissue at a sub-cellular level.","1","2023-06-23 00:00:00","2023-07-26 20:14:28","" -"91","Hospital for Sick Children","","sickkids","logo/sickkids.jpg","https://www.sickkids.ca/Research/","SickKids Research Institute (RI) is where over 2,000 researchers, trainees, and staff are working together to take on the toughest challenges in child health. As Canada's largest, hospital-based child health research institute, we conduct and translate groundbreaking research to improve child health outcomes, policy, and clinical care, train the next generation of researchers, and support global scientific communities with knowledge and state-of-the-art facilities. Innovation and collaboration across our seven distinct research programs have led to a number of incredible discoveries at SickKids, uncovering the mechanisms and outcomes of childhood disease. And with every research question in the lab, we are driving clinical changes.","4","2023-06-23 00:00:00","2023-07-26 20:14:28","" -"92","Human Protein Atlas","","hpa","logo/hpa.png","www.proteinatlas.org","The Human Protein Atlas is a Swedish-based program initiated in 2003 with the aim to map the expression and spatial distribution of all human proteins in cells and tissues using an integration of various omics technologies, including antibody-based imaging, mass spectrometry-based proteomics, transcriptomics and systems biology. The data is freely available in the Protein Atlas database (www.proteinatlas.org) to allow scientists both in academia and industry to freely access the data for exploration of the human proteome with the mission to accelerate life science research and drug discovery.The database is used by over 200,000 users per month and nearly 10 publications per day use data from the Protein Atlas.\n\nThe image data in the challenge comes from the HPA Cell Atlas, led by Dr. Emma Lundberg.","1","2023-06-23 00:00:00","2023-07-26 20:14:29","HPA" -"93","International Business Machines Corporation","","ibm","logo/ibm.svg","https://www.research.ibm.com/","At IBM Research we live by the scientific method. It's at the core of everything we do. We choose impact over market cycles, vision over vanity. We deeply believe that creative freedom, excellence, and integrity are essential to any breakthrough. We operate with a backbone. We don't cut corners. We take responsibility for technology and its role in society. We make decisions with a conscience — for a future that we believe is worth living in. We recognize the immense power and potential of computing — not as a commodity, but as an agent of progress and connection. This is the future, built right.","37","2023-06-23 00:00:00","2023-07-26 20:14:30","IBM" -"94","Innovative Medicines Initiative","","imi","logo/imi.png","http://www.imi.europa.eu/","At the Innovative Medicines Initiative (IMI), we are working to improve health by speeding up the development of, and patient access to, innovative medicines, particularly in areas where there is an unmet medical or social need. We do this by facilitating collaboration between the key players involved in health research, including universities, research centres, the pharmaceutical and other industries, small and medium-sized enterprises (SMEs), patient organisations, and medicines regulators. IMI is the world's biggest public-private partnership (PPP) in the life sciences. It is a partnership between the European Union (represented by the European Commission) and the European pharmaceutical industry (represented by EFPIA, the European Federation of Pharmaceutical Industries and Associations). Through the IMI2 programme, we have a €3.3 billion budget for the period 2014-2020.","1","2023-06-23 00:00:00","2023-07-26 20:14:30","IMI" -"95","Institut Curie","","institut-curie","logo/institut-curie.jpg","https://institut-curie.org/","Institut Curie is the leading cancer research and treatment centre in France and has been a recognised public utility foundation since 1921. Since its creation by Marie Curie, Institut Curie has worked on three missions: Care, Reserach, Transmission.","2","2023-06-23 00:00:00","2023-10-16 21:28:47","" -"96","Institute for Molecular Medicine Finland","","fimm","logo/fimm.png","https://www.helsinki.fi/en/hilife-helsinki-institute-life-science/units/fimm","FIMM - Institute for Molecular Medicine Finland is a translational research institute focusing on human genomics and precision medicine as part of the Helsinki Institute of Life Science HiLIFE at the University of Helsinki. FIMM has a driving mission to perform innovative research on patients and populations targeted towards understanding drivers of health and disease. We aim at delivering improvements to the safety, efficacy, and efficiency of healthcare in Finland and beyond.","1","2023-06-23 00:00:00","2023-10-16 21:28:54","FIMM" -"97","Institute of Translational Health Sciences","","iths","logo/iths.jpg","https://www.iths.org/","The Institute of Translational Health Sciences is dedicated to speeding science to the clinic for the benefit of patients and communities throughout Washington, Wyoming, Alaska, Montana, and Idaho.","1","2023-06-23 00:00:00","2023-07-26 20:14:34","ITHS" -"98","Intel","","intel","logo/intel.svg","https://www.intel.com/content/www/us/en/homepage.html","Intel(R) Software sits at the intersection of hardware, interoperability, and amazing customer experiences. We partner with the global technology ecosystem to make development EASY, OPEN, and SCALABLE so developers can do what they do best: deliver groundbreaking applications and end-to-end solutions on Intel technologies. Visit the Intel(r) Nervana(TM) AI Academy to gain access to tools, Intel optimized frameworks, libraries, technical experts and training, getting started guides, and more.","3","2023-06-23 00:00:00","2023-11-20 22:08:58","" -"99","International Cancer Genome Consortium","","icgc","logo/icgc.jpg","https://dcc.icgc.org/","The ICGC Data Portal provides many tools for visualizing, querying, and downloading cancer data, which is released on a quarterly schedule.","5","2023-06-23 00:00:00","2023-07-26 20:14:38","ICGC" -"100","International Flavors and Fragrances Inc.","","iff","logo/iff.png","https://www.iff.com/","We apply science and creativity for a better world. With the beauty of art and the precision of science, we are an international collective of thinkers who partner with customers to bring scents, tastes, experiences, ingredients and solutions for products the world craves. As a global leader in food, beverage, health, biosciences and sensorial experiences, we do a lot and continually innovate to do it better. For more than 130 years we've been focused on finding the most innovative solutions to help bring “better for you” products to market. While we have grown over the years, we remain agile in our approach and put our customers' needs at the forefront of our thinking. We offer end-to-end service that few can deliver on. Our unparalleled product portfolio is the most robust in the industry and we have leadership positions across key taste, texture, scent, nutrition, enzymes, cultures, soy proteins and probiotics categories.","1","2023-06-23 00:00:00","2023-07-26 20:14:38","IFF" -"101","International Genome Sample Resource","","igsr","logo/igsr.jpg","https://www.internationalgenome.org/home","The 1000 Genomes Project created a catalogue of common human genetic variation, using openly consented samples from people who declared themselves to be healthy. The reference data resources generated by the project remain heavily used by the biomedical science community. The International Genome Sample Resource (IGSR) maintains and shares the human genetic variation resources built by the 1000 Genomes Project. We also update the resources to the current reference assembly, add new data sets generated from the 1000 Genomes Project samples and add data from projects working with other openly consented samples.","1","2023-06-23 00:00:00","2023-07-26 20:14:39","IGSR" -"102","International Society for Computational Biology","","iscb","logo/iscb.png","https://www.iscb.org/cms_addon/conferences/ismbeccb2021/tracks/function","Society membership reflects commitment toward the advancement of computational biology. The ISCB is an international non-profit organization whose members come from the global bioinformatics and computational biology communities. The ISCB serves its global membership by providing high-quality meetings, publications, and reports on methods and tools; by disseminating key information about bioinformatics resources and relevant news from related fields; and by actively facilitating training, education, employment, career development, and networking. We advocate and provide leadership for resources and policies in support of scientific endeavors and to benefit society at large.","2","2023-06-23 00:00:00","2023-07-26 20:14:40","ISCB" -"103","Intuitive Surgical Inc.","","intuitive","logo/intuitive.jpg","https://www.intuitive.com/en-us","Intuitive advances minimally invasive care by innovating at the point of possibility. For nearly three decades we've created products and services born of inspiration and intelligence—from robotic-assisted surgical systems to data generation that unlocks the potential to benefit care systems worldwide. We work closely and collaboratively with our customers to help achieve better outcomes, better care team experiences, better patient experiences, and lower cost of care. Together, we envision a future of care that's less invasive, profoundly better, and where diseases are identified early and treated quickly so patients can get back to what matters most.","1","2023-06-23 00:00:00","2023-07-26 20:14:41","" -"104","Iowa State University","contact@iastate.edu","iowa-state-university","logo/iowa-state-university.png","https://www.iastate.edu/","Iowa State is a large university with a small feel. Forge lifelong friendships and earn a degree that will take you anywhere.","2","2023-06-23 00:00:00","2023-07-26 20:14:42","" -"105","Kaggle","","kaggle","logo/kaggle.png","https://www.kaggle.com/","Kaggle is a community of data scientists and data enthusiasts. Our platform enables you to learn from and mentor each other on your personal, academic, and professional data science journeys. \n\nTo get involved, you can [enter a machine learning competition](https://www.kaggle.com/competitions), [publish an open dataset](https://www.kaggle.com/datasets), or [share code in our reproducible data science environment](https://www.kaggle.com/kernels). \n\nKaggle's headquarters is located in San Francisco, but we have team members working from across the US and Australia. [Join our team](https://www.kaggle.com/careers) from wherever you call home.","3","2023-06-23 00:00:00","2023-11-20 22:11:41","" -"106","Kaiser Permanente Washington Health Research Institute","","kpwhri","logo/kpwhri.jpg","https://www.kpwashingtonresearch.org/","Kaiser Permanente Washington Health Research Institute (KPWHRI) is the non-proprietary, public-interest research center within Kaiser Permanente Washington, a nonprofit health system based in Seattle. Kaiser Permanente Washington provides coverage and care for more than 710,170 people in Washington. Our research produces timely, relevant findings that help people everywhere stay healthy and get the care they need. From testing new vaccines to helping people quit smoking to finding ways to delay or prevent Alzheimer's disease, our discoveries have helped millions of people worldwide lead healthier, happier lives.","1","2023-06-23 00:00:00","2023-07-26 20:14:44","KPWHRI" -"107","King's College London","","kcl","logo/kcl.jpg","https://www.kcl.ac.uk/","King's College London is an internationally renowned university delivering exceptional education and world-leading research. We are dedicated to driving positive and sustainable change in society and realising our vision of making the world a better place.","2","2023-06-23 00:00:00","2023-07-26 20:14:44","KCL" -"108","Knowledge Engine for Genomics","knoweng@illinois.edu","knoweng","logo/knoweng.png","https://knoweng.org/","KnowEnG, The Knowledge Engine for Genomics, will transform the way biomedical researchers analyze their genome-wide data by integrating multiple analytical methods derived from the most advanced data mining and machine learning research. Embedded with the breadth of existing knowledge of genes, and an intuitive and professionally designed user interface, the Knowledge Engine platform provides advanced capabilities in data analytics. The KnowEnG environment is deployed in a cloud infrastructure and will be fully available to the research community, as will be the software developed by the Center.","1","2023-06-23 00:00:00","2023-07-26 20:14:45","" -"109","Koch Institute","cancer@mit.edu","koch-institute","logo/koch-institute.jpg","https://ki.mit.edu/","At the Koch Institute for Integrative Cancer Research, we take a uniquely MIT approach to solving some of the most difficult problems in cancer. Our research combines MIT's rich traditions of interdisciplinary inquiry and technological innovation with the most advanced investigation into the fundamental biology of cancer. With an unprecedented commitment to cross-disciplinary collaboration, we are accelerating the discovery and application of new ways to detect, monitor, treat, and prevent the disease.","1","2023-06-23 00:00:00","2023-07-26 20:14:46","" -"110","Laura and John Arnold Foundation","","arnold-ventures","logo/arnold-ventures.jpg","https://www.arnoldventures.org/people/laura-arnold-john-arnold/","Arnold Ventures is a philanthropy working to improve the lives of all Americans by pursuing evidence-based solutions to our nation's most pressing problems. We fund research to better understand the root causes of broken systems that limit opportunity and create injustice. Our focus areas include Criminal Justice, Higher Education, Health, and Public Finance. In each area, we advocate for policy reforms that will lead to lasting, scalable change.","1","2023-06-23 00:00:00","2023-07-26 20:14:46","" -"111","Lausanne University Hospital","","chuv","logo/chuv.jpg","https://www.lausanneuniversityhospital.com/home","Lausanne University Hospital is one of the five university hospitals in Switzerland, with Geneva, Bern, Basel and Zurich. With its 16 clinical and medico-technical departments and their numerous services, the CHUV is renowned for its academic achievements in health care, research, and teaching. The CHUV is also a well-known center of medical education and research thanks to its collaboration with the Faculty of Biology and Medicine of the University of Lausanne and the Swiss Federal Institute of Technology in Lausanne (EPFL). Together, these institutions form a vast campus in the Lake Geneva region.","1","2023-06-23 00:00:00","2023-07-26 20:14:47","CHUV" -"112","Leukemia and Lymphoma Society","","lls","logo/lls.jpg","https://www.lls.org/","The Leukemia & Lymphoma Society (LLS) is at the forefront of the fight to cure blood cancer. We are the largest nonprofit dedicated to creating a world without blood cancers. Since 1949, we've invested more than $1.6 billion in groundbreaking research, pioneering many of today's most innovative approaches. LLS is a global leader in the fight against blood cancer.","1","2023-06-23 00:00:00","2023-07-26 20:14:48","LLS" -"113","Ligue Nationale Contre le Cancer","","ligue-cancer","logo/ligue-cancer.jpg","https://www.ligue-cancer.net/","Since 1918, the League has been fighting against cancer by being the first independent funder of research","1","2023-06-23 00:00:00","2023-07-26 20:14:48","" -"114","London's Global University","","ucl","logo/ucl.jpg","https://www.ucl.ac.uk/","Founded in 1826 in the heart of London, UCL is London's leading multidisciplinary university, with more than 16,000 staff and 50,000 students from over 150 different countries. We are a diverse community with the freedom and courage to challenge, to question and to think differently.","2","2023-06-23 00:00:00","2023-07-26 20:14:49","UCL" -"115","Ludwig Maximilian University of Munich","","lmu","logo/lmu.jpg","https://www.lmu.de/en/index.html","Ludwig-Maximilians-Universitat Munchen is a leading research university in Europe. Since its founding in 1472 it has been committed to the highest international standards of excellence in research and teaching.","2","2023-06-23 00:00:00","2023-07-26 20:14:51","LMU" -"116","Mahidol Oxford Tropical Medicine Research Unit","","moru","logo/moru.jpeg","https://www.tropmedres.ac/","The MORU Tropical Health Network, which hosts the ‘Thailand Wellcome Africa and Asia Programme', conducts targeted clinical and public health research that aims to discover and develop appropriate, practical, affordable interventions that measurably improve the health of people living in resource-limited parts of the world.","1","2023-06-23 00:00:00","2023-07-26 20:14:51","MORU" -"117","March of Dimes","","march-of-dimes","logo/march-of-dimes.jpg","https://www.marchofdimes.org/","March of Dimes is a nonprofit organization committed to ending preventable maternal health risks and death, ending preventable preterm birth and infant death and closing the health equity gap for all families.","1","2023-06-23 00:00:00","2023-07-26 20:14:51","" -"118","Massachusetts General Hospital","","mass-general","logo/mass-general.png","https://www.massgeneral.org/","In the delivery of our care, through our research and within our communities, Mass General is committed to the well-being of our patients locally and globally.","3","2023-06-23 00:00:00","2023-07-26 20:14:54","" -"119","Massachusetts Institute of Technology","","mit","logo/mit.jpg","https://www.mit.edu/","The MIT community is driven by a shared purpose: to make a better world through education, research, and innovation. We are fun and quirky, elite but not elitist, inventive and artistic, obsessed with numbers, and welcoming to talented people regardless of where they come from.","8","2023-06-23 00:00:00","2023-10-16 21:29:42","MIT" -"120","MathWorks","","mathworks","logo/mathworks.jpg","https://www.mathworks.com/","We at MathWorks believe in the importance of engineers and scientists. They increase human knowledge and profoundly improve our standard of living. We created MATLAB and Simulink to help them do their best work.","2","2023-06-23 00:00:00","2023-07-26 20:14:56","" -"121","Max Delbruck Center for Molecular Medicine","","mdc","logo/mdc.jpg","https://www.mdc-berlin.de/","The Max Delbruck Center is an internationally renowned biomedical research center in Berlin. It is named after Max Delbrück, one of the founders of modern genetics and molecular biology.","1","2023-06-23 00:00:00","2023-07-26 20:14:56","MDC" -"122","MD Anderson Cancer Center","","md-anderson","logo/md-anderson.jpg","https://www.mdanderson.org/","At MD Anderson, we understand how hard it can be to choose a hospital for cancer treatment. You've just received life-changing news, and now you have to decide how to handle it. Here are some of the reasons why MD Anderson is your best hope for cancer care.","1","2023-06-23 00:00:00","2023-07-26 20:14:57","" -"124","Memorial Sloan Kettering Cancer Center","","msk","logo/msk.jpg","https://www.mskcc.org/","The people of Memorial Sloan Kettering Cancer Center (MSK) are united by a singular mission: ending cancer for life. Our specialized care teams provide personalized, compassionate, expert care to patients of all ages. Informed by basic research done at our Sloan Kettering Institute, scientists across MSK collaborate to conduct innovative translational and clinical research that is driving a revolution in our understanding of cancer as a disease and improving the ability to prevent, diagnose, and treat it. MSK is dedicated to training the next generation of scientists and clinicians, who go on to pursue our mission at MSK and around the globe. One of the world's most respected comprehensive centers devoted exclusively to cancer, we have been recognized as one of the top two cancer hospitals in the country by U.S. News & World Report for more than 30 years.","3","2023-06-23 00:00:00","2023-10-16 21:30:31","MSK" -"125","Merck Co.","","merck","logo/merck.jpg","https://www.merck.com/","Our purpose: We use the power of leading-edge science to save and improve lives around the world. For more than 130 years, we have brought hope to humanity through the development of important medicines and vaccines. We aspire to be the premier research-intensive biopharmaceutical company in the world — and today, we are at the forefront of research to deliver innovative health solutions that advance the prevention and treatment of diseases in people and animals. We foster a diverse and inclusive global workforce and operate responsibly every day to enable a safe, sustainable and healthy future for all people and communities.","1","2023-06-23 00:00:00","2023-10-16 21:30:50","" -"126","Michael J. Fox Foundation","info@michaeljfox.org","mjff","logo/mjff.jpg","https://www.michaeljfox.org/","The Michael J. Fox Foundation is dedicated to finding a cure for Parkinson's disease through an aggressively funded research agenda and to ensuring the development of improved therapies for those living with Parkinson's today.","4","2023-06-23 00:00:00","2023-07-26 20:15:00","MJFF" -"127","MINES ParisTech","contact@mines-paristech.fr","mines-paristech","","http://www.mines-paristech.eu/","250 years of history for the Graduate School. 1 500 students. 17 research centres, 230 talented research professors, 1st school for collaborative research, a unique link with companies. Values built over the years, which we are proud to display, to maintain, to share.","1","2023-06-23 00:00:00","2023-07-26 20:15:00","" -"128","Mount Sinai","","mt-sinai","logo/mt-sinai.jpg","https://www.mountsinai.org/","The Mount Sinai Health System is an integrated health care system providing exceptional medical care to our local and global communities. Encompassing the Icahn School of Medicine at Mount Sinai and eight hospital campuses in the New York metropolitan area, as well as a large, regional ambulatory footprint, Mount Sinai is internationally acclaimed for its excellence in research, patient care, and education across a range of specialties. The Mount Sinai Health System was created from the combination of the Mount Sinai Medical Center and Continuum Health Partners, which both agreed unanimously to combine the two entities in July 2013.","28","2023-06-23 00:00:00","2023-07-26 20:15:01","" -"129","Multiple Myeloma Research Foundation","","mmrf","logo/mmrf.jpg","https://themmrf.org/","The MMRF is the largest nonprofit in the world focused on accelerating the cure for multiple myeloma. Our work is not done until each and every multiple myeloma patient has the answers they need. With our exceptional leadership, strategic collaboration and uniquely innovative approach, we are on the path to finding a cure for multiple myeloma.","1","2023-06-23 00:00:00","2023-07-26 20:15:03","MMRF" -"130","Nathan S. Kline Institute for Psychiatric Research","Webmaster@nki.rfmh.org","nki","logo/nki.png","https://www.nki.rfmh.org/","As one of the nation's most respected research centers focused on mental health, investigators at the Nathan S. Kline Institute for Psychiatric Research (NKI) study the causes, treatment, prevention, and rehabilitation of severe and persistent mental illnesses. As a facility of the New York State Office of Mental Health, founded in 1952, NKI has earned a reputation for its landmark contributions in psychiatric research, especially in the areas of psychopharmacological treatments for schizophrenia and major mood disorders, dementia research, clinical trials methodology, neuroimaging, therapeutic drug monitoring, and the application of computer technology to mental health services.","1","2023-06-23 00:00:00","2023-07-26 20:15:03","NKI" -"131","National Cancer Institute","NCIinfo@nih.gov","nci","logo/nci.jpg","https://www.cancer.gov/","The National Cancer Institute (NCI) is the federal government's principal agency for cancer research and training. NCI leads, conducts, and supports cancer research across the nation to advance scientific knowledge and help all people live longer, healthier lives.","11","2023-06-23 00:00:00","2023-07-26 20:15:04","NCI" -"132","National Center for Advancing Translational Sciences","info@ncats.nih.gov","ncats","logo/ncats.jpg","https://ncats.nih.gov/","The National Center for Advancing Translational Sciences (NCATS) — one of 27 Institutes and Centers at the National Institutes of Health (NIH) — was established to transform the translational process so that new treatments and cures for disease can be delivered to patients faster.","1","2023-06-23 00:00:00","2023-07-26 20:15:05","NCATS" -"133","National Center for Data to Health","","cd2h","","https://cd2h.org/","The National Center for Data to Health (CD2H) accelerates advancements in informatics by using findable, accessible, interoperable, and reusable (FAIR) principles to promote collaboration across the Clinical and Translational Science Awards (CTSA) Program community. CD2H tools and resources make it simple and valuable for CTSA Program members to get engaged, connect with peers, and contribute. By promoting collaboration, CD2H fosters a robust translational science informatics ecosystem that collectively develops solutions to solve clinical problems faster, more efficiently, and more effectively. CTSA Program members are poised to lead this charge by harnessing collective expertise and strengths to solve key informatics challenges. With this team science approach, advancements in translational research can ultimately improve patient care.","2","2023-06-23 00:00:00","2023-07-26 20:15:05","CD2H" -"134","National Institute of Environmental Health Sciences","","niehs","logo/niehs.png","https://www.niehs.nih.gov/","The National Institute of Environmental Health Sciences (NIEHS) is expanding and accelerating its contributions to scientific knowledge of human health and the environment, and to the health and well-being of people everywhere.","1","2023-06-23 00:00:00","2023-07-26 20:15:06","NIEHS" -"135","National Institute of General Medical Sciences","","nigms","logo/nigms.jpg","https://www.nigms.nih.gov/","The National Institute of General Medical Sciences (NIGMS) supports basic research that increases our understanding of biological processes and lays the foundation for advances in disease diagnosis, treatment, and prevention. NIGMS-funded scientists investigate how living systems work at a range of levels—from molecules and cells to tissues and organs—in research organisms, humans, and populations. Additionally, to ensure the vitality and continued productivity of the research enterprise, NIGMS provides leadership in training the next generation of scientists, enhancing the diversity of the scientific workforce, and developing research capacity throughout the country.","3","2023-06-23 00:00:00","2023-07-26 20:15:07","NIGMS" -"136","National Institute of Standards and Technology","do-webmaster@nist.gov","nist","logo/nist.png","https://www.nist.gov/","The National Institute of Standards and Technology (NIST) was founded in 1901 and is now part of the U.S. Department of Commerce. NIST is one of the nation's oldest physical science laboratories. Congress established the agency to remove a major challenge to U.S. industrial competitiveness at the time — a second-rate measurement infrastructure that lagged behind the capabilities of the United Kingdom, Germany and other economic rivals. From the smart electric power grid and electronic health records to atomic clocks, advanced nanomaterials and computer chips, innumerable products and services rely in some way on technology, measurement and standards provided by the National Institute of Standards and Technology.","3","2023-06-23 00:00:00","2023-07-26 20:15:08","NIST" -"137","National Science Foundation","","nsf","logo/nsf.jpg","https://www.nsf.gov/","The U.S. National Science Foundation is an independent federal agency that supports science and engineering in all 50 states and U.S. territories. NSF was established in 1950 by Congress to: a) Promote the progress of science. b) Advance the national health, prosperity and welfare. c) Secure the national defense.","1","2023-06-23 00:00:00","2023-10-16 21:31:24","NSF" -"138","Natural Sciences and Engineering Research Council","","nserc","logo/nserc.jpg","https://www.nserc-crsng.gc.ca/index_eng.asp","The Natural Sciences and Engineering Research Council of Canada funds visionaries, explorers and innovators who are searching for the scientific and technical breakthroughs that will benefit our country. We are Canada's largest supporter of discovery and innovation. We work with universities, colleges, businesses and not-for-profits to remove barriers, develop opportunities and attract new expertise to make Canada's research community thrive. We give Canadian scientists and engineers the means to go further because we believe in research without borders and beyond frontiers.","3","2023-06-23 00:00:00","2023-07-26 20:15:09","NSERC" -"139","Neosoma Inc.","","neosoma","logo/neosoma.jpg","https://www.neosomainc.com/","Every brain cancer patient is unique, and so is every brain tumor. Neuro-oncology teams need new tools and insights to advance the state of care. At Neosoma, our mission is to help clinicians improve outcomes by providing novel disease insights to physicians and clinical trials through innovative AI technology.","2","2023-06-23 00:00:00","2023-07-26 20:15:10","" -"140","Neurological Clinical Research Institute","NCRI-info@mgh.harvard.edu","ncri","","https://www.massgeneral.org/ncri","The Neurological Clinical Research Institute (NCRI) at Mass General is an academic research organization composed of innovative researchers experienced and passionate about designing, developing, facilitating, and conducting multicenter clinical trials in neurological diseases. Our goal is to develop new treatments for the patients we care for and for patients around the globe. We have particular expertise in ALS, Parkinson's disease and other neurodegenerative diseases.","1","2023-06-23 00:00:00","2023-07-26 20:15:11","NCRI" -"141","New York University","","nyc","logo/nyu.png","https://www.nyu.edu/","Since its founding in 1831, NYU has been an innovator in higher education, reaching out to an emerging middle class, embracing an urban identity and professional focus, and promoting a global vision that informs its 20 schools and colleges. Today, that trailblazing spirit makes NYU one of the most prominent and respected research universities in the world, featuring top-ranked academic programs and accepting fewer than one in eight undergraduates. Anchored in New York City and with degree-granting campuses in Abu Dhabi and Shanghai as well as 12 study away sites throughout the world, NYU is a leader in global education, with more international students and more students studying abroad than any other US university.","1","2023-06-23 00:00:00","2023-07-26 20:15:12","NYC" -"142","Northeast ALS Consortium","alstrials@neals.org","neals","logo/neals.jpg","https://www.neals.org/","The mission of the Northeast Amyotrophic Lateral Sclerosis Consortium(R) (NEALS) is to rapidly translate scientific advances into clinical research and new treatments for people with Amyotrophic Lateral Sclerosis (ALS) and motor neuron disease.","2","2023-06-23 00:00:00","2023-07-26 20:15:12","NEALS" -"143","Northeastern University","","neu","logo/neu.jpg","https://www.northeastern.edu/","At Northeastern, experience is our essence and ethos. It's what you gain when you make the world your classroom, your laboratory, and your platform to create change or grow your enterprise. Throughout our university network, experience draws you into society and compels you to solve its complex challenges. It makes you agile and able to reinvent yourself. To find ways of doing things differently, and better. And to seize opportunities as they unfold—anytime, anywhere.","2","2023-06-23 00:00:00","2023-07-26 20:15:13","NEU" -"144","Northwestern University","","nu","logo/nu.jpg","https://www.northwestern.edu/","Northwestern is committed to excellent teaching, innovative research and the personal and intellectual growth of its students in a diverse academic community.","2","2023-06-23 00:00:00","2023-07-26 20:15:14","NU" -"145","Novo Nordisk","","novo-nordisk","logo/novo-nordisk.jpg","https://www.novonordisk-us.com/","For more than 100 years, we have been translating the unmet medical needs of people living with a serious chronic disease into innovative medicines and delivery systems. Our treatments today are helping millions of people living with diabetes, obesity, rare bleeding disorders and growth hormone-related disorders. From our labs to our factory floors, we are discovering and developing innovative biological medicines and making them accessible to patients throughout the world.","1","2023-06-23 00:00:00","2023-07-26 20:15:15","" -"146","Numerate","","numerate","","","This organization may no longer exist, has rebranded, or has been merged under another organization.","1","2023-06-23 00:00:00","2023-08-08 17:59:10","" -"147","NVIDIA","","nvidia","logo/nvidia.png","https://www.nvidia.com/en-us/","NVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Our work in AI and the metaverse is transforming the world's largest industries and profoundly impacting society.","3","2023-06-23 00:00:00","2023-07-26 20:15:16","" -"148","Ohio State University","webmaster@osu.edu","osu","logo/osu.png","https://www.osu.edu/","Discover the Ohio State difference. We create unrivaled experiences that bring together expertise, ideas and resources that improve communities locally and globally.","2","2023-06-23 00:00:00","2023-07-26 20:15:17","OSU" -"149","Ontario Institute for Cancer Research","info@oicr.on.ca","oicr","logo/oicr.svg","https://oicr.on.ca/","The Ontario Institute for Cancer Research helps close the gap between groundbreaking cancer discoveries and life-changing patient outcomes. OICR is a research institute that collaborates with partners across Ontario and around the world to accelerate the development of new cancer research discoveries and propel them from the lab to the clinic, bringing health and economic benefits to the people of Ontario.","6","2023-06-23 00:00:00","2023-07-26 20:15:18","OICR" -"150","Oregon Health and Science University","","ohsu","logo/ohsu.jpg","https://www.ohsu.edu/","OHSU is Oregon's only public academic health center. We are a system of hospitals and clinics across Oregon and southwest Washington. We are an institution of higher learning, with schools of medicine, nursing, pharmacy, dentistry and public health - and with a network of campuses and partners throughout Oregon. We are a national research hub, with thousands of scientists developing lifesaving therapies and deeper understanding. We are a statewide economic engine and Portland's largest employer. And as a public organization, we provide services for the most vulnerable Oregonians, and outreach to improve health in communities across the state.","11","2023-06-23 00:00:00","2023-10-16 21:31:47","OHSU" -"151","Oslo University Hospital","","ous","logo/ous.png","https://oslo-universitetssykehus.no/oslo-university-hospital","​Oslo University Hospital (OUS) ​is a highly specialised hospital in charge of extensive regional and local hospital assignments and the provision of high quality services for the citizens of Oslo. The hospital also has a nationwide responsibility for a number of national and multi-regional assignments and has several national centres of competence.","1","2023-06-23 00:00:00","2023-07-26 20:15:21","OUS" -"152","Pacific Northwest National Laboratory","","pnnl","logo/pnnl.png","https://www.pnnl.gov/","Pacific Northwest National Laboratory is a different kind of national lab. PNNL advances the frontiers of knowledge, taking on some of the world's greatest science and technology challenges. Distinctive strengths in chemistry, Earth sciences, biology, and data science are central to our scientific discovery mission. Our research lays a foundation for innovations that advance sustainable energy through decarbonization and energy storage and enhance national security through nuclear materials and threat analyses. PNNL collaborates with academia in fundamental research and with industry to transition technologies to market.","2","2023-06-23 00:00:00","2023-07-26 20:15:22","PNNL" -"153","Pfizer Inc.","","pfizer","logo/pfizer.jpg","https://www.pfizer.com/","We're in relentless pursuit of breakthroughs that change patients' lives. We innovate every day to make the world a healthier place. It was Charles Pfizer's vision at the beginning and it holds true today.","1","2023-06-23 00:00:00","2023-07-26 20:15:22","" -"154","Prize4Life","","prize4life","logo/prize4life.jpeg","","Prize4Life seeks to create breakthroughs in effective treatments for Amyotrophic Lateral Sclerosis (ALS, or Lou Gehrig's Disease) using the leverage of large inducement prizes. Instead of recognizing historical accomplishments, Prize4Life has a simple formula for transformational change. We design and launch prizes that we believe are achievable in a 2-3 year timeframe and then recruit teams to compete for the prize purse. The first team to find and demonstrate the required breakthrough wins the prize.","2","2023-06-23 00:00:00","2023-11-21 01:21:14","" -"155","Project Data Sphere","","project-data-sphere","logo/project-data-sphere.jpg","https://www.projectdatasphere.org/","At Project Data Sphere®, we believe in breaking down barriers to cancer clinical trial data sharing — barriers that historically have kept valuable trial data from ultimately benefitting the patients who so selflessly participate in them. By aggregating trial data from biopharmaceutical companies, academic medical centers, and government organizations and making it freely available on our open-access platform, we have established ourselves as a premier resource for the global oncology research community. Our deep relationships with renowned oncology experts allow us to convene research collaborations that leverage the power of pooled clinical trial data and which ultimately position PDS to be a catalyst for the discovery of urgently needed new treatments while helping to make cancer trials faster, more effective, and less expensive.","1","2023-06-23 00:00:00","2023-07-26 20:15:26","" -"156","Prostate Cancer Canada","","prostate-cancer-canada","logo/prostate-cancer-canada.png","https://cancer.ca/en/","At the Canadian Cancer Society, we are committed to improving and saving lives. That's why we are always looking for new ways to prevent cancer, find it early and treat it more successfully. It's why we're always ready to give people with cancer the help and support they need to lead more fulfilling lives.","2","2023-06-23 00:00:00","2023-07-26 20:15:27","" -"157","Prostate Cancer Foundation","","pcf","logo/pcf.jpg","https://www.pcf.org/","The Prostate Cancer Foundation (PCF) funds the world's most promising research to improve the prevention, detection, and treatment of prostate cancer and ultimately cure it for good.","1","2023-06-23 00:00:00","2023-07-26 20:15:28","PCF" -"158","Providence Health and Services","","providence","logo/providence.jpg","https://www.providence.org/en","At Providence we see more than patients, we see the life that pulses through us all. That's why we're dedicated to a holistic approach to medicine that employs not only the most advanced treatments to improve outcomes, but also puts compassion and humanity at the heart of every interaction.","1","2023-06-23 00:00:00","2023-07-26 20:15:29","" -"159","QIMR Berghofer Medical Research Institute","","qimr-berghofer","logo/qimr-berghofer.jpg","https://www.qimrberghofer.edu.au/","From humble beginnings in 1945, the Queensland Institute of Medical Research, now known as QIMR Berghofer, is one of Australia's most successful medical research institutes, translating discoveries from bench to bedside for a better future of health.","1","2023-06-23 00:00:00","2023-07-26 20:15:30","" -"160","Queen's University","","queensu","logo/queensu.jpg","https://www.queensu.ca/","We stand on a strong history of scholarship, discovery, and innovation. nOur education transforms Queen's students. Our diversity enriches the community. Our research changes the world. Together, we are tackling humanity's greatest challenges.","1","2023-06-23 00:00:00","2023-07-26 20:15:31","" -"161","Radboud University Medical Center","","radboud-umc","logo/radboud-umc.jpeg","https://www.radboudumc.nl/en/research","Radboud university medical center specializes in patient care, scientific research, teaching and training. Our mission is to have a significant impact on health care. We aim to be pioneers in shaping the health care of the future. We do this in a person-centered and innovative way.","10","2023-06-23 00:00:00","2023-07-26 20:15:31","" -"162","Radiological Society of North America","","rsna","logo/rsna.png","https://www.rsna.org/","The Radiological Society of North America (RSNA(R)) is an international society of radiologists, medical physicists and other medical professionals with more than 53,400 members from 136 countries across the globe. RSNA hosts the world's premier radiology forum, drawing approximately 55,000 attendees annually to McCormick Place in Chicago, and publishes two top peer-reviewed journals: *Radiology*, the highest-impact scientific journal in the field, and *RadioGraphics*, the only journal dedicated to continuing education in radiology. The Society is based in Oak Brook, Ill.","3","2023-06-23 00:00:00","2023-10-16 21:32:38","RSNA" -"164","Ray and Dagmar Dolby Family Fund","info@dolbyventures.com","dolby-family-ventures","logo/dolby-family-ventures.jpg","http://www.dolbyventures.com/","Dolby Family Ventures is an early stage venture firm focused on building great technology companies. We partner with best-in-class innovators and strong investment syndicate partners at the seed stage of a company's development. The fund honors the legacy of Ray Dolby and his commitment to engineers and their vision to solve the world's toughest problems. Dolby Family Ventures formalizes the Dolby family's ongoing multi-generational commitment to supporting talented entrepreneurs. We work actively with entrepreneurs to implement best practices in operational finance, strategy, and board development processes.","1","2023-06-23 00:00:00","2023-07-26 20:15:34","" -"165","Rice University","","rice","logo/rice.jpg","https://www.rice.edu/","Located in an urban environment on a 300-acre tree-lined campus, Rice University seizes its advantageous position to pursue pathbreaking research and create innovative collaboration opportunities that contribute to the betterment of our world.","1","2023-06-23 00:00:00","2023-07-26 20:15:35","" -"166","Robert Wood Johnson Foundation","","rwjf","logo/rwjf.jpg","https://www.rwjf.org/","RWJF works in collaboration with policymakers, business leaders, community groups and many others. Together, we share a common interest in addressing the many harmful obstacles to wellbeing, including poverty, powerlessness, and discrimination, and advancing health equity for all. We focus on identifying, illuminating, and addressing barriers to health, particularly those caused by structural racism and its intersection with other forms of discrimination, including sexism, ableism, and prejudice based on sexual orientation. We lean on evidence to advance health equity. We cultivate leaders who work individually and collectively across sectors to address health equity. We promote policies, practices, and systems change to dismantle the structural barriers to wellbeing created by racism. And we work to amplify voices to shift national conversations and attitudes about health and health equity.","1","2023-06-23 00:00:00","2023-07-26 20:15:35","RWJF" -"167","Rockefeller University","","rockefeller","logo/rockefeller.jpg","https://www.rockefeller.edu/","The world's leading biomedical research university, Rockefeller draws top scientists and graduate students from around the world in pursuit of one mission: to conduct science for the benefit of humanity.","1","2023-06-23 00:00:00","2023-10-16 21:33:09","" -"168","Rosenberg Alzheimer's Project","","rosenberg-alzheimers-project","","","This organization may no longer exist, has rebranded, or has been merged under another organization.","1","2023-06-23 00:00:00","2023-08-08 17:59:30","" -"169","Rush University Medical Center","","rush","logo/rush.jpg","https://www.rush.edu/","Rush University System for Health is consistently recognized for our outstanding patient care, education, research and community partnerships. Learn more about our mission, history, policies and leadership.","1","2023-06-23 00:00:00","2023-07-26 20:15:38","RUSH" -"170","RWTH Aachen University","","rwth-aachen","logo/rwth-aachen.png","https://www.rwth-aachen.de/go/id/a/?lidx=1","RWTH Aachen University is a place where the future of our industrialised world is thought out. The University is proving to be a hotspot with increasing international recognition where innovative answers to global challenges are developed.","8","2023-06-23 00:00:00","2023-07-26 20:15:39","" -"171","Sage Bionetworks","info@sagebase.org","sage","logo/sage-bionetworks.png","https://sagebionetworks.org/","Sage Bionetworks is a nonprofit health research organization that is speeding the translation of science into medicine. We believe that high-quality, well-annotated data acts as the foundation of modern biomedical innovation. We dream of a world where people work together across institutional boundaries to meaningfully address major medical research problems. We incubate new ways for diverse groups of people to practice research together. We advance our practices using an integrated and iterative design cycle that plays out between our scientific teams and our core service teams. As our innovations become norms, we develop them into robust core capabilities that can be put into practice across our portfolio of research programs. This portfolio includes publicly funded programs that create data resources and knowledge bases, pre-competitive collaborations across industry partners, and federated networks of healthcare data providers. In turn, these projects provide an active p...","48","2023-06-23 00:00:00","2023-10-05 15:22:50","" -"172","Sanofi","","sanofi","logo/sanofi.jpg","https://www.sanofi.com/","We are Sanofi. We are an innovative global healthcare company, driven by one purpose: we chase the miracles of science to improve people's lives. Our teams across the world strive to transform the practice of medicine, turning the impossible into the possible for patients. We provide potentially life-changing treatments and the protection of life-saving vaccines to millions of people, and affordable access to our medicines in some of the world's poorest countries.","2","2023-06-23 00:00:00","2023-10-16 22:32:10","" -"173","Sapienza University of Rome","","sapienza","logo/sapienza.png","https://www.uniroma1.it/en/pagina-strutturale/home","Founded in 1303, Sapienza is the oldest university in Rome and the largest in Europe. Its mission is to contribute to the development of a knowledge society through research, excellence, quality education and international cooperation.","3","2023-06-23 00:00:00","2023-07-26 20:15:43","" -"174","Sartorius AG","","sartorius","logo/sartorius.jpg","https://www.sartorius.com/en","Sartorius AG is an international pharmaceutical and laboratory equipment supplier, covering the segments of Bioprocess Solutions and Lab Products & Services.","1","2023-06-23 00:00:00","2023-07-26 20:15:42","" -"175","Seattle Cancer Care Alliance","","scca","logo/fred-hutch.jpg","https://www.seattlecca.org/","SCCA is now Fred Hutchinson Cancer Center, an independent, nonprofit cancer care and research center that also serves as the cancer program for UW Medicine. The superior care you have come to expect will continue uninterrupted.","1","2023-06-23 00:00:00","2023-07-26 20:15:43","SCCA" -"176","Semmelweis University","","semmelweis-university","logo/semmelweis-university.png","https://semmelweis.hu/english/","Semmelweis University is a leading institution of higher education in Hungary and the Central European region within the area of medicine and health sciences. Its main commitment is based on the integrity of education, research and healing, which make Semmelweis University an internationally renowned centre of knowledge.","2","2023-06-23 00:00:00","2023-07-26 20:15:43","" -"177","Sentieon","​info@sentieon.com","sentieon","logo/sentieon.jpg","https://www.sentieon.com/","Sentieon(R), incorporated in July 2014, develops highly-optimized algorithms for bioinformatics applications, using the team's expertise in algorithm, software, and system optimization. Sentieon(R) is a team of professionals experienced in image processing, telecom, computational lithography, large-scale data mining, and bioinformatics. Using our accumulated expertise in modeling, optimization, machine learning, and high-performance computing, we strive to enable precision data for precision medicine.","1","2023-06-23 00:00:00","2023-07-26 20:15:44","" -"178","Siemens Healthineers","","siemens-healthineers","logo/siemens-healthineers.jpg","https://www.siemens-healthineers.com/","We pioneer breakthroughs in healthcare. For everyone. Everywhere.","1","2023-06-23 00:00:00","2023-07-26 20:15:45","" -"179","Stanford University","","stanford","logo/stanford.jpg","https://www.stanford.edu/","Stanford was founded almost 150 years ago on a bedrock of societal purpose. Our mission is to contribute to the world by educating students for lives of leadership and purposeful contribution; advancing fundamental knowledge and cultivating creativity; and accelerating solutions and amplifying their impact.","18","2023-06-23 00:00:00","2023-07-26 20:15:46","" -"180","Swiss Initiative in Systems Biology","admin@systemsx.ch","systemsx","logo/systemsx.jpg","http://www.systemsx.ch/","SystemsX.ch is the largest ever public research initiative in Switzerland and focuses specifically on a broad topical area of basic research. The initiative advances systems biology in our country with the claim of belonging to the best in the world in this area of research.","1","2023-06-23 00:00:00","2023-07-26 20:15:47","" -"181","Takeda","","takeda","logo/takeda.jpg","https://www.takeda.com/en-us/","Takeda is a patient-focused, values-based, R&D-driven global biopharmaceutical company committed to bringing Better Health and a Brighter Future to people worldwide. Our passion and pursuit of potentially life-changing treatments for patients are deeply rooted in over 230 years of distinguished history in Japan.","2","2023-06-23 00:00:00","2023-07-26 20:15:48","" -"182","Texas Biomedical Research Institute","","texas-biomedical-research-institute","logo/texas_biomed.png","https://www.txbiomed.org/","Texas Biomedical Research Institute is pioneering and sharing scientific breakthroughs to protect you, your families and our global community from the threat of infectious diseases. The Institute has an 80-year history of success that includes work on the first COVID-19 vaccine and therapies, the first Ebola treatment, the first Hepatitis-C therapy, and thousands of developmental discoveries. Texas Biomed helps create healthier communities with science that inspires new generations through STEM education programs, delivers jobs and economic impact in our community and heals through innovative research. Learn more about how you can #Stand4Science.","1","2023-06-23 00:00:00","2023-07-26 20:15:50","" -"183","The University of California-Davis","","uc-davis","logo/uc_davis.png","https://www.ucdavis.edu/","We grow California. UC Davis was founded in 1908 to serve the state of California. We do and we always will. And today, the seed that was planted those years ago has grown into one of the world's top universities.","2","2023-06-23 00:00:00","2023-07-26 20:15:51","" -"184","The University of Texas at Austin","","ut","logo/ut-austin.svg","https://www.utexas.edu/","Like the state it calls home, The University of Texas at Austin is a bold, ambitious leader supporting some 52,000 diverse students, 3,000 teaching faculty, and top national programs across 18 colleges and schools. As Texas' leading research university, UT attracts more than $650 million annually for discovery. Amid the backdrop of Austin, Texas, a city recognized for its creative and entrepreneurial spirit, the university provides a place to explore countless opportunities for tomorrow's artists, scientists, athletes, doctors, entrepreneurs and engineers.","1","2023-06-23 00:00:00","2023-07-26 20:15:52","UT" -"185","Thomas Jefferson University Hospital","","jefferson-health","logo/jefferson.jpeg","https://hospitals.jefferson.edu/","We are Jefferson. At Jefferson Health, we are reimagining health care through our service-minded and diverse community of providers and specialists. Our mission is to improve lives. We strive to be bold and innovative, while putting your health and safety first. Each day, we are focused on you.","2","2023-06-23 00:00:00","2023-07-26 20:15:52","" -"186","TracInnovations","info@tracinno.dk","tracinnovations","logo/tracinnovations.webp","https://tracinnovations.com/","TracInnovations is a Danish company established in 2015 focusing on innovative solutions for image based diagnosis and treatment. TracInnovations has developed the Tracoline system, which is a MRI Markerless Motion Tracker and Monitor System that unnoticed records patient's head movements during brain scans.","1","2023-06-23 00:00:00","2023-07-26 20:15:53","" -"187","Trinity College Institute of Neuroscience","neuroscience@tcd.ie","tcd-neuroscience","logo/tcd.png","https://www.tcd.ie/Neuroscience/","The Trinity College Institute of Neuroscience (TCIN) is a Trinity Research Institute (TRI) with 50 Principal Investigators and 250 researchers from a wide range of disciplines including Psychology, Psychiatry, Physiology, Pharmacology, Medicine, Biochemistry, Engineering, and Genetics, among others. These diverse disciplinary origins contribute to its core activities: promoting and supporting interdisciplinary basic and translational research, as well as teaching, public engagement, and national leadership in Neuroscience.","1","2023-06-23 00:00:00","2023-10-16 22:41:29","" -"188","Tulane University","","tulane","logo/tu_new_shield.svg","https://tulane.edu/","Tulane's motto - non sibi, sed suis - embodies who we are and what we stand for. We are entrepreneurs on the front lines of life-changing technologies, as well as hometown heroes. Tulanians see challenges as opportunities, and strive to improve the lives of others in our own community and around the globe.","1","2023-06-23 00:00:00","2023-10-16 22:41:38","" -"189","U.S. Food and Drug Administration","","fda","logo/fda.svg","https://www.fda.gov/home","The Food and Drug Administration is responsible for protecting the public health by ensuring the safety, efficacy, and security of human and veterinary drugs, biological products, and medical devices; and by ensuring the safety of our nation's food supply, cosmetics, and products that emit radiation. FDA also has responsibility for regulating the manufacturing, marketing, and distribution of tobacco products to protect the public health and to reduce tobacco use by minors. FDA is responsible for advancing the public health by helping to speed innovations that make medical products more effective, safer, and more affordable and by helping the public get the accurate, science-based information they need to use medical products and foods to maintain and improve their health. FDA also plays a significant role in the Nation's counterterrorism capability. FDA fulfills this responsibility by ensuring the security of the food supply and by fostering development of medical products to r...","12","2023-06-23 00:00:00","2023-07-26 20:15:55","FDA" -"190","UNC Eshelman School of Pharmacy","","unc-eshelman-school-of-pharmacy","logo/unc.png","https://pharmacy.unc.edu/","Everything we do begins and ends with a patient in mind. Developing leaders in pharmacy education, pharmacy practice and pharmaceutical sciences who make a difference in human health worldwide.","1","2023-06-23 00:00:00","2023-07-26 20:15:56","" -"191","University of Alabama","","ua","logo/ua.png","https://www.ua.edu/","We are dedicated to excellence in teaching, research and service. We provide a robust campus environment where our students can reach their greatest potential while learning from the best and brightest faculty and making a positive difference in the community, the state and the world.","1","2023-06-23 00:00:00","2023-07-26 20:15:57","UA" -"192","University of Alabama at Birmingham","","uab","logo/uab.jpg","https://www.uab.edu/home/","At UAB, we have never settled on merely finding what's next—we have helped build the future through new ideas and initiatives in the classroom, the laboratory, the studio and the clinic.","1","2023-06-23 00:00:00","2023-07-26 20:15:58","UAB" -"193","University of Arkansas for Medical Sciences","","uams","logo/uams.jpg","https://www.uams.edu/","By 2029, the University of Arkansas for Medical Sciences (UAMS) will lead Arkansas to be the healthiest state in the region through its synergies of education, clinical care, research and purposeful leadership. With this bold statement, UAMS resolved that in the coming decade its status as Arkansas' only academic health system will allow it to deliver dramatic and lasting health and health care improvements to its home state. Aiding in this vision will be its statewide network of campuses for public education and clinical outreach, along with cores of expertise in medical specialties, population health, digital health, health informatics and translational research.","1","2023-06-23 00:00:00","2023-07-26 20:15:59","UAMS" -"194","University of Basel","","university-of-basel","logo/uni_basel.svg","https://www.unibas.ch/en.html","As a comprehensive university offering a wide range of high-quality educational opportunities, the University of Basel attracts students from Switzerland and the entire world, offering them outstanding studying conditions as they work towards their bachelor's, master's or PhD degrees. Today, the University of Basel has around 13,000 students from over a hundred nations, including 2,900 PhD students. The University of Basel has seven faculties covering a wide spectrum of academic disciplines. At the same time, the university has positioned itself amidst the international competition in the form of five strategic focal areas: Life Sciences, Visual Studies, Nanosciences, Sustainability and Energy Research and European and Global Studies. In international rankings, the University of Basel is regularly placed among the 100 top universities in the world thanks to its research achievements. The University of Basel has deep roots in the economically powerful and culturally rich Basel re...","3","2023-06-23 00:00:00","2023-10-16 21:34:12","" -"195","University of California, San Diego","","ucsd","logo/ucsd.png","https://ucsd.edu/","We make changemakers. Recognized as one of the top 15 research universities worldwide, our culture of collaboration sparks discoveries that advance society and drive economic impact. Everything we do is dedicated to ensuring our students have the opportunity to become changemakers, equipped with the multidisciplinary tools needed to accelerate answers to our world's most pressing issues.","3","2023-06-23 00:00:00","2023-08-08 18:48:47","UCSD" -"196","University of California, San Francisco","","ucsf","logo/ucsf.svg","https://www.ucsf.edu/","At UC San Francisco, we are driven by the idea that when the best research, the best teaching and the best patient care converge, we can deliver breakthroughs that help heal the world. Excellence is in our DNA. From genomics and immunology to specialty care for women and children, UCSF brings together the world's leading experts in nearly every area of health. We are home to five Nobel laureates who have advanced the understanding of cancer, neurodegenerative diseases, aging and stem cells. Our hospitals and educational programs consistently rank among the best in the country, according to the latest surveys by U.S. News & World Report. We are the leading university dedicated exclusively to the health sciences.","12","2023-06-23 00:00:00","2023-08-08 18:48:39","UCSF" -"197","University of California, Santa Cruz","","ucsc","logo/uc-santa-cruz-2021.svg","https://www.ucsc.edu/","An inspired, global, public research university leading at the intersection of innovation and justice.","8","2023-06-23 00:00:00","2023-08-08 18:48:44","UCSC" -"198","University of Cincinnati","","uc","logo/uc.png","https://www.uc.edu/","The University of Cincinnati offers students a balance of educational excellence and real-world experience. UC is a public research university with an enrollment of nearly 48,000 students and is ranked No. 4 in the nation for co-ops and internships by U.S. News & World Report (No. 1 among public institutions). Today, more than 315,000 living alumni count themselves as Bearcats — united not just by their loyalty to our nationally known sports teams, but by their common love of the place, the people and the ideas that make up the University of Cincinnati.","1","2023-06-23 00:00:00","2023-07-26 20:16:03","UC" -"199","University of Colorado Anschutz Medical Campus","","cu-anschutz","logo/cu_anschutz.svg","https://www.cuanschutz.edu/","The ​University of Colorado Anschutz Medical Campus is the largest academic health center in the Rocky Mountain region at the forefront of transformative education, science, medicine and healthcare. The campus includes the University of Colorado health professional schools, multiple centers and institutes and two nationally ranked hospitals, UCHealth University of Colorado Hospital and Children's Hospital Colorado, which treat nearly 2 million patients each year. All interconnected, these organizations collaboratively improve the quality of patient care they deliver, research they conduct and health professionals they train.","4","2023-06-23 00:00:00","2023-07-26 20:16:03","" -"200","University of Connecticut","","uconn","logo/uconn.png","https://uconn.edu/","Learning and academics are about exploring the things that interest you, growing with that knowledge, and finding the path on which you'll be most successful. With 14 schools and colleges and more than 115+ undergraduate majors, you'll find what you're looking for at UConn. And what if you come up with something unique to study? You can create your own major. Whether you want to learn from the past by studying history or you want to set the course for the future with groundbreaking scientific research, learning opportunities here abound. Challenge yourself to reach new academic heights in rigorous courses taught by our expert faculty. Take advantage of undergraduate research awards including the Summer Undergraduate Research Fund or UConn IDEA Grants; study in a lab; or pursue a creative endeavor. Push yourself further, supplementing traditional coursework with enrichment such as Education Abroad or our acclaimed Honors Program. Whatever you choose, we're here to help you find y...","1","2023-06-23 00:00:00","2023-07-26 20:16:05","UCONN" -"201","University of Houston","","uh","logo/uh-primary.svg","https://www.uh.edu/","At the University of Houston, we spur innovation by encouraging the very spark of an idea to the transfer of knowledge and technology. The UH innovation ecosystem has a rich history of advancing Houston's innovation economy.","1","2023-06-23 00:00:00","2023-07-26 20:16:06","UH" -"202","University of Illinois Urbana-Champaign","","uiuc","logo/wordmark_horizontal.png","https://illinois.edu/","Illinois students, scholars, and alumni are a community with the power to change the world. With our land-grant heritage as a foundation, we pioneer innovative research that tackles global problems and expands the human experience. Our transformative learning experiences, in and out of the classroom, are designed to produce alumni who desire to make a significant, societal impact.","1","2023-06-23 00:00:00","2023-07-26 20:16:07","UIUC" -"203","University of Kent","","kent","logo/ukent.jpeg","https://www.kent.ac.uk/","Welcome to the university of ambition where desire meets determination. We stand for ambition, with our diverse community of staff and students committed to making a difference at regional, national and global level. It's something we're very proud of.","1","2023-06-23 00:00:00","2023-07-26 20:16:07","" -"204","University of Kentucky","","uk","logo/uky.png","http://www.uky.edu/","The University of Kentucky has a broad range of resources centered on a single campus in the heart of the Bluegrass. Our wide array of programs allows us to excel in multidisciplinary studies and fosters an environment of cooperative engagement across all colleges, programs, and research endeavors. Because of the lives we touch and teach, we remain anchored in our mission to Kentucky- to educate, innovate, heal, and serve. To be sure, our complex, multi-faceted mission looks different today in many ways than it did in 1865. However, our sense of responsibility to our communities on campus and across the region is resolute. The mission has evolved and grown. The vision of service to our Commonwealth and the world beyond remains the same. They remain our compass -the soul of the University of Kentucky.","1","2023-06-23 00:00:00","2023-10-16 21:36:22","UK" -"205","University of Lausanne","","unil","logo/unil-logo.svg","https://www.unil.ch/central/en/home.html","The University of Lausanne is a higher teaching and research institution composed of seven faculties with approximately 17,100 students and about 4,400 research, teaching and technical staff. Its research activities focus on three main themes: human and social sciences, life sciences and medicine, and environmental sciences. UNIL lays great store by the quality and innovation of its teaching. This is characterised by a highly interdisciplinary approach which is even reflected in the organisation of its faculties.","2","2023-06-23 00:00:00","2023-10-16 21:36:30","UNIL" -"206","University of Lisbon","","ulisboa","logo/ulisboa.png","https://www.ulisboa.pt/en","Universidade de Lisboa (ULisboa) is the largest and most prestigious university in Portugal and is one of Europe's leading universities. Heir to a university tradition that spans over seven centuries, ULisboa acquired its current status in July 2013, following the merger of the former Universidade Técnica de Lisboa and Universidade de Lisboa. ULisboa brings together various areas of knowledge and has a privileged position for facilitating the contemporary evolution of science, technology, arts and humanities. The quality of teaching, research, innovation and culture of ULisboa is attracting an ever increasing amount of talent from around the world.","2","2023-06-23 00:00:00","2023-07-26 20:16:10","" -"207","University of London","","uol","logo/uol.jpg","https://london.ac.uk/","The University of London is the UK's leading provider of digital and blended distance education internationally, offering programmes to 45,000 students in 190 countries around the world. Although proudly rooted in London, our community and impact are global. We are a national leader in the humanities, and we promote their value to society and the economy through knowledge creation and exchange. We are also a federation of 17 esteemed higher education institutions, with collaboration at the heart of our ethos. The University of London federation is a collective community of more than 240,000 learners and 50,000 staff, delivering world-leading research across all disciplines. Our passion for increasing access to education and mobilising the collective power and expertise of the federation is central to our ability to transform lives around the world and address the global challenges of the future.","2","2023-06-23 00:00:00","2023-07-26 20:16:10","UoL" -"208","University of Luxembourg","","university-of-luxembourg","logo/university-of-luxembourg.png","https://wwwen.uni.lu/","Founded in 2003, the University of Luxembourg is the only public university of the Grand Duchy of Luxembourg. Multilingual, international and research-oriented, it is also a modern institution with a personal atmosphere.","1","2023-06-23 00:00:00","2023-07-26 20:16:11","" -"209","University of Maryland","","umd","logo/umd.png","https://www.umd.edu/","The University of Maryland, College Park is the state's flagship university and one of the nation's preeminent public research universities. A global leader in research, entrepreneurship and innovation, the university is home to more than 40,700 students, 14,000 faculty and staff, and nearly 400,000 alumni all dedicated to the pursuit of Fearless Ideas. Located just outside Washington, D.C., we discover and share new knowledge every day through our renowned research enterprise and programs in academics, the arts and athletics. And we are committed to social entrepreneurship as the nation's first “Do Good” campus.","5","2023-06-23 00:00:00","2023-07-26 20:16:12","UMD" -"210","University of Michigan","","umich","logo/block-m-maize.png","https://umich.edu/","Welcome to the University of Michigan, a place with deep traditions focused on creating brighter futures. We invite you to explore the diverse and vibrant community that makes us the home of Leaders & Best. More than any other university, we have the potential to be so much more than the sum of our many excellent parts. It's this potential to have a positive impact on the society we serve that represents our greatest value as a university.","1","2023-06-23 00:00:00","2023-07-26 20:16:14","" -"211","University of North Carolina at Chapel Hill","","unc","logo/univ-unc.png","https://www.unc.edu/","The nation's first public university is at the heart of what's next, preparing a diverse student body to become creators, explorers, innovators and leaders in North Carolina and throughout the world. Carolina's nationally recognized, innovative teaching, campus-wide spirit of inquiry and dedication to public service continue the legacy that began in 1795 when the University first opened its doors to students. In Chapel Hill, students develop a voice for critical thought and the courage to guide change. They connect to the future they're already shaping. Carolina is committed to access for all, providing life-changing opportunities such as the Carolina Covenant, which promises a debt-free education to low-income students. In its third century - an era of groundbreaking study and research -UNC-Chapel Hill is harnessing the very best of our fast-changing world. We're proud to advance knowledge for this and each generation to come.","4","2023-06-23 00:00:00","2023-10-16 21:37:47","UNC" -"213","University of Padova","","university-of-padova","logo/university-of-padua.jpg","https://www.unipd.it/en/","The University of Padua is one of Europe's oldest and most prestigious seats of learning. As a multi-disciplinary institute of higher education, the University aims to provide its students with professional training and a solid cultural background. The qualification received from the University of Padua act as a symbol of the ambitious objectives respected and coveted by both students and employers alike. Founded in 1222, Padua's Studium Patavinum was a place of study that readily welcomed Italian students and scholars, as well as those from various European countries searching for cultural freedom and expression. This freedom continues to define and express the essence of the University through its motto as Universa universis patavina libertas.","5","2023-06-23 00:00:00","2023-07-26 20:16:16","" -"214","University of Padua","","university-of-padua","logo/university-of-padua.jpg","https://www.unipd.it/en/","The University of Padua is one of Europe's oldest and most prestigious seats of learning. As a multi-disciplinary institute of higher education, the University aims to provide its students with professional training and a solid cultural background. The qualification received from the University of Padua act as a symbol of the ambitious objectives respected and coveted by both students and employers alike. Founded in 1222, Padua's Studium Patavinum was a place of study that readily welcomed Italian students and scholars, as well as those from various European countries searching for cultural freedom and expression. This freedom continues to define and express the essence of the University through its motto as Universa universis patavina libertas.","1","2023-06-23 00:00:00","2023-07-26 20:16:17","" -"215","University of Pennsylvania","","upenn","logo/upenn.png","https://www.upenn.edu/","Penn's academics are boosted by its inherent culture and ecosystem of innovation. You name it, if it's cutting-edge, the University's faculty—and students—have their hands in it. Grounded in the liberal arts and sciences and enriched by the integrated resources of four undergraduate and 12 graduate schools, Penn offers students an unparalleled education informed by inclusivity, intellectual rigor, research, and the impetus to create new knowledge to the benefit of individuals and communities around the world.","6","2023-06-23 00:00:00","2023-07-26 20:16:17","" -"216","University of Rochester","","rochester","logo/rochester.jpeg","https://www.rochester.edu/","One of the world's leading research universities, Rochester has a long tradition of breaking boundaries—always pushing and questioning, learning and unlearning. We transform ideas into enterprises that create value and make the world ever better.","2","2023-06-23 00:00:00","2023-07-26 20:16:18","" -"217","University of South Florida","","usf","logo/usf.png","https://www.usf.edu/","Welcome to the University of South Florida. Though a relatively young university, founded in 1956, we have rich traditions - traditions of access and opportunity for students, of academic excellence, of groundbreaking research, of serving our communities.","1","2023-06-23 00:00:00","2023-10-16 21:43:44","USF" -"218","University of Southampton","","university-of-southampton","logo/university-of-southampton.png","https://www.southampton.ac.uk/","As a global top 100 university, our expert academics and wide range of study options will help you achieve your goals.","1","2023-06-23 00:00:00","2023-07-26 20:16:21","" -"219","University of Texas Southwestern Medical Center","","ut-southwestern","logo/ut-swestern.gif","https://www.utsouthwestern.edu/","UT Southwestern, one of the premier academic medical centers in the nation, integrates pioneering biomedical research with exceptional clinical care and education. The institution's faculty includes many distinguished members, including six who have been awarded Nobel Prizes since 1985. The faculty of more than 2,800 is responsible for groundbreaking medical advances and is committed to translating science-driven research quickly to new clinical treatments. UT Southwestern physicians provide medical care in about 80 specialties to more than 105,000 hospitalized patients, nearly 370,000 emergency room cases, and oversee approximately 3 million outpatient visits a year.","2","2023-06-23 00:00:00","2023-07-26 20:16:21","" -"220","University of Toronto","","u-of-t","logo/utoronto.png","https://www.utoronto.ca/","We are proud to be one of the world's top research-intensive universities, bringing together top minds from every conceivable background and discipline to collaborate on the world's most pressing challenges. Our community is a catalyst for discovery, innovation and progress, creating knowledge and solutions that make a tangible difference around the globe. And we prepare our students for success through an outstanding global education rooted in excellence, inclusion and close-knit learning communities. The ideas, innovations and contributions of more than 660,000 graduates advance U of T's impact on communities across the globe. Together, we continue to defy gravity by taking on what might seem unattainable today and generating the ideas and talent needed to build a more equitable, sustainable and prosperous future.","10","2023-06-23 00:00:00","2023-07-26 20:16:21","U of T" -"221","University of Vermont","","uvm","logo/the-university-of-vermont.png","https://www.uvm.edu/","UVM is a top research university of ideal size, large enough to offer a breadth of ideas, resources, and opportunities, yet scaled to enable close faculty-student mentorship across all levels of study, from bachelor's to doctoral programs.","1","2023-06-23 00:00:00","2023-07-26 20:16:22","UVM" -"222","University of Verona","relazioni.internazionali@ateneo.univr.it","university-of-verona","logo/university-of-verona.png","https://www.univr.it/en/international","The University of Verona strives for excellence in teaching, research and innovation. It has 22,000 students and 1,500 staff including lecturers, researchers, technical and administrative personnel who work to continually improve and grow the university. A forward-thinking institution which continuously seeks to strengthen the link between its degree courses and the real world of work, the university's main objective for the near future is to become progressively more welcoming and adapted to student needs.","1","2023-06-23 00:00:00","2023-10-27 20:11:57","" -"223","University of Virginia","","uva","logo/uva_primary_logo.jpg","https://www.virginia.edu/","The University is an iconic public institution of higher education, boasting nationally ranked schools and programs, diverse and distinguished faculty, a major academic medical center and proud history as a renowned research university. The community and culture of the University are enriched by active student self-governance, sustained commitment to the arts and a robust NCAA Division I Athletics program.","1","2023-06-23 00:00:00","2023-07-26 20:16:24","UVA" -"224","University of Washington","","uw","logo/uw.svg","https://www.washington.edu/","Since our founding in 1861, the University of Washington has been a hub for learning, innovation, problem solving and community building. Driven by a mission to serve the greater good, our students, faculty and staff tackle today's most pressing challenges with courage and creativity, making a difference across Washington state — and around the world.","8","2023-06-23 00:00:00","2023-07-26 20:16:25","UW" -"225","University of Wisconsin-Madison","","uw-madison","logo/uw-logo.png","https://www.wisc.edu/","Since its founding in 1848, this campus has been a catalyst for the extraordinary. As a public land-grant university and major research institution, our students, staff, and faculty engage in a world-class education while solving real-world problems. With public service — or as we call it, the Wisconsin Idea — as our guiding principle, Badgers are creating a better future for everyone.","1","2023-06-23 00:00:00","2023-07-26 20:16:26","" -"226","University of Zurich","","uzh","logo/uzh.png","https://www.uzh.ch/en.html","With its 28,000 enrolled students, the University of Zurich is Switzerland's largest university. Founded in the year 1833, UZH was Europe's first university to be established by a democratic political system. Made up of seven faculties covering some 100 different subject areas, the University offers a wide variety of Bachelor's, Master's and PhD programs.","4","2023-06-23 00:00:00","2023-07-26 20:16:26","UZH" -"227","Urban Green Energy","","uge","logo/ugei-logo.svg","https://www.ugei.com/","Since 2008 when our journey began, we've been focused on expanding utilization of renewable energy. In our early days, we worked on finding use cases for clean energy technologies before they were widely adopted, building projects ranging from wind and solar microgrids in remote locations, to lighting the Eiffel Tower with 100% renewable energy in 2014. Over time we turned our focus entirely to solar and battery storage in the U.S. where we're building a growing portfolio of distributed energy assets, Leaning on more than a decade of experience across 700 projects totaling more than 500 megawatts, we're proud to be making a significant impact on the world's transition to clean energy, and we're just getting started.","1","2023-06-23 00:00:00","2023-07-26 20:16:28","UGE" -"228","US Army Medical Research Institute of Infectious Diseases","","usamriid","logo/usarmy.png","https://usamriid.health.mil/","To provide leading edge medical capabilities to deter and defend against current and emerging biological threat agents.","1","2023-06-23 00:00:00","2023-11-21 01:01:14","USAMRIID" -"229","VA Durham Health Care","","va-durham-health-care","logo/va-logo-white.png","https://www.durham.va.gov/","Since 1953, Durham Veterans Affairs Medical Center has been improving the health of the men and women who have so proudly served our nation. We consider it our privilege to serve your healthcare needs in any way we can. Services are available to more than 200,000 Veterans living in a 27-county area of central and eastern North Carolina. The VA Durham Healthcare System provides you with outstanding health care, trains America's future health care providers, and conducts important medical research.","2","2023-06-23 00:00:00","2023-07-26 20:16:29","" -"230","Verily","info@verily.com","verily","logo/verily.jpeg","https://verily.com/","True, comprehensive health is expanding exponentially. Massive increases in health information & computing power are coinciding with health challenges of a scale & magnitude we've never seen—creating urgency for value-based care and improved outcomes for all. Precision health represents a fundamental shift to health and to care that is more individualized, accessible, and affordable.","1","2023-06-23 00:00:00","2023-07-26 20:16:29","" -"231","VHA Innovation Ecosystem","","vha-ie","logo/vaInnovation.jpeg","https://www.innovation.va.gov/ecosystem/views/home.html","VHA Innovation Ecosystem (VHA IE) is the catalyst for enabling the discovery and spread of mission-driven health care innovation that exceeds expectations, restores hope, and builds trust within the Veteran community. VHA IE leverages the collective power of innovation champions from across VA, academia, non-profit and industry to operationalize innovation in the Nation's largest integrated health care system.","3","2023-06-23 00:00:00","2023-07-26 20:16:31","VHA IE" -"232","Washington University in St. Louis","","wustl","logo/wustl.png","https://wustl.edu/","At WashU, we generate, disseminate, and apply knowledge. We foster freedom of inquiry and expression of ideas in our research, teaching and learning. We aim to create an environment that encourages and supports wide-ranging exploration at the frontier of discovery by embracing diverse perspectives from individuals of all identities and backgrounds. We promote higher education and rigorous research as a fundamental component of an open, vibrant society. We strive to enhance the lives and livelihoods not only of our students, patients, and employees but also of the people of the greater St. Louis community and beyond. We do so by addressing scientific, social, economic, medical, and other challenges in the local, national, and international realms.","1","2023-06-23 00:00:00","2023-10-14 06:11:40","WUStL" -"233","Wayne State University","","wayne-state-university","logo/wayne-state-university.png","https://wayne.edu/","Our mission is to create and advance knowledge, prepare a diverse student body to thrive, and positively impact local and global communities. Our guiding values cut across organizational boundaries, bind us culturally, and permeate our strategic and tactical initiatives. They are the defining traits of the WSU community.","1","2023-06-23 00:00:00","2023-10-14 06:11:38","" -"234","Weizmann Institute of Science","contact-us@weizmann.ac.il","weizmann-institute-of-science","logo/wiz.jpeg","https://www.weizmann.ac.il/pages/","The Weizmann Institute of Science is one of the world's leading multidisciplinary basic research institutions in the natural and exact sciences. It is located in Rehovot, Israel, just south of Tel Aviv. It was initially established as the Daniel Sieff Institute in 1934, by Israel and Rebecca Sieff of London in memory of their son Daniel. In 1949, it was renamed for Dr. Chaim Weizmann, the first President of the State of Israel and Founder of the Institute.","3","2023-06-23 00:00:00","2023-11-20 22:20:49","" -"235","Wellcome Sanger Institute","","sanger","logo/sanger.jpeg","https://www.sanger.ac.uk/","We tackle some of the most difficult challenges in genomic research. This demands science at scale; a visionary and creative approach to research that pushes the boundaries of our understanding in ever new and exciting ways.","2","2023-06-23 00:00:00","2023-10-14 06:11:36","" -"236","White House Office of Science and Technology Policy","","ostp","logo/ostp.png","https://www.whitehouse.gov/ostp/","President Biden often says, 'America is the only nation that can be defined by a single word: possibilities.' The White House Office of Science and Technology (OSTP) works to bring that idea to life by harnessing the power of science, technology, and innovation to achieve America's greatest aspirations. OSTP's mission includes-a) Providing advice to the President and the Executive Office of the President on matters related to science and technology; b) Strengthening and advancing American science and technology; c) Working with federal departments and agencies and with Congress to create bold visions, unified strategies, clear plans, wise policies, and effective, equitable programs for science and technology; d) Engaging with external partners, including industry, academia, philanthropic organizations, and civil society; state, local, Tribal and territorial governments; and other nations; and, e) Ensuring equity, inclusion, and integrity in all aspects of science and technology.","1","2023-06-23 00:00:00","2023-10-16 21:45:02","OSTP" -"237","InChI Trust","","inchi","logo/inchi.png","https://www.inchi-trust.org/","InChI: open-source chemical structure representation algorithm. InChI is a structure-based chemical identifier, originally developed by IUPAC. As a standard identifier for chemical databases, InChI is essential for enabling effective information management across chemistry. InChI with InChIKey are non-proprietary open standards. InChI turns chemical structures into unique machine readable strings, used for describing, storing and searching chemical structures. All associated algorithms and software are open source.","1","2023-06-23 00:00:00","2023-10-16 21:45:06","" -"238","National Center for Toxicological Research","","nctr","","https://www.fda.gov/about-fda/office-chief-scientist/national-center-toxicological-research","The National Center for Toxicological Research (NCTR), is the only FDA Center located outside the Washington D.C. metropolitan area. The one-million square foot research campus in Jefferson, Arkansas plays a critical role in the missions of FDA and the Department of Health and Human Services to promote and protect public health. Regulatory science researchers, academia, and other regulatory science research organizations and groups from around the world investigate, learn, and train at the Federal facility. NCTR, FDA's internationally recognized research center, plays a critical role in FDA's mission. The unique scientific expertise of NCTR is critical in supporting FDA product centers and their regulatory roles.","2","2023-06-23 00:00:00","2023-10-14 06:11:34","NCTR" -"239","McGill University","","mcgill","logo/mcgill.jpg","https://www.mcgill.ca/","McGill University is one of Canada's best-known institutions of higher learning and one of the leading universities in the world. International students from more than 150 countries make up nearly 30% of McGill's student body ‒ the highest proportion of any Canadian research university.","1","2023-06-23 00:00:00","2023-10-14 06:11:32","" -"240","Medical Artificial Intelligence Lab","spark@mailab.io","mai-lab","logo/mai-lab.jpg","https://mailab.io/","We are a leading ecosystem for data science and artificial intelligence (AI) innovations in medical diagnostic imaging. Our lab is dedicated to creating AI solutions and data science applications to transform the healthcare landscape of countries in Africa. We are a team of scientists from around the world working locally to disrupt healthcare challenges in resourced limited settings by implementing AI innovations in Africa where it has the most potential.","1","2023-06-23 00:00:00","2023-10-14 06:11:31","" -"241","Duke University Medical Center","","duke-health","logo/duke-health.jpg","https://www.dukehealth.org/locations/duke-university-medical-center","Duke University Medical Center is the name given to the group of patient care, education and medical research facilities on the medical campus of Duke University in Durham, North Carolina.","1","2023-06-23 00:00:00","2023-10-14 06:11:30","" -"242","Yale University","","yale","logo/yale.jpg","https://www.yale.edu/","Since its founding in 1701, Yale has been dedicated to expanding and sharing knowledge, inspiring innovation, and preserving cultural and scientific information for future generations. Yale’s reach is both local and international. It partners with its hometown of New Haven, Connecticut to strengthen the city’s community and economy. And it engages with people and institutions across the globe in the quest to promote cultural understanding, improve the human condition, delve more deeply into the secrets of the universe, and train the next generation of world leaders.","3","2023-06-23 00:00:00","2023-10-14 06:11:26","" -"243","Missouri University","","mizzou","logo/mizzou.jpg","https://missouri.edu/","Top 5 reasons to choose Mizzou: 1) U.S. News & World Report ranked Mizzou the #1 Best Value among Midwest flagships; 2) 95% of Mizzou graduates are successful within six months of graduation; 3) Mizzou offers all undergraduate students real-life experiences and hands-on learning in their field; 4) Mizzou’s graduation rate is 75%; 5) Columbia, Missouri, is consistently ranked one of the best college towns in the country","1","2023-06-23 00:00:00","2023-11-21 01:00:27","" -"244","Yale School of Medicine","","ysm","logo/ysm.png","https://medicine.yale.edu/","Yale School of Medicine educates and nurtures creative leaders in medicine and science, promoting curiosity and critical inquiry in an inclusive environment enriched by diversity. We advance discovery and innovation fostered by partnerships across the university, our local community, and the world. We care for patients with compassion, and commit to improving the health of all people.","1","2023-06-23 00:00:00","2023-11-21 00:59:51","YSM" -"245","Children's National Hospital","","childrens-national","logo/childrens-national.jpg","https://childrensnational.org/","Children's National Hospital is ranked #5 in the nation by U.S. News & World Report. We're ranked #1 for newborns and we're the best pediatric hospital for neurology and neurosurgery in the Mid-Atlantic. What's more, we ranked in all 10 specialties, with top 10 honors in neurology and neurosurgery, cancer, nephrology, orthopedics, pulmonology and lung surgery, and diabetes and endocrinology. This recognition of our commitment to bringing health and well-being to all children continues to inspire our teams.","1","2023-06-23 00:00:00","2023-07-26 20:16:42","" -"246","Helmholtz AI","","helmholtz-ai","logo/helmholtz-ai.jpg","https://www.helmholtz.ai/","We are a research-driven hub for applied artificial intelligence (AI) that: a) fosters cross-field creativity by stimulating collaborative research projects; b) identifies and leverages similarities between applications to advance generalised AI / machine learning (ML) methods; c) integrates field-specific excellence and AI/ML prowess; d) improves the quality, scalability and timely availability of emerging methods and tools; and e) empowers and trains the current and next generation of scientists, to enable the efficient and agile development and implementation of AI/ML assets across the whole Helmholtz Association.","1","2023-06-23 00:00:00","2023-11-21 01:03:10","" -"247","Mayo Clinic","","mayo-clinic","logo/mayo-clinic.png","https://www.mayoclinic.org/","Mayo Clinic is a nonprofit organization committed to clinical practice, education and research, providing expert, whole-person care to everyone who needs healing.","6","2023-06-23 00:00:00","2023-07-26 20:16:43","" -"248","Technical University of Munich","","tum","logo/tum.jpg","https://www.tum.de/en/","TUM has once again been named a University of Excellence and is thus the only technical university to continuously retain this status since 2006. The title is awarded as a part of the Excellence Strategy of the German federal and state governments, in strategic international support of German cutting-edge research. We are using this funding to realize the future concept TUM Agenda 2030. We are expanding technically-oriented humanities and social sciences and are reorganizing previous internal structures to be more innovation-oriented: The constraining, discipline-based Faculty structure is being replaced by seven Schools which are linked to one another by integrative research institutes. In the sense of an ""open marketplace of knowledge"", we support talented individuals in all their diversity, at all levels and across substantive subject boundaries. We work in alliances with international partners to re-orient towards Europe as well as to the southern global hemisphere in order t...","2","2023-06-23 00:00:00","2023-10-16 21:46:32","TUM" -"249","Center for Devices and Radiological Health","","cdrh","logo/fda.svg","https://www.fda.gov/about-fda/fda-organization/center-devices-and-radiological-health","In keeping with our mission, the Center for Devices and Radiological Health (CDRH) is responsible for protecting and promoting the public health. We assure that patients and providers have timely and continued access to safe, effective, and high-quality medical devices and safe radiation-emitting products. We provide consumers, patients, their caregivers, and providers with understandable and accessible science-based information about the products we oversee. We facilitate medical device innovation by advancing regulatory science, providing industry with predictable, consistent, transparent, and efficient regulatory pathways, and assuring consumer confidence in devices marketed in the U.S. We seek to continually improve our effectiveness in fulfilling our mission by planning strategically and regularly monitoring our progress.","2","2023-06-23 00:00:00","2023-08-10 21:36:27","CDRH" -"250","Lagos State University Teaching Hospital","","lasuth","logo/lasuth.jpg","https://www.lasuth.org.ng/","To provide high quality Healthcare Services in a friendly Environment where patients' satisfaction is the ultimate. Guided by the needs of our patients and their families, we aim to deliver the very best health care in a safe and compassionate environment; to advance care through innovative research and education; and to improve the health and well-being of the diverse communities we serve.","1","2023-06-23 00:00:00","2023-07-26 20:16:45","LASUTH" -"251","NSIA-Kano Diagnostic Center","enquiries@nkdc.ng","nkdc","logo/nkdc.jpeg","https://www.nhdic.ng/facility/nkdc/","The NKDC medical diagnostics facility opened its doors to the public on the 16th of March, 2020, in Kano - Northern Nigeria’s commercial centre. This state-of-the-art facility is home to a group of enthusiastic, passionate and patient-centric medical professionals who continuously aim to improve patient experiences. We offer 24/7 radiology and medical laboratory services all year round.","1","2023-06-23 00:00:00","2023-10-16 21:47:10","NKDC" -"252","Nationwide Children's Hospital","","nationwide-childrens","logo/nationwide-childrens.jpg","https://www.nationwidechildrens.org/","At Nationwide Children’s Hospital, our vision remains unchanged. We aspire to create the best outcomes for children everywhere. This means families come to Nationwide Children’s from around the globe knowing they will get the highest quality care. It means we will reach to cure rare diseases. It means we will sequence a child’s tumor to select the best care pathway. It means we will strive to make an entire population healthier, not just through their physical health, but also in their mental health. It means we will redefine the role of the children’s hospital in the achievement of optimal health.","1","2023-06-23 00:00:00","2023-07-26 20:16:46","" -"253","Dana-Farber Brigham Cancer Center","","dana-farber-brigham-cancer-center","logo/bwh.png","https://www.brighamandwomens.org/cancer","At Dana-Farber Brigham Cancer Center, all we do is cancer. Because no two people are the same, our approach to treatment and care is personalized - with a deep understanding of your cancer and how to get you well. Through our 12 specialized disease treatment centers, experts from our two organizations, Dana-Farber Cancer Institute and Brigham and Women’s Hospital, work together as one team to offer the most advanced treatments with compassion and care that makes all the difference.","1","2023-06-23 00:00:00","2023-10-16 21:47:47","" -"254","Lacunda Fund","secretariat@lacunafund.org","lacunda-fund","logo/lacuna-fund.jpg","https://lacunafund.org/","Lacuna Fund is the world’s first collaborative effort to provide data scientists, researchers, and social entrepreneurs in low- and middle-income contexts globally with the resources they need to produce labeled datasets that address urgent problems in their communities.","1","2023-06-23 00:00:00","2023-10-16 21:55:03","" -"255","MLCommons","","mlcommons","logo/mlc.jpg","https://mlcommons.org/en/","The mission of MLCommons(R) is to accelerate machine learning innovation and increase its positive impact on society. Together with its 50+ founding Members and Affiliates, including startups, leading companies, academics, and non-profits from around the globe, MLCommons will help grow machine learning from a research field into a mature industry through benchmarks, public datasets and best practices. Every major technological advance follows a similar trajectory towards universal adoption and impact. The arc from research to broad accessibility generally takes from 30-40 years: from early automobiles to the family car, from development of ARPANET to the mainstream World Wide Web, from the first cellular phones to an smartphone in every pocket. Each of these examples started with technological breakthroughs, but for decades was limited by expertise, access, and expense. Machine learning is no different. ML and artificial intelligence have been around for decades, but even today ...","1","2023-06-23 00:00:00","2023-10-16 21:55:21","" -"256","Harvard Medical School","","hms","logo/hms.jpg","https://hms.harvard.edu/","Since the School was established in 1782, faculty members have improved human health by innovating in their roles as physicians, mentors and scholars. They’ve piloted educational models, developed new curricula to address emerging needs in health care, and produced thousands of leaders and compassionate caregivers who are shaping the fields of science and medicine throughout the world with their expertise and passion.","8","2023-08-04 06:00:47","2023-08-04 23:38:09","HMS" -"257","Centre for Structural Systems Biology","info@cssb-hamburg.de","cssb","logo/cssb.jpeg","https://www.cssb-hamburg.de/","CSSB is a joint initiative of nine research partners from Northern Germany, including three universities and six research institutes that devotes itself to infection biology research.","1","2023-08-04 22:00:31","2023-10-16 20:44:20","CSSB" -"258","University Medical Center Groningen","","umcg","logo/umcg.jpg","https://www.umcg.nl/","The University Medical Center Groningen (UMCG) is one of the largest hospitals in the Netherlands and is the largest employer in the Northern Netherlands. The more than 12,000 employees work together on care, research, training and education with the common goal: building the future of health.","1","2023-08-04 22:07:45","2023-10-16 21:55:55","UMCG" -"259","Eindhoven University of Technology","","tue","logo/tue.jpeg","https://www.tue.nl/en/","We educate students and advance knowledge in science & technology for the benefit of humanity. We integrate education and research to enable our students and scientists to become thought leaders and to design and achieve the unimaginable. In close collaboration with our public and private partners, we translate our basic research into meaningful solutions.","2","2023-08-04 22:12:40","2023-10-16 20:47:30","TU/e" -"260","Wageningen University & Research","","wur","logo/wur.jpeg","https://www.wur.nl/en.htm","Wageningen University & Research is a collaboration between Wageningen University and the Wageningen Research foundation. ""To explore the potential of nature to improve the quality of life"". That is the mission of Wageningen University & Research. Over 7,600 employees, 13,100 students and over 150.000 participants to WUR’s Life Long Learning from more than hundred countries work everywhere around the world in the domain of healthy food and living environment for governments and the business community-at-large. The strength of Wageningen University & Research lies in its ability to join the forces of specialised research institutes and the university. It also lies in the combined efforts of the various fields of natural and social sciences. This union of expertise leads to scientific breakthroughs that can quickly be put into practice and be incorporated into education. This is the Wageningen Approach. Collaboration with other parties such as government, business and NGOs is indi...","1","2023-08-04 22:15:19","2023-11-21 00:58:32","WUR" -"261","University Medical Center Utrecht","researchoffice@umcutrecht.nl","umc-utrecht","logo/umc-utrecht.jpeg","https://www.umcutrecht.nl/en/research","In the UMC Utrecht research is concentrated in six strategic programs with each a limited number of disease targets. Patient care is integrated in these programs. A relentless multidisciplinary approach guarantees patients benefit from the latest available expertise and innovative technological solutions.","6","2023-08-04 22:16:49","2023-10-16 20:48:54","" -"262","Amsterdam University Medical Centers","","amsterdam-umc","logo/amsterdam-umc.jpeg","https://www.amsterdamumc.org/en.htm","Amsterdam UMC is a leading medical center that combines complex high-quality patient care, innovative scientific research, and education of the next generation health care professionals. We believe that health care practice, research and education belong together, with each shaping and informing the other.","1","2023-08-04 22:19:22","2023-10-16 20:55:48","" -"263","Maastricht University","","um","logo/um.jpg","https://www.maastrichtuniversity.nl/","Maastricht University (UM) is the most international university in the Netherlands and, with nearly 22,000 students and 4,400 employees, is still growing. The university distinguishes itself with its innovative education model, international character and multidisciplinary approach to research and education.","1","2023-08-04 22:24:47","2023-11-20 21:09:18","UM" -"264","Delft University of Technology","","tu-delft","logo/tu-delft.jpg","https://www.tudelft.nl/en/","Top education and research are at the heart of the oldest and largest technical university in the Netherlands. Our 8 faculties offer 16 bachelor's and more than 30 master's programmes. Our more than 25,000 students and 6,000 employees share a fascination for science, design and technology. Our common mission: impact for a better society.","1","2023-08-04 23:14:17","2023-11-20 21:09:23","" -"265","Alliance of TU/e, WUR, UU and UMC Utrecht","info@ewuu.nl","ewuu","logo/ewuu.jpg","https://ewuu.nl/en/","In 2019 Eindhoven University of Technology, Wageningen University & Research, Utrecht University and University Medical Centre Utrecht decided to form an alliance and to work together. The motto of this strategic collaboration is challenging future generations. Young researchers, lecturers and students are at the helm and work together right across disciplines. The challenges future generations will face are large but so are the possibilities for meeting those challenges. The institutions combine their expertise in order to contribute to social transitions in energy, sustainability, health and food.","1","2023-08-04 23:17:20","2023-11-20 21:09:39","EWUU" -"266","Utrecht University","","uu","logo/uu.jpeg","https://www.uu.nl/en","We are Utrecht University. The place for new collaborations and cross-pollination. Students, academic and administrative staff, policymakers, members of the public, professionals and business owners; you are invited to contribute to a better world.","1","2023-08-04 23:19:33","2023-11-20 21:09:43","UU" -"267","Surgical Science","","surgical-science","logo/surgical-science.png","https://surgicalscience.com/","Training without putting patients at risk. This is why we exist - to give surgeons an excellent platform to train in the fundamental technical skills before entering the operation room. For over 20 years, we have been committed to providing state-of-the-art medical training simulators that focus on ease of use and validation. The simple idea is to learn the practical techniques of instrument handling in a realistic but safe environment so that you can pay full attention to the patient when you begin the operation.","1","2023-08-04 23:51:56","2023-11-20 21:09:49","" -"268","Wellcome/EPSRC Centre for Interventional and Surgical Sciences","","weiss","logo/weiss.jpg","https://www.ucl.ac.uk/interventional-surgical-sciences","At the Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), engineers, clinicians and scientists work together to develop technologies that enable safer and more effective treatments for patients across a wide range of conditions. The Centre is based at Charles Bell House, a building that brings together researchers from a wide range of departments at UCL, including Medical Physics and Biomedical Engineering, Computer Science and Mechanical Engineering. These academic researchers work in partnership with clinical researchers from areas such as the UCL Division of Surgery & Interventional Sciences and leading hospitals. At WEISS, research is being developed with a wide range of clinical applications in mind, including cardiovascular, paediatric, ophthalmic, neurological and urological surgical interventions. In particular, the Centre aims to advance engineering sciences in intraoperative imaging and sensing, data fusion and extraction, human-technology interfa...","1","2023-08-05 00:00:44","2023-11-20 21:09:54","WEISS" -"269","Medtronic","","medtronic","logo/medtronic.png","https://www.medtronic.com/us-en/index.html","Health tech for a better future. From AI to connected care and beyond, our technology is building a bridge to better health for more people.","1","2023-08-05 00:02:47","2023-11-20 21:09:56","" -"270","King's College Hopistal","","kch","logo/kch.jpg","https://www.kch.nhs.uk/","We are one of London’s largest and busiest teaching hospitals. We provide a strong profile of local hospital services for people living in the boroughs of Lambeth, Southwark, Lewisham, and Bromley. Our specialist services are also available to patients from a wider area. We providing nationally and internationally recognised treatment and care in liver disease and transplantation, neurosciences, haemato-oncology, and fetal medicine. Our vision is to be bold, and our new Trust values - Kind, Respectful Team - help ensure we bring a positive attitude to the way we interact with patients, relatives, and the many people who use our services.","2","2023-08-05 00:08:37","2023-11-20 21:44:33","KCH" -"271","Western University","","western","logo/western.jpg","https://www.uwo.ca/index.html","We are a leading research-intensive university and global community of individuals focused on making change in the world, today.","1","2023-08-05 00:10:52","2023-11-21 00:57:43","" -"272","Robarts Research Institute","","robarts","logo/robarts.jpg","https://www.robarts.ca/","Opened in 1986, Robarts Research Institute at Western University is a medical research facility in London, Ontario, with more than 600 people working to investigate some of the most debilitating diseases of our time, from heart disease and stroke to diabetes, Alzheimer’s and many forms of cancer. We believe we’ve got a winning formula to accelerate medical discovery: attract the brightest and best people, give them the freedom to think big and set the bar high. From our roots under the scientific leadership of renowned neurologist Dr. Henry Barnett - whose work with Aspirin as a preventive therapy for heart attack and stroke remains one of the most important developments in 20th century medicine - the Institute has applied that formula to become a national leader in biological, clinical and imaging research.","1","2023-08-05 00:12:27","2023-11-20 21:44:48","" -"273","British Acoustic Neuroma Association","","bana-uk","logo/bana-uk.jpeg","https://www.bana-uk.com/","BANA was formed in 1992 by a group of patients and their partners. They were introduced to each other by ENT and Neurosurgeon Consultants from the Queen’s Medical Centre Hospital in Nottingham and from the very beginning, mutual support was their primary aim. They also wanted to provide reliable information to those diagnosed and to promote research into Acoustic Neuromas and the effects associated with them. More than two decades on, these fledgling intentions remain the charitable objectives that drive the charity forward on behalf of all those affected.","1","2023-08-05 00:15:03","2023-11-21 01:19:09","BANA" -"274","Ninewells Hospital","","ninewells-hospital","logo/nhs-tayside.png","https://www.nhstayside.scot.nhs.uk/GoingToHospital/OurPremisesA-Z/NinewellsHospital/index.htm","","1","2023-08-05 00:20:05","2023-11-20 21:45:07","" -"275","Universal Protein Resource","","uniprot","logo/uniprot.jpg","https://www.uniprot.org/","The Universal Protein Resource (UniProt) is a comprehensive resource for protein sequence and annotation data. The UniProt databases are the UniProt Knowledgebase (UniProtKB), the UniProt Reference Clusters (UniRef), and the UniProt Archive (UniParc). The UniProt consortium and host institutions EMBL-EBI, SIB and PIR are committed to the long-term preservation of the UniProt databases.","1","2023-08-05 05:21:46","2023-11-20 21:45:11","" -"276","Charing Cross Hospital","","charing-cross-hospital","logo/imperial-nhs.jpg","https://www.imperial.nhs.uk/our-locations/charing-cross-hospital","Charing Cross Hospital provides a range of acute and specialist services, a 24/7 accident and emergency department and hosts the hyper acute stroke unit for the region. It is also a growing hub for integrated care in partnership with local GPs and community providers.","1","2023-08-05 05:27:03","2023-11-20 21:45:20","" -"277","Elisabeth-TweeSteden Hospital","","etz","logo/etz.jpg","https://www.etz.nl/","The ETZ (Elisabeth-TweeSteden Hospital) is a top clinical teaching hospital and trauma center. With three locations in Tilburg and Waalwijk, ETZ is the hospital for all residents of the Central Brabant region, but also (far) beyond.","1","2023-08-05 05:28:21","2023-11-20 21:45:23","ETZ" -"278","InVitro Cell Research","","icr","logo/icr.png","https://invitrocellresearch.com/","Founded in 2015, InVitro Cell Research, LLC (ICR) is a privately funded company focused on regenerative and preventive personalized medicine. We are dedicated to discovering and developing interventions to slow and reverse biological aging and prevent major age-related diseases. While our offices and labs in the greater New York City area offer over 15,000 square feet of state-of-the-art research space, our scientists set us apart and make us special. They help guide and define our mission. What is our mission? Researching how to repair aging people, fast.","1","2023-08-05 05:33:19","2023-11-20 21:45:29","ICR" -"279","Accelerating Medicines Partnership(R) Parkinson's Disease","","amp-pd","logo/amp-pd.png","https://www.amp-pd.org/","The Accelerating Medicines Partnership(R) (AMP(R)) program is a public-private partnership between the National Institutes of Health (NIH), multiple biopharmaceutical and life sciences companies, and non-profit organizations. Managed through the Foundation for the NIH (FNIH), AMP aims to identify and validate the most promising biological targets for therapeutics. Disease areas covered by AMP at the launch of this site include Alzheimer’s disease, type 2 diabetes, the autoimmune disorders of rheumatoid arthritis and systemic lupus erythematosus (lupus) and Parkinson’s disease. Additional disease areas are being evaluated for addition to AMP.","1","2023-08-05 05:39:55","2023-11-20 21:45:38","AMP-PD" -"280","Vanderbilt University","","vanderbilt","logo/vanderbilt.jpg","https://www.vanderbilt.edu/","From its founding in 1873 as an institution devoted to “strengthening the ties which should exist between all sections of our common country,” Vanderbilt University has forged a tradition of academic excellence infused with a unique spirit of collaboration and collegiality. Our mission lies in the quest to bring out the best in humanity—pushing new ideas into the frontiers of discovery, challenging the limits of what’s possible and working diligently in the service of others. Vanderbilt’s closely connected park-like campus, set in the heart of the rapidly growing city of Nashville, Tennessee, is representative of the enduring bonds that unite us as One Vanderbilt community.","1","2023-08-07 20:28:32","2023-11-20 21:45:45","" -"281","Basque Center On Cognition, Brain and Language","","bcbl","logo/bcbl.jpg","https://www.bcbl.eu/en","Our research aims to unravel the neurocognitive mechanisms involved in the acquisition, comprehension and production of language, with special emphasis on bilingualism and multilingualism. We study processes involved in normal child language acquisition and second language learning in adults, as well as learning disorders, language disorders, language-related effects of aging and neurodegeneration and language use in different social contexts.","1","2023-08-07 20:29:41","2023-11-20 21:45:52","BCBL" -"282","Erasmus Medical Center","","emc","logo/emc.jpeg","https://www.erasmusmc.nl/en/","We are Erasmus MC. Every day our staff, volunteers, and students work with dedication and commitment and are passionate about everything that we stand for.","3","2023-08-07 20:31:10","2023-11-20 21:45:58","EMC" -"283","Indiana University","","iu","logo/iu.jpg","https://www.iu.edu/index.html","IU is home to top-ranked business and music schools. We’re home to the world’s first school of philanthropy, the nation’s first school of informatics, and the country’s largest medical school. Our hundreds of academic programs are among the world’s best, and we’re always looking toward the horizon, thinking about what’s next. To better prepare our students for the careers of tomorrow, we’ve launched or reconfigured 10 schools in the last decade, and we’re constantly adding new academic programs, like IU Bloomington’s Intelligent Systems Engineering program and IU Online’s 100% virtual Master of Science in Educational Technology for Learning.","2","2023-08-08 17:26:11","2023-11-20 21:46:01","IU" -"284","Science for Life Laboratory","","scilifelab","logo/scilifelab.jpg","https://www.scilifelab.se/","SciLifeLab, Science for Life Laboratory, is an institution for the advancement of molecular biosciences in Sweden. We are funded as a national research infrastructure by the Swedish government. Our organization leverages the unique strengths of individual researchers across Sweden into a focused resource for the life science community. We provide access for thousands of researchers to the cutting-edge instrumentation and deep scientific expertise necessary to be internationally competitive in bioscience research. This infrastructure is supported and developed by our research community, including internationally recognized experts in life science and technology. Our units and expertise create a unique environment for carrying out health and environmental research at the highest level. SciLifeLab started out in 2010 as a joint effort between four universities: Karolinska Institutet, KTH Royal Institute of Technology, Stockholm University and Uppsala University. Today, we support re...","1","2023-08-08 17:26:35","2023-11-20 22:13:23","" -"285","Uppsala University","","uppsala","logo/uppsala.jpg","https://www.uu.se/en","Uppsala University was founded in 1477. Today it is a strong, comprehensive research university ranked among the best in the world, with 50,000 students and close to 5,000 researchers.","1","2023-08-08 17:28:30","2023-11-21 01:19:20","UU" -"286","Google LLC","","google","logo/google.jpg","https://about.google/","Our mission is to organize the world’s information and make it universally accessible and useful.","3","2023-08-08 17:29:33","2023-11-20 22:25:44","" -"287","Precision Value & Health","","precision-value-&-health","logo/precision-value-health.jpeg","https://www.precisionvaluehealth.com/","Across the commercialization continuum, Precision Value & Health teams are focused on transforming data for health and leveraging evidence and insights to tailor communications for every stakeholder. From payers to health systems, scientists to healthcare providers, and consumers to advocates, our results are designed to shift the trajectory and accelerate your success. Precision Value & Health’s teams include PRECISIONadvisors (global pricing and market access strategy), PRECISIONeffect (branding and launch experts), PRECISIONheor (evidence generation and strategy), PRECISIONscientia (medical communications), PRECISIONvalue (managed markets marketing), and PRECISIONxtract (data-driven solutions and engagement).","1","2023-08-08 17:37:16","2023-11-20 22:25:52","" -"288","STLogics","","stlogics","logo/stlogics.jpg","https://www.stlogics.com/index.html","The STLogics Team has over 60 years of combined business experience to share. This broad business savvy enables our team to provide mentorship to those seeking to enhance the velocity of their trajectory to success. We can assist from small start-up initiatives to large corporations with our keen management skills and futuristic thinking capabilities. If your organization desires growth optimization or is entertaining the thought of acquisition consultation or a merger, STLogics can propel your revolutionary vision to reality. STLogics Holding Company provides operational and strategic advice to our affiliates in an effort to enhance their effectiveness and growth. We simply support and nurture our family of companies to enable them to maximize service to their clients. Our goal is to expand and diversify over various verticals, thus allowing us to foster innovation and create optimal results for client needs.","1","2023-08-08 17:41:14","2023-11-20 22:25:56","" -"289","Conference Ventures","","conference-ventures","","http://conferenceventures.com/","This organization may no longer exist, has rebranded, or has been merged under another organization.","1","2023-08-08 17:44:00","2023-11-20 22:26:05","" -"290","Google Brain","","google-brain","logo/google-ai.jpg","https://research.google/teams/brain/","This organization may no longer exist, has rebranded, or has been merged under another organization.","1","2023-08-08 17:56:04","2023-11-20 22:26:10","" -"291","Princeton University","","princeton","logo/princeton.jpg","https://www.princeton.edu/","Princeton is about people. Our University is enriched by the wide range of experiences and perspectives of our students, faculty, staff and alumni.","1","2023-08-08 18:02:09","2023-11-20 22:26:14","" -"292","Prairie View A&M University","","pvamu","logo/pvamu.jpg","https://www.pvamu.edu/","Welcome to Prairie View A&M University, home of the Panthers. Our HBCU, affectionately known as “The Hill,” is deeply rooted in culture & tradition and provides an undeniable educational experience to more than 9,000 diverse students on one of the most beautiful campuses in the state of Texas. Our award-winning faculty work diligently to create challenging and rewarding experiences that inspire you to dream big and soar to new heights. Are YOU ready to EXPERIENCE PVAMU?","1","2023-08-08 18:17:53","2023-11-20 22:26:19","PVAMU" -"293","University of California, Berkeley","","berkeley","logo/berkeley.png","https://www.berkeley.edu/","From a group of academic pioneers in 1868 to the Free Speech Movement in 1964, Berkeley is a place where the brightest minds from across the globe come together to explore, ask questions and improve the world.","4","2023-08-08 18:48:17","2023-11-20 22:26:32","" -"294","Center for Genetically Engineered Materials","","c-gem","logo/c-gem.jpg","https://gem-net.net/","C-GEM is establishing a fundamentally new way to program chemical matter and transform the way scientists design and produce materials and medicines. Using computation and experiment, C-GEM is repurposing nature’s protein synthesizing machine–the ribosome and its associated translation factors–to biosynthesize genetically encoded, sequence-defined chemical polymers with unprecedented functions and activities. Our combined activities span the fields of chemical biology, synthetic biology, synthetic chemistry, structural biology, computational biology, and molecular biology, and are highly collaborative. To catalyze these efforts, C-GEM implemented GEM-NET, a sophisticated data management system to promote data sharing within and outside the team, and with industry, the NSF, and the public. By fostering innovation at the chemical-biology-materials frontier, C-GEM is establishing a diverse chemical workforce, perfecting the integration of research with training, and captivating scien...","1","2023-08-08 19:14:43","2023-11-20 22:26:35","C-GEM" -"295","Oregon State University","","oregon-state","logo/oregon-state.jpg","https://oregonstate.edu/","Oregon State University is a dynamic community of dreamers, doers, problem-solvers and change-makers. We don’t wait for challenges to present themselves — we seek them out and take them on. We welcome students, faculty and staff from every background and perspective into a community where everyone feels seen and heard. We have deep-rooted mindfulness for the natural world and all who depend on it, and together, we apply knowledge, tools and skills to build a better future for all.","1","2023-08-08 19:23:28","2023-11-21 01:19:26","OSU" -"296","Laboratory for Innovation Science at Harvard","","lish","logo/lish.jpg","https://lish.harvard.edu/","The Laboratory for Innovation Science at Harvard (LISH) is spurring the development of a science of innovation through a systematic program of solving real-world innovation challenges while simultaneously conducting rigorous scientific research and analysis. LISH is a Harvard-wide research program led by faculty co-directors Karim Lakhani, Harvard Business School; Eva Guinan, Harvard Medical School; David Parkes, Harvard School of Engineering and Applied Sciences; and Kyle Myers, Harvard Business School; with support from the Institute for Quantitative Social Science. With our partners in both academia and industry, LISH conducts research on innovation within three areas of application: Crowdsourcing & Open Innovation; Data Science & AI Development; and Science of Science; addressing questions under three main research tracks-Incentives & Governance; Creativity & Problem-Solving; and Organization & Processes.","1","2023-08-08 19:24:59","2023-11-20 22:26:44","LISH" -"297","NIH Common Funds Library of Integrated Network-Based Cellular Signatures","","lincs","logo/lincs-program.jpg","https://lincsproject.org/LINCS/","The LINCS project is based on the premise that disrupting any one of the many steps of a given biological process will cause related changes in the molecular and cellular characteristics, behavior, and/or function of the cell - the observable composite of which is known as the cellular phenotype. Observing how and when a cell’s phenotype is altered by specific stressors can provide clues about the underlying mechanisms involved in perturbation and, ultimately, disease.","1","2023-08-08 19:25:32","2023-11-20 22:26:48","LINCS" -"298","Recursion Pharmaceuticals","","recursion","logo/recursion.jpg","https://www.recursion.com/","From our earliest days, our story was unlikely. We are a company started by two graduate students and a professor, headquartered in Salt Lake City, Utah. Our humble and unlikely beginnings are foundational to what we’ve built today. We were underdogs, and felt that way. Now we are leaders in this space, and we vow to stay hungry and focused on our mission. We are a biotechnology company scaling more like a technology company, and we are just getting started.","1","2023-08-08 19:41:20","2023-11-20 22:26:53","" -"299","Google Cloud","","google-cloud","logo/google-cloud.jpg","https://cloud.google.com/?hl=en","Google Cloud is widely recognized as a global leader in delivering a secure, open and intelligent enterprise cloud platform. Our technology is built on Google’s private network and is the product of nearly 20 years of innovation in security, network architecture, collaboration, artificial intelligence and open source software. We offer a simply engineered set of tools and unparalleled technology across Google Cloud Platform and G Suite that help bring people, insights and ideas together. Customers across more than 150 countries trust Google Cloud to modernize their computing environment for today’s digital world.","1","2023-08-08 19:43:02","2023-11-20 22:26:58","" -"300","DoiT International","","doit","logo/doit.png","https://www.doit.com/","You have the cloud and we have your back. For nearly a decade, we’ve been helping businesses build and scale cloud solutions with our world-class cloud engineering support. We help our customers with technical support and consulting on building and operating complex large-scale distributed systems, developing better machine learning models and setting up big data solutions using Google Cloud, Amazon AWS and Microsoft Azure.","1","2023-08-08 19:43:17","2023-11-20 22:27:03","" -"301","Lambda","","lambda","logo/lambda.jpg","https://lambdalabs.com/","Our workstations, servers, laptops, and cloud services power engineers and researchers at the forefront of human knowledge. Our customers include Intel, Microsoft, Amazon Research, Kaiser Permanente, MIT, Stanford, Harvard, Caltech, and the Department of Defense. With Lambda, you simply plug the system into the wall and get started making business and scientific breakthroughs. That's why the greatest companies and research labs in the world work with Lambda.","1","2023-08-08 19:43:31","2023-11-20 22:27:11","" -"302","Center for the Study of Movement, Cognition, and Mobility","","cmcm","logo/tasmc.jpeg","https://rnd.tasmc.org.il/laboratories/center-for-the-study-of-movement-cognition-and-mobility-prof-jeff-hausdorff/","As the baby boomers age, the number of adults who suffer from frequent falls, gait disorders, cognitive impairment, dementia, and other neurological diseases continues to increase dramatically. New understandings and therapeutic approaches are needed. Our research aims to improve the personalized treatment of age-related movement, cognition, and mobility disorders and to alleviate the burden associated with them.`","1","2023-08-08 19:54:16","2023-11-20 22:27:18","CMCM" -"303","Research Group for Neurorehabilitation","","enrgy","logo/ku-leuven.jpg","https://gbiomed.kuleuven.be/english/research/50000743/research/research-units/enrgy","The mission of the Neurorehabilitation Research Group (eNRGy) is to advance the evidence-base of neurorehabilitation of child and adult populations with acute and chronic neurological conditions. In doing so, our research activities tackle both fundamental and translational research questions aimed at increasing our understanding of neurobehavioral and neuromuscular mechanisms, relevant for innovation and refinement of rehabilitation interventions. The clinical challenge of eNRGy lies in addressing the complexity of the brain and its role in neuromotor function, including deficits in the motor, sensory, social and cognitive domain.","1","2023-08-08 19:55:53","2023-11-20 22:39:07","eNRGy" -"304","Hinda and Arthur Marcus Institute for Aging","","marcus-institute","logo/hebrew-seniorlife.jpg","https://www.marcusinstituteforaging.org/","Since 1966, the Hinda and Arthur Marcus Institute for Aging Research has challenged conventional wisdom to better understand how we age. The questions we ask - and the answers we uncover - directly impact standards of care and help seniors live more vital, meaningful lives. The Marcus Institute is one of the largest gerontological research facilities in a clinical setting in the U.S. Our decades-long relationship with Harvard Medical School attracts expert teaching staff and outstanding research fellows. Our research portfolio increased 90% from 2010 to 2022 and ranks us in the top 10% of institutions funded by the National Institutes of Health.","1","2023-08-08 19:59:31","2023-11-20 22:39:17","" -"305","University Hospital Zurich","","usz","logo/usz.jpg","https://www.usz.ch/en/","The University Hospital Zurich (USZ) is open to all patients every day and provides fundamental medical care and cutting-edge medicine in a central location in Zurich. We use our superior academic knowledge to treat a wide range of health issues, taking a personal touch and utilizing highly specialized and up-to-date research.","1","2023-08-09 22:21:15","2023-11-20 22:39:22","USZ" -"306","Zurich University of Applied Sciences","","zhaw","logo/zhaw.jpg","https://www.zhaw.ch/en/university/","The ZHAW is one of the leading universities of applied sciences in Switzerland. It offers teaching, research, continuing education and other services that are both practice-oriented and science-based. Research & development at the ZHAW focuses on key societal challenges, with a particular emphasis on energy and societal integration. With its expertise in sustainable development and digital transformation, the ZHAW imparts forward-looking knowledge and takes an active part in shaping the digital and ecological transformation. With locations in Winterthur, Zurich and Wädenswil, the ZHAW is firmly anchored in its region whilst collaborating with international partners.","1","2023-08-09 22:22:32","2023-11-20 22:39:28","ZHAW" -"307","Helmholtz Munich","","helmholtz-munich","logo/helmholtz-munich.jpg","https://www.helmholtz-munich.de/en","We are Helmholtz Munich. We discover breakthrough solutions for better health in a rapidly changing world. Our world is constantly changing. This impacts our health. Many widespread diseases such as diabetes, allergies and lung diseases are on the rise. Climate change is causing new diseases to emerge. We develop solutions for a healthier future. Our cutting-edge research is the springboard for medical innovations. Together with our partners, we accelerate the transfer from ideas to applications, from labs to startups, from science to society.","1","2023-08-09 22:23:10","2023-11-20 22:39:34","" -"308","Imperial College London","","imperial","logo/imperial.jpg","https://www.imperial.ac.uk/","Imperial is a global top ten university with a world-class reputation in science, engineering, business and medicine. Together, we are Imperial.","1","2023-08-09 22:24:26","2023-11-20 22:39:40","" -"309","Geneva University Hospitals","","hug","logo/hug.png","https://www.hug.ch/","The result of a centuries-old tradition of excellence in medicine and science, the HUG was created in 1995. Bringing together the eight Geneva public hospitals and, since July 1, 2016, two clinics (Joli-Mont and Crans-Montana), they represent the leading university hospital in Switzerland. They also have 30 outpatient consultations, spread throughout the canton of Geneva.","1","2023-08-09 22:26:11","2023-11-20 22:39:43","HUG" -"310","National University Hospital","","nuh","logo/nuh.jpeg","https://www.nuh.com.sg/Pages/Home.aspx","The National University Hospital (NUH) is Singapore’s leading university hospital. While the hospital at Kent Ridge first received its patients on 24 June 1985, our legacy started from 1905, the date of the founding of what is today the NUS Yong Loo Lin School of Medicine. NUH is the principal teaching hospital of the medical school. Our unique identity as a university hospital is a key attraction for healthcare professionals who aspire to do more than practise tertiary medical care. We offer an environment where research and teaching are an integral part of medicine, and continue to shape medicine and transform care for the community we care for. We are an academic medical centre with over 1,200 beds, serving more than one million patients a year with over 50 medical, surgical and dental specialties. NUH is the only public and not-for-profit hospital in Singapore to provide trusted care for adults, women and children under one roof, including the only paediatric kidney and live...","1","2023-08-09 22:27:16","2023-11-20 22:39:47","NUH" -"311","Princess Maxima Center for Pediatric Oncology","","princess-maxima-center","logo/princess-maxima-center.jpg","https://www.prinsesmaximacentrum.nl/en","When a child is seriously ill with cancer, only one thing comes first: cure. That is why at the Princess Máxima Center for pediatric oncology we work together every day in a groundbreaking and passionate way to improve the survival rate and quality of life of children with cancer. Now, and in the longer term. Because children still have a whole life ahead of them. The Princess Máxima Center is not an ordinary hospital, but a research hospital. All children with cancer in the Netherlands are treated here. This makes the Princess Máxima Center the largest pediatric cancer center in Europe. Over 450 researchers and 900 healthcare professionals work closely with Dutch and international hospitals on better treatments and new perspectives on cures. In this way, we give the child of today the very best care and take important steps to improve the chances of survival for the children who are not yet cured.","1","2023-08-09 22:29:04","2023-11-20 22:39:55","" -"312","CHAIMELEON Consortium","","chaimeleon","logo/chaimeleon.svg","https://chaimeleon.eu/#partners","The interdisciplinary CHAIMELEON consortium is made up of 18 partners from 9 countries: Fundación para la Investigación del Hospital Universitario la Fe de la Comunidad Valenciana (ES), Universita di Pisa (IT), Universita Degli Studi di Roma la Sapienza (IT), Centro Hospitalar Universitário de Santo António (PT), ICCS Policlinico San Donato (IT), College des Enseignants de Radiologie (FR), Universiteit Masstricht (NL), Charité Universitätsmedizin Berlin (DE), Imperial College London (UK), Ben-Gurion University of the Negev (IL), Universitat Politècnica de Valencia (ES), GE Healthcare (DE), Quibim (ES), Medexprim (FR), Bahia (ES), Matical Innovation (ES), European Institute of Biomedical Imaging Research (AT), Universitat de Valencia (ES). It constitutes a pan-European ecosystem of knowledge, infrastructures, biobanks and technologies on oncology, AI/in-silico and cloud computing addressed to health. The CHAIMELON project also collaborates with other European projects and initiatives.","1","2023-08-09 22:48:43","2023-11-20 22:40:01","" -"313","Office of Digital Transformation","","odt","logo/fda.svg","https://www.fda.gov/about-fda/office-commissioner/office-digital-transformation","The Office of Digital Transformation (ODT) provides the vision and leadership in information technology (IT), data, and cybersecurity needed to advance FDA’s mission and strategic priorities. ODT is led by the Chief Information Officer and reports to the FDA Commissioner. ODT directs and coordinates enterprise strategic planning, policy, and resource management to ensure that Agency IT, data, and cybersecurity investments and activities provide maximum value to FDA. ODT is comprised of the Office of Information Management and Technology (OIMT), Office of Data, Analytics, and Research (ODAR), and the Office of Information Security (OIS), under the direction of the Chief Technology Officer (CTO), Chief Data Officer (CDO), and Chief Information Security Officer (CISO). ODT is committed to delivering trusted technology and data solutions that enable FDA to reimagine the possible. Watch this video to learn more about our organization and how we are striving to make an impact at FDA.","2","2023-08-10 21:37:33","2023-08-10 21:39:34","ODT" -"314","Office of Minority Health and Health Equity","","omhhe","logo/fda.svg","https://www.fda.gov/about-fda/office-commissioner/office-minority-health-and-health-equity","The FDA Office of Minority Health and Health Equity (OMHHE) serves to promote and protect the health of diverse populations through research and communication of science that addresses health disparities.","1","2023-08-10 21:37:42","2023-08-10 21:40:30","OMHHE" -"315","Office of Data, Analytics, and Research","","odar","logo/fda.svg","https://www.fda.gov/about-fda/office-digital-transformation/office-data-analytics-and-research-odar","The Office of Data, Analytics, and Research (ODAR) manages and improves FDA’s ability to leverage data as a strategic asset by establishing enterprise data strategy and priorities.","2","2023-08-10 21:37:44","2023-08-10 21:38:28","ODAR" -"316","Medicines and Healthcare products Regulatory Agency","","mhra","logo/mhra.jpg","https://www.gov.uk/government/organisations/medicines-and-healthcare-products-regulatory-agency","We are the regulator of medicines, medical devices and blood components for transfusion in the UK. We put patients first in everything we do, right across the lifecycle of the products we regulate. We rigorously use science and data to inform our decisions, enable medical innovation and to make sure that medicines and healthcare products available in the UK are safe and effective.","1","2023-08-10 22:10:11","2023-11-20 22:40:12","MHRA" -"317","MDClone","","mdclone","logo/mdclone.jpg","https://www.mdclone.com/","MDClone is a technology firm focused on unlocking healthcare data and empowering exploration, discovery, and collaboration to improve patients' health. At MDClone, we are a growing startup with big aspirations. We are determined to make an impact on healthcare worldwide with tools, processes, and services focused on turning data into better outcomes. MDClone is focused on empowering healthcare institutions, enabling stronger and more secure relationships between healthcare providers and life science companies, and developing regional and global collaboration with privacy-enabled shared data sets.","1","2023-08-10 22:11:58","2023-11-20 22:40:25","" -"318","Washington Business Dynamics, LLC","","wbd","logo/wbd.jpeg","https://www.wbdynamics.com/","Since our founding, WBD has sought to be a management consulting provider of choice for the federal government and the private sector. We are privileged to count many of the world’s foremost institutions and organizations among our client list. We partnered with these organizations’ senior leaders and immediately began uncovering value. Our staff brings a superior analytic capability, time-tested best practices, and a logical approach to solve problems and position organizations for future success.","1","2023-08-10 22:12:50","2023-11-20 22:40:38","WBD" -"319","Medical College of Wisconsin","","mcw","logo/medical-college-wisconsin-logo.svg","https://www.mcw.edu/","The Medical College of Wisconsin is a private medical school, pharmacy school, and graduate school of sciences headquartered in Milwaukee, Wisconsin. The school was established in 1893 and is the largest research center in eastern Wisconsin.","5","2023-09-09 01:40:31","2023-09-09 03:10:17","MCW" -"320","Boston University","","bu","logo/bu.jpg","https://www.bu.edu/","Boston University is no small operation. With over 36,000 students from more than 130 countries, over 10,000 faculty and staff, 17 schools and colleges and the Faculty of Computing & Data Sciences, and more than 300 programs of study, our three campuses are always humming, always in high gear. Get to know the people and teams that keep the University running smoothly.","1","2023-09-12 23:58:11","2023-11-20 22:40:44","BU" -"321","Telethon Institute of Genetics and Medicine","","tigem","logo/tigem.jpg","https://www.tigem.it/","The Telethon Institute of Genetics and Medicine (TIGEM), a Telethon Foundation organization, was founded in 1994 as a leading European research center. TIGEM is a Telethon Foundation research centre in Pozzuoli, Italy. TIGEM comprises several research groups and over 200 staff members, all dedicated to understanding the molecular mechanisms behind rare genetic diseases and developing novel treatments. These diseases, often overlooked by pharmaceutical industries, are most common in children and adolescents. TIGEM’s research falls into three main themes: Cell Biology and Disease Mechanisms, Genomic Medicine, and Molecular Therapy. Our research is supported by a number of in-house highly specialised facilities, as well as significant international support in the form of funding and collaborative opportunities.","1","2023-09-13 00:01:07","2023-11-20 22:40:49","TIGEM" -"322","Genome Institute of Singapore","","gis","logo/gis.jpg","https://www.a-star.edu.sg/gis","When the Genome Institute of Singapore (GIS) was established in 2000, the science of genomics was still in its infancy. Since then, genomics has proved its relevance to all aspects of biology and medicine. It is now possible to sequence entire populations and communities, resolve organs at the single-cell level, and develop treatments guided by genomic data. We are now able to edit genomes at will, synthesise chromosomes, and perform complex experiments in silico by harnessing the ever-growing reservoir of public-access data. Importantly, while much has been done, much remains to be discovered as our knowledge of genomes, both human and non-human, remains incomplete. Through it all, GIS has maintained its leadership and relevance in genomic science by focusing on its three core strengths - asking the right biological questions, applying and developing cutting-edge technology platforms, and embracing multi-disciplinary team science. These core strengths have served us well, and wi...","1","2023-09-13 00:05:51","2023-11-20 22:48:16","GIS" -"323","University of Rostock","","university-of-rostock","logo/university-of-rostock.jpg","https://www.uni-rostock.de/en/","Founded in 1419, the University of Rostock is the oldest in the Baltic Sea Region. True to the motto “Traditio et Innovatio”, the University of Rostock has constantly further developed. The multitude of new buildings represents the university’s modernity.","1","2023-09-13 00:22:55","2023-11-20 22:59:13","" -"324","FlowCAP","","flowcap","","","This organization may no longer exist, has rebranded, or has been merged under another organization.","1","2023-09-13 00:36:41","2023-09-13 00:37:01","" -"325","University of California, Santa Barbara","","ucsb","logo/uc-santa-barbara.jpg","https://www.ucsb.edu/","At UC Santa Barbara, we offer a dynamic environment that prizes academic inquiry and interpersonal connection to inspire scholarly ambition, creativity, and discoveries with wide-ranging impact. We’re inquisitive and curious, community-driven and globally-focused. Across our campus, you’ll find independent thinkers and consensus builders, Nobel Laureates and leaders chasing noble causes. But no matter how you define us, we are above all Gauchos — diverse in our pursuits, yet connected in our collective drive toward excellence.","2","2023-09-13 16:57:59","2023-11-21 01:16:04","UCSB" -"326","GlaxoSmithKline","","gsk","logo/gsk.jpg","https://www.gsk.com/en-gb/","We are a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together. We aim to positively impact the health of 2.5 billion people by the end of 2030. Our bold ambitions for patients are reflected in new commitments to growth and a step-change in performance. We are a company where outstanding people can thrive.","2","2023-09-13 17:17:03","2023-11-20 22:59:33","" -"327","Carnegie Mellon University","","cmu","logo/cmu.jpg","https://www.cmu.edu/","Carnegie Mellon University challenges the curious and passionate to imagine and deliver work that matters. A private, global research university, Carnegie Mellon stands among the world's most renowned educational institutions, and sets its own course. Start the journey here. Over the past 10 years, more than 400 startups linked to CMU have raised more than $7 billion in follow-on funding. Those investment numbers are especially high because of the sheer size of Pittsburgh’s growing autonomous vehicles cluster - including Uber, Aurora, Waymo and Motional - all of which are here because of their strong ties to CMU. With cutting-edge brain science, path-breaking performances, innovative startups, driverless cars, big data, big ambitions, Nobel and Turing prizes, hands-on learning, and a whole lot of robots, CMU doesn't imagine the future, we create it.","1","2023-09-13 23:36:25","2023-11-20 22:59:39","CMU" -"328","ContextVision","","contextvision","logo/contextvision.png","https://www.contextvision.com/","Our cutting-edge technology helps doctors accurately interpret medical images, a crucial foundation for better diagnosis and treatment. Healthcare providers worldwide face the same key challenge - a challenge that ContextVision is helping to solve: how to increase patient care while coping with limited resources. ContextVision provides intelligent technology that improves healthcare service and outcomes for more people. The company specializes in image analysis and artificial intelligence.","2","2023-09-15 17:21:50","2023-11-20 22:59:45","" -"329","Karolinska Institute","","ki","logo/ki.jpg","https://ki.se/en","Karolinska Institutet is one of the world’s leading medical universities. Our vision is to advance knowledge about life and strive towards better health for all. Karolinska Institutet accounts for the single largest share of all academic medical research conducted in Sweden and offers the country’s broadest range of education in medicine and health sciences. The Nobel Assembly at Karolinska Institutet selects the Nobel laureates in Physiology or Medicine.","1","2023-09-15 17:24:17","2023-11-20 22:59:48","KI" -"330","Research to the People","hello@researchtothepeople.org","research-to-the-people","logo/research-to-the-people.png","https://www.researchtothepeople.org/","Research to the People is a patient-partnered research program for open Oncology and Rare Disease Cases.","1","2023-09-28 21:15:01","2023-10-06 20:58:33","" -"333","University of Utah","","u-of-u","logo/u-of-u.jpg","https://www.utah.edu/","Imagine what you want to accomplish, then really making it happen. Imagine designing and publishing a video game before earning your diploma, starting a business while studying business, and doing all this in a setting that begs you to get out and do something. Imagine, then Do. Opportunity awaits and all things are possible at a place we call Imagine U. The University of Utah.","3","2023-10-06 20:17:06","2023-11-20 23:00:08","" -"336","University of California, Irvine","","uci","logo/uci.jpg","https://uci.edu/","In 1965, the University of California, Irvine was founded with a mission to catalyze the community and enhance lives through rigorous academics, cutting-edge research, and dedicated public service. Today, we draw on the unyielding spirit of our pioneering faculty, staff and students who arrived on campus with a dream to inspire change and generate new ideas. We believe that true progress is made when different perspectives come together to advance our understanding of the world around us. And we enlighten our communities and point the way to a better future. At UCI, we shine brighter.","1","2023-10-06 20:26:57","2023-11-20 23:00:27","UCI" -"337","Harvard Personal Genome Project","","harvard-pgp","logo/harvard-pgp.png","https://pgp.med.harvard.edu/","Starting in 2005 as a pilot experiment with 10 individuals, the Harvard Personal Genome Project (Harvard PGP) pioneered a new form of genomics research. The main goal of the project is to allow scientists to connect human genetic information (human DNA sequence, gene expression, associated microbial sequence data, etc) with human trait information (medical information, biospecimens and physical traits) and environmental exposures. Project participants consent to provide biological samples from themselves in order to perform whole genome sequencing, and use of these materials for biological research. The project now has over 5,000 participants.","3","2023-10-06 20:31:44","2023-11-20 23:37:54","" -"339","Johns Hopkins University","","jhu","logo/johns-hopkins.jpg","https://www.jhu.edu/","“What are we aiming at?” That’s the question our university’s first president, Daniel Coit Gilman, asked at his inauguration in 1876. What is this place all about, exactly? His answer: “The encouragement of research . . . and the advancement of individual scholars, who by their excellence will advance the sciences they pursue, and the society where they dwell.” Gilman believed that teaching and research go hand in hand—that success in one depends on success in the other—and that a modern university must do both well. He also believed that sharing our knowledge and discoveries would help make the world a better place. In 145 years, we haven’t strayed from that vision. This is still a destination for excellent, ambitious scholars and a world leader in teaching and research. Distinguished professors mentor students in the arts and music, humanities, social and natural sciences, engineering, international studies, education, business, and the health professions. Those same faculty...","3","2023-10-06 20:32:36","2023-11-20 23:01:10","JHU" -"342","University of Kansas Medical Center","","kumc","logo/kumc.jpg","https://www.kumc.edu/","The University of Kansas Medical Center's mission is to improve lives and communities in Kansas and beyond through innovation in education, research and health care.","1","2023-10-06 20:34:22","2023-11-20 23:01:07","KUMC" -"343","Rare Genomes Project","","rgp-project","logo/rgp-project.svg","https://raregenomes.org/how-it-works","The Rare Genomes Project at the Broad Institute of MIT and Harvard is a team of researchers, physicians, software developers, genetic counselors, and study coordinators who believe that the latest advances in genomic sequencing are changing medicine and should be more broadly available to families with rare and undiagnosed conditions.","1","2023-10-06 20:36:09","2023-11-20 23:38:05","" -"344","Invitae","","invitae","logo/invitae.jpg","https://www.invitae.com/en?gad=1&gclid=CjwKCAjw4P6oBhBsEiwAKYVkq6rR_TeHQ4BDrXBBmTUELJgcJvCoj6dlNobNg2hbY4wzcRdk5P6-IxoCCj4QAvD_BwE","At Invitae, we believe that good health is possible—and that genetic information has the ability to transform the way medicine is practiced, making what once seemed impossible possible, as we empower people to make decisions about their health through the power of genetics.","1","2023-10-06 20:38:01","2023-11-20 23:38:12","" -"346","Seattle Children's Hospital","","seattle-childrens","logo/seattle-childrens.jpg","https://www.seattlechildrens.org/","This isn’t about beating the odds. This is about changing them. We fight relentlessly to make sure there’s no such thing as “out of options” and to make sure kids who “didn't have a chance” can have the childhoods they deserve. At Seattle Children’s, we’re united by a compelling mission: We provide hope, care and cures to help every child live the healthiest and most fulfilling life possible. Consistently ranked one of the nation’s best children’s hospitals.Together, we deliver superior patient care, advance new discoveries and treatments through pediatric research and serve as the pediatric and adolescent academic medical center for Washington, Alaska, Montana and Idaho – the largest region of any children’s hospital in the country. U.S. News & World Report has recognized Seattle Children’s as a top children’s hospital every year since it began ranking medical facilities more than 30 years ago. This means your child will be cared for by the very best.","1","2023-10-06 20:39:31","2023-11-20 23:38:25","" -"347","Christian-Albrechts-Universität zu Kiel","","cau","logo/cau.png","https://www.uni-kiel.de/en/","Kiel University (CAU) was founded back in 1665. It is Schleswig-Holstein's oldest, largest and best-known university, with 27,000 students and around 3,700 members of staff. It is also the only fully-fledged university in the state. Seven Nobel prize winners have worked here. The CAU has been successfully taking part in the Excellence Initiative since 2006.","3","2023-10-06 20:40:42","2023-11-20 23:38:31","CAU" -"348","CACHE","","cache","logo/cache.png","https://cache-challenge.org/","CACHE will help define the state-of-the-art in molecular design by providing unbiased, high quality experimental feedback on computational hit-finding predictions. To this end, CACHE will initiate a new hit-finding benchmarking exercise every four months. These public competitions (challenges) will have the added benefit of identifying new chemical starting points for biologically interesting targets. Each competition will focus on a new protein target representing one of five possible challenges in hit-finding, based on the type of target data available. Participants will use their computational method to predict hits that will be tested experimentally by CACHE. Each challenge will involve two cycles of predictions in order to give participants the opportunity to incorporate learnings from the first round into their designs. At the end of each challenge, CACHE will release all data, including chemical structures, to the public.","4","2023-10-06 21:25:30","2023-11-20 23:15:21","" -"349","National Institute of Diabetes and Digestive and Kidney Diseases","healthinfo@niddk.nih.gov","niddk","logo/nih.png","https://www.niddk.nih.gov/","NIDDK research creates knowledge about and treatments for diseases that are among the most chronic, costly, and consequential for patients, their families, and the Nation.","1","2023-10-18 17:07:25","2023-10-27 20:25:54","NIDDK" -"350","Jeroen Bosch Ziekenhuis","","jbz","logo/jbz.jpg","https://www.jeroenboschziekenhuis.nl/","Our starting point is that you deserve the care that suits you. Together with you, we determine what you need and from whom, so that you can live the life you want for as long as possible. We use all our medical expertise to achieve this and work together, for example with your family and friends, your GP, the municipality and home care. Here you can read how we have been working since 2016 on care that suits you and work that suits you. Simply because you matter.","1","2023-11-02 15:42:18","2023-11-20 23:39:18","JBZ" -"351","Diagnostic Image Analysis Group","","diagnostic-image-analysis-group","logo/radboud-umc.jpeg","https://www.diagnijmegen.nl/","The Diagnostic Image Analysis Group is part of the Departments of Imaging, Pathology, Radiation Oncology, Cardiology, and Neurology of Radboud University Medical Center. We develop computer algorithms to interpret and process medical images.","3","2023-11-02 18:12:04","2023-11-20 23:39:14","" -"352","Center for Applied Medical Research, University of Navarre","","cima","logo/cima.jpg","https://cima.cun.es/en/","We are a research center committed to excellence in translational research, based on novel biological knowledge and aimed at finding therapeutic solutions to patients' needs. We are the biomedical research center of the Universidad de Navarra. With our academic status we work on a non-profit basis to reinvest the surpluses in the progress of our research and to fulfill our mission of service to patients and society.","1","2023-11-08 20:21:05","2023-11-20 23:39:25","CIMA" -"353","London School of Hygiene and Tropical Medicine","","lshtm","logo/lshtm.jpg","https://www.lshtm.ac.uk/","The London School of Hygiene & Tropical Medicine is renowned for its research, postgraduate studies and continuing education in public and global health. We have an annual research income of more than £190 million and are one of the highest-rated research institutions in the UK.","1","2023-11-08 20:22:27","2023-11-20 23:39:33","LSHTM" -"354","Quantib","","quantib","logo/quantib.jpg","https://www.quantib.com/","The Quantib story started 9 years ago as a spin-off of Erasmus MC, a globally leading academic center. That's how Quantib was founded but we haven't stopped growing since. We serve customers worldwide, have offices in Europe and the US and employ over 30 bright, motivated people. Our AI solutions are FDA-cleared, CE-marked and vendor neutral. Their easy integration with PACS makes them integrate seamlessly into radiologists' workflows.","1","2023-11-08 23:06:25","2023-11-20 23:39:50","" -"355","Biomediq","","biomediq","logo/biomediq.svg","http://www.biomediq.com/index.html","Biomediq is a research-based company providing software-based solutions for clinical trials and clinical practice. We perform contract research and market validated, automatic and semi-automatic analyses of: 1) knee MRI for scoring of cartilage quantity (volume, thickness, ...) and quality (surface smoothness, homogeneity, congruity, ...); and bone structure in relation to osteoarthritis; 2) mammograms for breast cancer risk; 3) atrophy and tissue structure from Brain MRI for Alzheimer's disease; and 4) synovitis and erosions from Hand MRI for rheumatoid arthritis","1","2023-11-08 23:10:13","2023-11-20 23:40:00","" -"356","International Research Laboratory on Artifical Intelligence","","ipal","logo/ipal.png","https://ipal.cnrs.fr/","IPAL is a CNRS International (French-Singaporean) Research Laboratory (IRL 2955), based in Singapore. It was funded in 1998 as a special overseas CNRS Research Project in order to create a framework for collaborative research projects including CNRS, NUS, and A*Star. This first research structure moved to the status of CNRS Research Group in 2000. In 2007, IPAL became a CNRS IRL (the highest label among the CNRS international programs). The IRL agreement was signed in January 2007, for an initial period of 4 years (renewable), between the CNRS (INS2I institute), A*Star (I2R Institute), NUS (School of Computing), and the University of Grenoble-Alpes, France. The agreement was renewed in 2011 and 2015, with additional partners (Institut Mines Telecom, France, and Sorbonne University, France). In 2019, the IPAL agreement has been extended for two more years in order to prepare a new scientific program focused on Artificial Intelligence, starting in 2021. The main partners involved ...","1","2023-11-08 23:54:53","2023-11-20 23:40:09","IPAL" -"357","Centre National de la Recherche Scientifique","","cnrs","logo/cnrs.jpg","https://www.cnrs.fr/en","The French National Centre for Scientific Research is among the world's leading research institutions. Its scientists explore the living world, matter, the Universe, and the functioning of human societies in order to meet the major challenges of today and tomorrow. Internationally recognised for the excellence of its scientific research, the CNRS is a reference in the world of research and development, as well as for the general public.","1","2023-11-08 23:57:51","2023-11-20 23:40:22","CNRS" -"358","Université Joseph Fourier","","ujf","","www.ujf-grenoble.fr","This organization may no longer exist, has rebranded, or has been merged under another organization.","1","2023-11-09 00:02:07","2023-11-09 00:04:03","UJF" -"359","Sorbonne Université","","sorbonne-university","logo/sorbonne-university.png","https://www.sorbonne-universite.fr/en","Sorbonne Université promotes excellence at the heart of each of its disciplines and runs numerous interdisciplinary programs capable of meeting the major challenges of the 21st century.","1","2023-11-09 00:05:42","2023-11-20 23:40:36","" -"360","A*STAR-I2R","","a*star-i2r","","https://www.iala-aism.org/organisation/st-electronics-info-software-systems-pte-ltd/","The Institute for Infocomm Research (I^2R pronounced as i-squared-r) is a member of the Agency for Science, Technology and Research (A*STAR) family and is Singapore’s largest ICT research institute. Established in 2002, our vision is to power a vibrant and strong infocomm ecosystem in Singapore. We seek to foster world-class research and develop a deep talent pool of infocomm professionals to power a vibrant knowledge-based Singapore. At I2R, our key research areas are in Artificial Intelligence, Audio; Language & Speech, Data Analytics, Communications & Networks, Cybersecurity, Heterogeneous Analytics, Healthcare, Robotics & AV, Satellite, Smart Energy & Environment and Video & Image Analytics.","1","2023-11-09 00:10:02","2023-11-20 23:32:39","" -"361","Université Pierre-et-Marie-Curie","","upmc","logo/sorbonne-university.png","https://www.sorbonne-universite.fr/en","This organization may no longer exist, has rebranded, or has been merged under another organization.","1","2023-11-09 00:13:38","2023-11-20 23:40:37","UPMC" -"363","Gentofte Hospital","","gentofte-hospital","logo/gentofte-hospital.jpg","https://www.gentoftehospital.dk/English-/Pages/default.aspx","Founded in 1927, Gentofte Hospital stands as one of Denmark's oldest and most esteemed healthcare institutions. With a rich history spanning many years, our hospital has played a important role in the nation's healthcare landscape, offering specialized medical care, advanced research, and academic collaboration. On the first of January 2015, Herlev Hospital and Gentofte Hospital were merged in order to provide the best possible service to its patients. The merge doesn´t affect the individual patient, but only contributes to a more streamlined workflow for the employees.","1","2023-11-09 00:21:38","2023-11-20 23:40:53","" -"364","Rigshospitalet","","rigshospitalet","logo/gentofte-hospital.jpg","https://www.rigshospitalet.dk/english/Pages/default.aspx","We are a highly specialised hospital which, with a few exceptions, covers all medical specialist areas.","1","2023-11-09 00:21:40","2023-11-20 23:41:36","" -"365","Fraunhofer Institute for Digital Medicine MEVIS`","","mevis","logo/fraunhofer.jpeg","https://www.mevis.fraunhofer.de/","Embedded in a worldwide network of clinical and academic partners, Fraunhofer MEVIS develops real-world software solutions for image and data supported early detection, diagnosis, and therapy. Strong focus is placed on cancer as well as diseases of the circulatory system, brain, breast, liver, and lung. The goal is to detect diseases earlier and more reliably, tailor treatments to each individual, and make therapeutic success more measurable. In addition, the institute develops software systems for industrial partners to undertake image-based studies to determine the effectiveness of medicine and contrast agents. To reach its goals, Fraunhofer MEVIS works closely with medical technology and pharmaceutical companies, providing solutions for the entire chain of development from applied research to certified medical products.","1","2023-11-09 18:32:08","2023-11-20 23:53:32","MEVIS" -"366","Rutgers University","","rutgers","logo/rutgers.png","https://www.rutgers.edu/","Rutgers, The State University of New Jersey, stands among America’s highest-ranked, most diverse public research universities. The oldest, largest, and top-ranked public university in the New York/New Jersey metropolitan area, you’ll find us at our main locations in three New Jersey cities, and our footprint can be seen around the region. We’re an academic, health, and research powerhouse and a university of opportunity.","1","2023-11-09 18:51:08","2023-11-20 23:53:40","" -"367","Philips","","philips","logo/philips.jpg","https://www.usa.philips.com/healthcare","At Philips, our purpose is to improve people’s health and well-being through meaningful innovation. We aim to improve 2.5 billion lives per year by 2030, including 400 million in underserved communities. As a technology company, we – and our brand licensees – innovate for people with one consistent belief: there’s always a way to make life better.","2","2023-11-09 20:43:17","2023-11-20 23:53:53","" -"368","Translational Research IT","","trait","logo/health-ri.jpg","http://trait.health-ri.nl/","The Translational Research IT (TraIT) project provides an easy-to-access and easy-to-use infrastructure for data sharing, together with a set of tools for further exploration of the collected data. It operates across the four major domains of translational research: clinical, imaging, biobanking, and experimental (any-omics). TraIT gives scientists within multi-site projects the resources needed to share and disseminate data and analyses. Importantly, the project aimed to adopt and adapt existing and proven solutions (e.g. XNAT, Ldot, cBioPortal) rather than embarking on major software development projects. As of January 2020, more than 4000 researchers from over 400 studies and dispersed over more than 500 locations are making use of one or more of TraIT’s services.","1","2023-11-09 21:21:20","2023-11-20 23:54:06","TraIT" -"369","Stichting IT Projecten","","stitpro","logo/stitpro.png","https://stitpro.nl/projects/","StITPro provides subsidies to ICT projects. StITPro wants to ensure that software is developed for educational and socially relevant purposes. Conditions for this are that the software is 'open source', the use of the software extends beyond the initial target group and the software remains operational and supported for a longer period of time.","2","2023-11-09 21:31:58","2023-11-20 23:54:10","" -"370","Universidade do Porto","","u-porto","logo/u-porto.jpg","https://www.up.pt/portal/en/","The University of Porto is a public foundation regulated by private law and with statutory, educational, scientific, cultural, administrative, financial, patrimonial and disciplinary autonomy. U.Porto can undertake activities with other national or international entities (public, private or cooperative). The University of Porto can create or participate in associations or societies, for-profit or non-profit, as long as the activities are compatible with its mission.","2","2023-11-09 21:35:42","2023-11-20 23:54:27","" -"371","National University of Sciences & Technology","","nust","logo/nust.jpeg","https://nust.edu.pk/","Welcome to the National University of Sciences & Technology, a prestigious institute of higher learning that has become a benchmark of excellence in South Asia. As the leader of this esteemed institution, I am honored to serve and committed to advancing its mission of providing affordable, SDG-engaged, fourth-generation entrepreneurial education. Our faculty and staff are dedicated to excellence in teaching, research, and service, and I am proud of all that we have accomplished together. During the coming year, I am eager to work with all of you to continue this progress and provide a dynamic and supportive learning environment for our students. Our goal is to equip them with the necessary skills and knowledge to tackle the world's most pressing challenges, while also preparing them for the fast-changing world. I welcome you to join us in any capacity to shape the future, lead the nation's progress, and contribute to serving humanity. Let us work together to make the best of 2023,...","1","2023-11-09 21:36:47","2023-11-20 23:54:34","NUST" -"372","University of Dundee","","dundee","logo/dundee.jpg","https://www.dundee.ac.uk/","To transform lives, working locally and globally through the creation, sharing, and application of knowledge.","1","2023-11-09 21:37:52","2023-11-20 23:55:27","" -"373","ISTITUTO ONCOLOGICO VENETO IRCCS","","iov","logo/iov.jpg","https://www.ioveneto.it/en/","The Veneto Institute of Oncology IOV – IRCCS is the first and only medical center in the Veneto region specific for the prevention, diagnosis and treatment of cancer and for cancer research. IOV was established by the Veneto Regional Government in December 2005, becoming a highly specialized health research center of national and international importance. It is recognized by the Ministry of Health as a research hospital (IRCCS) and by the Organization of European Cancer Institutes (OECI) as a Comprehensive Cancer Center. It is a member of the network of excellence Alliance Against Cancer (ACC), the largest Italian organization of clinical and translational cancer research, and of the European Network for Rare Adult Solid Cancer EURACAN.","1","2023-11-09 21:40:36","2023-11-20 23:55:38","IOV" -"374","European Institute of Oncology","","ieo","logo/ieo.jpg","https://www.ieo.it/en/","The IEO (European Institute of Oncology) is one of the world's most prestigious hospitals and the fastest growing comprehensive cancer centre in Europe. IEO integrates the various areas related to the fight against cancer such as prevention, diagnosis, treatment, training and education, basic and translational research.","1","2023-11-09 21:45:04","2023-11-20 23:55:42","IEO" -"375","Oncology Institute Francisco Gentil","","ipo","logo/ipo.jpeg","https://www.ipolisboa.min-saude.pt/","IPO was born out of the dream and work of Francisco Gentil, a surgeon, far ahead of his time, who founded the Portuguese Institute for the Study of Cancer in 1923, focussed on the care to cancer patients, research, study and treatment of the disease. On the founder’s proposal, the Institute was linked, from the beginning, to Medical School of Lisbon University – only 60 years later International Union Against Cancer (UICC) and World Health Organization (WHO) recognised this model of which Portugal was a pioneer and which enabled to bring together the major goals behind the creation of the institution.","1","2023-11-09 21:45:40","2023-11-20 23:55:46","IPO" -"376","University of New South Wales","","unsw-sydney","logo/unsw-sydney.jpg","https://www.unsw.edu.au/","The essence of UNSW Sydney is not found in our impressive facilities or beautiful grounds. It is found in our students, our staff, our alumni and our generous donors. Our collective difference reflects the unique perspectives of our people, place and purpose as we play our part in the creation of a just society.","1","2023-11-09 21:48:25","2023-11-20 23:55:53","UNSW Sydney" -"377","Politecnico di Torino","","polito","logo/polito.jpg","https://www.polito.it/","Politecnico di Torino was the first Italian Engineering School founded in the wave of the technical and scientific innovation that gave rise to the most prestigious European polytechnic schools in the mid-19th century. Founded as School for Engineers in 1859, it then became Regio Politecnico di Torino in 1906. Engineers, architects, designers and urban planners have been trained at Politecnico di Torino for over 160 years with rigor, integrity and high-level standards. This long ever-changing history has rated Politecnico among the top European technical Universities for education and research, with 38,700 students and a teaching staff of more than 1,000. In an evolving global context disrupted by the effects of globalization, climate change, population aging, new and increasingly pervasive technologies, Universities are expected to progress in order to produce an impact on a rapidly changing society. Politecnico di Torino has therefore decided to transform itself into a “platf...","1","2023-11-09 21:52:02","2023-11-20 23:55:59","PoliTo" -"378","3DHISTECH Ltd.","","3dhistech","logo/3dhistech.jpg","https://www.3dhistech.com/","3DHISTECH is dedicated to providing clinical pathologists, researchers and universities with digital pathology solutions to facilitate quick and accurate diagnostics, supporting medical discoveries and fostering education.","1","2023-11-10 16:46:05","2023-11-20 23:56:09","" -"379","3Scan","","3scan","logo/3scan.jpg","www.3scan.com","This organization may no longer exist, has rebranded, or has been merged under another organization.","1","2023-11-10 16:46:07","2023-11-20 23:56:14","" -"380","MedicalPHIT","","medicalphit","logo/medicalphit.jpeg","https://phit.nl/","We make hIT work'. MedicalPHIT employs experts in the field of data exchange, interoperability and IT in healthcare. The focus is on smart solutions to improve healthcare processes. 'We make hIT work' is one of our core values ​​for good reason. We score well on customer and employee satisfaction. We achieve this by being curious and sharing our knowledge. But also by operating as a close-knit team, with independence and making an impact of paramount importance.","1","2023-11-10 16:48:00","2023-11-20 23:56:35","" -"381","Roche Holding AG","","roche","logo/roche.jpg","https://www.roche.com/","Throughout our 125-year history, Roche has grown into one of the world’s largest biotech companies, as well as a leading provider of in-vitro diagnostics and a global supplier of transformative innovative solutions across major disease areas. Our commitment to our people, partners, stakeholders and, most importantly, our patients remains as strong as it was on the first day of our journey.","1","2023-11-10 16:49:26","2023-11-21 00:13:31","" -"382","Sakura Finetek USA","","sakura","logo/sakura.jpeg","https://www.sakuraus.com/","At Sakura Finetek, we are committed to advancing cancer diagnostics by providing integrated solutions for anatomic pathology and patients through best-in-class innovation, quality and customer care.","1","2023-11-10 16:51:21","2023-11-21 00:13:33","" -"383","Sectra","","sectra","logo/sectra.jpg","https://sectra.com/","Driven by knowledge and passion, our vision is to contribute to a healthier and safer society. Sectra successfully develops and sells cutting-edge solutions in the expanding niche segments of medical IT and cybersecurity. The Sectra Group has some 800 employees worldwide.","1","2023-11-10 16:52:42","2023-11-21 00:13:37","" -"384","Pathomation","","pathomation","logo/pathomation.jpeg","https://www.pathomation.com/","Pathomation is a Belgian digital pathology company. It was founded in 2012 by pathologists Mark Kockx and Wim Waelput, and data scientist – software expert Yves Sucaet.","1","2023-11-10 16:53:32","2023-11-21 00:13:44","" -"385","MedUni Wien","","meduni-vienna","logo/meduni-vienna.png","https://www.meduniwien.ac.at/web/en/","The Medical University of Vienna is a leading medical center. The individual institutes, centers, departments and clinics thereby form an inseparable unity of education, research and patient care.","1","2023-11-10 17:13:34","2023-11-21 00:13:56","" -"386","Laboratory for Ophthalmic Image Analysis","","optima","logo/optima.png","https://optima.meduniwien.ac.at/","Laboratory for Ophthalmic Image Analysis (OPTIMA) is an interdisciplinary research lab composed of retinal specialists, computer scientists and software engineers, developing innovative image analysis methods for precision medicine in retinal disease. Our research focus lies on the quantitative analysis of state-of-the-art ophthalmic imaging data, in particular OCT, and the development of prognostic disease models for improved patient management in leading eye diseases. The lab has access to extremely large sets of ophthalmic images and is well-equipped with a dedicated high-performance computing cluster containing the latest generation GPUs. The group keeps close collaboration with several high-performance academic research institutions, as well as partnership with imaging device and pharmaceutical companies. The Medical University of Vienna is an international center of excellence and one of the largest research institutions in Europe located at the heart of historic Vienna. ...","1","2023-11-10 17:16:57","2023-11-21 00:14:06","OPTIMA" -"387","Vienna Reading Center","","vrc","logo/vrc.png","https://viennareadingcenter.meduniwien.ac.at/","The Vienna Reading Center (VRC) provides best-in-class imaging services for clinical, pharmaceutical and academic research in the area of ophthalmology. We are a professional team equipped to respond to the requirements of both international multi-center and single-site investigator studies. Our group includes dedicated clinical retinal experts, high-end software development with year-long ophthalmic image analysis background, administrative and quality management personnel and certified readers. The VRC has established a solid network of collaborations with over 600 academic sites distributed across 5 continents, which have served successfully in numerous prospective randomized clinical trials. In addition to our imaging services, we offer a broad range of complementary services to effectively accomplish new therapeutic strategies for ocular diseases. Our services are supported by state-of-the-art technology offering conventional as well as the most specialized methods available...","1","2023-11-10 17:20:56","2023-11-21 00:14:11","VRC" -"388","Laboratoire de Traitement de l’information Médicale","","latim","logo/latim.jpg","https://latim.univ-brest.fr/","Born from the complementarity between the field of health and the communication sciences, the LaTIM (""laboratoire de traitement de l’information médicale"" for laboratory of medical information processing) develops a multidisciplinary research driven by members from University of Western Brittany, IMT Atlantique, INSERM and Brest CHRU (university hospitals). Information is at the heart of the research project of the unit; being by nature multimodal, complex, heterogeneous, shared and distributed, it is integrated by researchers into methodological solutions for the sole purpose of improving the actual medical benefit. The field of expression of this research focuses on the therapeutic action in oncology (ACTION team) and in the field of interventional therapies (IMAGINE team). Benefiting from a unit within the CHRU, the UMR (joint research unit) has (in addition to access to its own platforms) a privileged access to hospital technical platforms, as well as to all clinical data and ...","1","2023-11-10 17:33:16","2023-11-21 00:14:26","LaTIM" -"389","European Progression Of Neurological Disease initiative","","europond","logo/europond.jpg","http://europond.eu/#:~:text=The%20EuroPOND%20initiative%20is%20a,a%20range%20of%20neurological%20disorders.","The EuroPOND initiative is a unique team of scientists spanning computational neuroscience and clinical neurology. Together we are developing computational models and using state-of-the-art data-science techniques to understand a range of neurological disorders. We are learning characteristic patterns of progression directly from large medical data sets including Alzheimer’s disease, Multiple Sclerosis, normal ageing, and abnormal brain development in preterm infants. These disease signatures will enable improved diagnosis and management of neurological disorders.","1","2023-11-10 17:33:16","2023-11-21 00:14:36","" -"390","Alzheimer's Association","","alz","logo/alz.jpg","https://www.alz.org/","The Alzheimer's Association leads the way to end Alzheimer's and all other dementia — by accelerating global research, driving risk reduction and early detection, and maximizing quality care and support.","1","2023-11-10 17:45:22","2023-11-21 00:14:49","ALZ" -"391","Alzheimer's Society","","alzheimers-society","logo/alzheimers-society.jpg","https://www.alzheimers.org.uk/","At Alzheimer’s Society we’re working towards a world where dementia no longer devastates lives. We do this by giving help to those living with dementia today, and providing hope for the future. As a Society, we are made up of people with dementia, carers, trusted experts, campaigners, researchers and clinicians. We are the UK’s largest collective force of people with unparalleled knowledge and over 40 years of experience addressing the biggest challenges facing people living with dementia.","1","2023-11-10 17:46:24","2023-11-21 00:14:59","" -"392","Institute for Systems and Computer Engineering, Technology and Science","","inesc-tec","logo/inesc-tec.jpg","https://www.inesctec.pt/en","INESC TEC is a private non-profit research association, with Public Interest status, dedicated to scientific research and technological development, technology transfer, advanced consulting and training, and pre-incubation of new technology-based companies. As an institution operating at the interface of the academic and business worlds, bringing closer together academia, companies, public administration, and society, INESC TEC typically applies the knowledge and results generated as part of its research in technology transfer projects, seeking value creation and immediate social relevance.","1","2023-11-10 17:49:29","2023-11-21 00:15:05","INESC TEC" -"393","i3S Association","","i3s","logo/i3s.png","https://www.i3s.up.pt/","The i3S Association merges three institutes and researchers from several schools of the UPorto, thus consolidating an extensive collaboration between all institutions spanning many years. The long-term collaboration between IBMC, INEB and IPATIMUP - the three founding institutes of i3S - encompasses joint projects, co-supervision of PhD students, sharing of large equipment and employment of research staff under coordinated policies. Six schools of the UPorto (FMUP, ICBAS, FMDUP, FCUP, FEUP and FFUP) and three hospitals (CH S João, CH Porto and IPO) also contribute to the activities of i3S. This wide participation of schools, research institutions and hospitals in a research institute is unique in Portugal and it is a valuable asset for science and technology development, while creating an environment that feeds real breakthrough research and translation of discoveries into the clinic. The building where i3S is headquartered, still fairly fresh as it was completed in 2015, is also...","1","2023-11-10 17:53:33","2023-11-21 00:15:13","" -"394","Institute of Molecular Pathology and Immunology of the University of Porto","","ipatimup","logo/ipatimup.jpeg","https://www.ipatimup.pt/Site/","At a time when budgetary constraints and the pandemic are still being felt in terms of oncological diseases, with an impact on both the increase in mortality and the number of cases diagnosed late, Ipatimup begins a new cycle of fortnightly sessions on cancer literacy with same objectives as the first edition: inform about the most recent therapies in the fight against cancer, simplify concepts, raise awareness of early diagnosis and place patients at the center of the discussion. The initiative, which takes place from January 19 to March 23, 2023, in six district capitals, will once again bring together some of the best national experts, with emphasis on the presence of Prof. Manuel Sobrinho Simões. In this edition, we also have the participation of the renowned actor Jorge Serafim who, through popular tales and some humor, will humanize the theme. The initiative is carried out in partnership with Antena1, RTP and Roche Foundation Medicine and also has the support of Merck.","1","2023-11-10 17:57:21","2023-11-21 00:15:32","IPATIMUP" -"395","Isfahan University of Medical Sciences","","mui","","http://www.mui.ac.ir/","As one of the oldest scientific institutions in Iran, Isfahan University of Medical sciences and Health Services abbreviated as MUI has been a pioneer in medical education and research, as well as delivery of health and treatment services in the country. MUI established in 1946, is a first degree governmental university. Faculties are medical sciences oriented with a new trend toward medical engineering and biomedical sciences. It is located in metropolitan city of Isfahan the center of Isfahan province, at central area of Iran. Currently it has more than 1500 academic members working in nine faculties and more then 40 research centers. MUI is responsible for delivery of health services across the vast expanse of the health network which was created in 1985 with the integration of medical education and health services provision in the country. Currently more than 20 health networks and 18 teaching hospitals are covering the health management system of the province.","1","2023-11-10 18:22:25","2023-11-10 18:24:34","MUI" -"396","Shri Guru Gobind Singhji Institute of Engineering and Technology","","sggs","logo/sggs.jpg","https://www.sggs.ac.in/","Established in 1981, Shri Guru Gobind Singhji Institute of Engineering and Technology (SGGSIET), Nanded, is one of the promising leader institutions in technical education, research and technology transfer. Since its inception, the institute is dedicated to students’ centric learning and believes in pursuing academic excellence. It is having neat, clean and green campus spread over land of 46 acres. It receives 100% grant-in aid from Government of Maharashtra. In less than 25 years of its inception, the Institute has made a mark in technical education and quality research which got endorsed by a third party survey constituted by Government of Maharashtra and headed by Dr. F. C. Kohli, Chairman, TCS. Through that survey conducted in 2004, SGGSIE&T, Nanded is identified as an Institute which can be raised to the level of Center of Excellence along with three other well established organizations such as College of Engineering, Pune; VJTI, Mumbai and ICT, Mumbai. The institute offers...","1","2023-11-10 18:31:41","2023-11-21 00:15:58","SGGS" -"397","Universiti Teknologi PETRONAS","","utp","logo/utp.jpg","https://www.utp.edu.my/Pages/Home.aspx","Universiti Teknologi PETRONAS (UTP) was established on 10 January 1997 and is the best private university in Malaysia. The campus is built on a 400 hectare (1,000 acres) site strategically located at Bandar Seri Iskandar, Perak Darul Ridzuan, Malaysia. The university is a wholly-owned subsidiary of PETRONAS, the national oil and gas company of Malaysia. UTP offers a wide range of industry-relevant engineering, science and technology programmes at undergraduate and postgraduate levels. It aims to produce well-rounded graduates with excellent leadership qualities and communication abilities. The university conducts extensive research activities in collaboration with PETRONAS and other institutions and industries, locally and abroad, on six research focus and niche areas. They are self-sustainable building, transport infrastructure, health analytics, hydrocarbon recovery, contaminant management and autonomous system.","1","2023-11-10 18:34:58","2023-11-21 00:16:11","UTP" -"398","Inserm","","inserm","logo/inserm.jpg","https://www.inserm.fr/en/home/","Founded in 1964, Inserm is a public scientific and technological institute which operates under the joint authority of the French Ministries of Health and Research. The institute is dedicated to biomedical research and human health, and is involved in the entire range of activities from the laboratory to the patient’s bedside. It also partners with the most prestigious research institutions in the world that are committed to scientific challenges and progress in these fields.","1","2023-11-10 18:36:35","2023-11-21 00:16:21","" -"399","University of Edinburgh","","university-of-edinburgh","logo/university-of-edinburgh.jpeg","https://www.ed.ac.uk/","Imagine what you could do at a world-leading university that is globally recognised for its teaching, research and innovation. The University of Edinburgh has been providing students with world-class teaching for more than 425 years, unlocking the potential of some of the world's leading thinkers since 1583.","1","2023-11-10 18:37:36","2023-11-21 00:16:27","" -"400","University of Texas Health Science Center at Houston","","uth","logo/uthealth-houston.jpg","https://www.uth.edu/","UTHealth Houston is Texas’ resource for health care education, innovation, scientific discovery, and excellence in patient care. With half a century of experience, UTHealth Houston is one of the nation’s most comprehensive academic health centers.","1","2023-11-10 18:40:53","2023-11-21 00:16:36","UTH" -"401","Université de Bourgogne","","ub","logo/u-bourgogne.jpg","https://en.u-bourgogne.fr/","uB fulfils a dual mission of education and research in all scientific fields. Located in Burgundy between Paris and Lyon, the city of Dijon is home to uB's main campus, with several others spread across the region. It offers 400 different degrees across all levels (Bachelor, Master, and PhD), employs 3,000 staff members, and enrols 34,000 students, among whom more than 2,900 are international. Most programmes are taught in French, but a growing number are taught in English.","1","2023-11-10 18:41:53","2023-11-21 00:16:45","uB" -"402","Shushrusha Hospital","","shushrusha","logo/shushrusha.jpg","https://www.shushrushahospital.org/index.html","Around the period of 1965-70s the state of Maharashtra was undergoing sea change in its development under the able leadership of the then Chief Minister, Shri YB Chavan who initiated the cooperative movement in a big way. Taking advantage of this movement and to benefit the masses, the hospital was conceptualized and planned by Late Dr Vasant Shripad Ranadive under the auspices of Shushrusha Citizen’s Cooperative Hospital Society, Dadar (W). The hospital was founded in 1966, having been registered in 1964, under The Maharashtra Cooperative Societies Act, 1960, and under Maharashtra Nursing Homes Registration Act, 1949. The completed building was inaugurated by the then prime minister of India, Mrs Indira Gandhi, in 1969. Originally it started with 2 floors. Dr Ranadive passed away in 1971. Shortly thereafter it entered a phase of slackening of patient flow when Dr Nandu S Laud, MS (Ortho), took the responsibility of rejuvenating it and developed it to the present level in a gradu...","1","2023-11-10 18:44:45","2023-11-21 00:16:53","" -"403","Dr. Shankarrao Chavan Government Medical College","","drscgmc","logo/drscgmc.jpeg","https://www.drscgmcnanded.in/index.php","Dr.Shankarrao Chavan Government Medical College (Dr.SCGMC) & Hospital - Vishnupuri, situated in Nanded city of Maharashtra. It was established in 1988. The College shifted to the Vishnupuri, Nanded area in March 2015 located on the Nanded-Latur State Highway. Initially, started in 1988, in the Vazirabad area of Nanded attached to Shri Guru Gobind Singhji Memorial Civil hospital.The hospital has grown into a much bigger hospital in an area of 115 acres campus after its shift to the Vishnupuri, Nanded area in the outskirts of the city offering a huge scope for expansion in future in all aspects of medical education research & further development in all technical specialities.","1","2023-11-10 20:07:33","2023-11-21 00:17:00","Dr.SCGMC" -"404","Computational Structural Biology Group","","computational-structural-biology-group-","logo/biozentrum.jpg","http://www.biozentrum.unibas.ch/schwede/","","3","2023-11-11 01:27:47","2023-11-21 00:19:37","" -"405","Swiss Institute of Bioinformatics (SIB)","","sib","logo/sib.jpg","http://sib.swiss/","SIB is a leading organization in biological and biomedical data science. It maximizes the impact of, and investments in scientific projects by making data FAIR (Findable, Accessible, Interoperable and Reusable), provides long-term access to leading Swiss biodata resources, and is a high-quality partner enabling innovation in academia, hospitals and industry. It does this through its complementary pillars on coordination, open databases and software tools, and centre of excellence.","3","2023-11-13 22:23:58","2023-11-21 00:17:21","SIB" -"406","Biozentrum of the University of Basel","","biozentrum","logo/biozentrum.jpg","http://www.biozentrum.unibas.ch/","The Biozentrum of the University of Basel is one of the leading life sciences institutes in the world. The primary focus is basic molecular and biomedical research and teaching. It’s international and interdisciplinary research groups explore how molecules and cells create life, spanning the scale from atom to organism. Founded in 1971, the Biozentrum has been the birth place of many fundamental discoveries in biology and medicine, spawning several Nobel Laureates.","3","2023-11-13 22:24:00","2023-11-21 00:17:11","" -"407","National Institute of Aging","","nia","logo/nih.png","https://www.nia.nih.gov/","NIA leads a broad scientific effort to understand the nature of aging and to extend the healthy, active years of life. NIA is the primary federal agency supporting and conducting Alzheimer's disease research.","3","2023-11-16 22:06:31","2023-11-21 00:13:03","NIA" -"408","National Aeronautics and Space Administration","","nasa","logo/nasa.jpg","https://www.nasa.gov/","NASA explores the unknown in air and space, innovates for the benefit of humanity, and inspires the world through discovery.","1","2023-11-16 22:08:34","2023-11-21 00:17:31","NASA" -"414","CDC National Center for Injury Prevention and Control","","ncipc","logo/cdc-ncipc.jpg","https://www.cdc.gov/injury/","For 30 years, CDC’s National Center for Injury Prevention and Control (Injury Center) has been a leader in protecting Americans from injury and violence so that individuals, families, and communities can be safe, healthy, and thriving. We work proactively with our partners to track trends, conduct research, raise awareness, and implement prevention programs.","1","2023-12-06 07:22:56","2023-12-06 08:50:23","NCIPC" -"415","Centers for Disease Control and Prevention","","cdc","logo/cdc.jpg","https://www.cdc.gov/injury/","CDC is the nation’s leading science-based, data-driven, service organization that protects the public’s health. For more than 70 years, we’ve put science into action to help children stay healthy so they can grow and learn; to help families, businesses, and communities fight disease and stay strong; and to protect the public’s health.","2","2023-12-06 07:26:44","2023-12-06 08:15:44","CDC" -"416","United States Consumer Product Safety Commission","","cpsc","logo/cpsc.jpg","https://www.cpsc.gov/","CPSC works to save lives and keep families safe by reducing the unreasonable risk of injuries and deaths associated with consumer products and fulfilling its vision to be the recognized global leader in consumer product safety. CPSC does this by: 1) Issuing and enforcing mandatory standards or banning consumer products if no feasible standard would adequately protect the public; 2) Obtaining the recall of products and arranging for a repair, replacement or refund for recalled products; 3) Researching potential product hazards; 4) Developing voluntary standards with standards organizations, manufacturers and businesses; 5) Informing and educating consumers directly and through traditional, online, and social media and by working with foreign, state and local governments and private organizations; and 6) Educating manufacturers worldwide about our regulations, supply chain integrity and development of safe products.","1","2023-12-06 07:29:21","2023-12-06 07:33:21","CPSC" -"417","VisioMel","","visiomel","","https://www.sfpathol.org/actions-data-challenge-2022-23-francais.html","VisioMel began in 2021 when the French Society of Pathology, the French Society of Dermatology, the French Cutaneous Cancers Group, and the National Professional Council of Pathologists decided to build a challenge using clinical variables from a national database on melanoma (RIC-Mel).","1","2023-12-06 07:39:45","2023-12-06 07:41:13","" -"418","Health Data Hub","","hdh","logo/hdh.png","https://www.health-data-hub.fr/","Health data can be useful to improve the health system, making it more efficient, more personalized and more humanistic. Every citizen deserves it! It is through the processing and cross-referencing of a large volume of quality data that the most impactful research can be carried out: improving the screening and diagnosis of a disease, analyzing the side effects of treatments, developing trials. clinics... We offer a set of services to support the players who contribute to finding tomorrow's solutions to improve the health of citizens: supporting project leaders, building and operating a technological platform to offer them the best tools, bringing together and formatting the data with the greatest potential for research.","2","2023-12-06 07:39:52","2023-12-06 07:43:28","HDH" -"419","Délégation ministérielle au Numérique en Santé","","dns","logo/dns.jpg","https://gnius.esante.gouv.fr/en/players/player-profiles/delegation-ministerielle-au-numerique-en-sante-dns","The Ministerial Delegation for eHealth (DNS) is responsible for steering all eHealth transformation projects. The DNS reports directly to the Minister of Health. It closely oversees the Agence du Numérique en Santé (""ANS""). To bring all the stakeholders on board, the major pillars of eHealth policy are debated by the eHealth Council. The delegation also seeks advice from an ethics unit to ensure that its actions are consistent with humanist values and to interface with European and international initiatives relating to eHealth. The technical doctrine of the eHealth roadmap and the associated architecture diagram are updated regularly.","1","2023-12-06 07:51:13","2023-12-06 07:51:13","DNS" -"420","French Society of Pathology","","sfp","logo/sfp.png","https://www.sfpathol.org/actions-data-challenge-2022-23-francais.html","The SFP brings together pathologists from all modes of practice. It is governed as an association under the law of 1901, recognized as being of public utility. Our goal is to promote pathological anatomy and cytology in all its aspects. The SFP is a partner of the ICCR (International Collaboration on Cancer Reporting)","1","2023-12-06 07:53:48","2023-12-06 08:01:20","SFP" -"421","Grand Défi","","grand-defi","logo/dns.jpg","https://www.gouvernement.fr/decouvrir-les-grands-defis","The Grand Challenges, chosen by the Innovation Council and financed to the tune of €120M per year by the Fund for Innovation and Industry (FII), aim to respond to societal challenges in strategic areas requiring the lifting technological barriers.","1","2023-12-06 08:01:20","2023-12-06 08:03:51","" -"422","CDC National Center for Health Statistics","","nchs","logo/cdc-nchs.jpg","https://www.cdc.gov/nchs/index.htm","NCHS provides timely and accurate health statistics for the United States.","1","2023-12-06 08:15:35","2023-12-06 08:50:27","NCHS" -"423","UCI Machine Learning Repository","","uci-machine-learning-repository","logo/uci-ml-repo.png","https://archive.ics.uci.edu/","The UCI Machine Learning Repository is a collection of databases, domain theories, and data generators that are used by the machine learning community for the empirical analysis of machine learning algorithms. The archive was created as an ftp archive in 1987 by UCI PhD student David Aha. Since that time, it has been widely used by students, educators, and researchers all over the world as a primary source of machine learning datasets.","2","2023-12-06 08:24:19","2023-12-06 08:27:58","" -"424","National Oceanic and Atmospheric Administration","","noaa","logo/noaa.jpg","https://www.noaa.gov/","National Oceanic and Atmospheric Administration (NOAA) is an agency that enriches life through science. Our reach goes from the surface of the sun to the depths of the ocean floor as we work to keep the public informed of the changing environment around them.","1","2023-12-06 08:31:23","2023-12-06 08:32:49","NOAA" -"425","U.S. Department of Commerce","","us-department-of-commerce","logo/us-dept-commerce.jpg","https://www.commerce.gov/","The Department of Commerce’s mission is to create the conditions for economic growth and opportunity for all communities.","1","2023-12-06 08:33:26","2023-12-06 08:34:14","" -"426","AARP Foundation","","aarp-foundation","logo/aarp.png","https://www.aarp.org/aarp-foundation/","AARP Foundation creates and advances effective solutions to reduce poverty for and with older adults. In 2022, the people AARP Foundation served received more than $726 million in income, benefits, refunds, and credits. We fought systemic injustice, and we helped older adults with low income seize opportunities to re-enter the workforce, bolster their budgets, give back to their communities, and recover from disasters. But we didn’t do it alone. Our donors, partners, volunteers, board, and staff were united in a single purpose: to ensure that vulnerable older adults could secure the essentials. Together, we made a difference.","1","2023-12-06 08:38:27","2023-12-06 08:40:04","" -"427","Planned Parenthood Federation of America","","ppfa","logo/ppfa.jpg","https://www.plannedparenthood.org/","Planned Parenthood is a trusted health care provider, an informed educator, a passionate advocate, and a global partner helping similar organizations around the world. Planned Parenthood delivers vital reproductive health care, sex education, and information to millions of people worldwide.","1","2023-12-06 08:47:14","2023-12-06 08:48:09","PPFA" -"428","CDC National Survey of Family Growth","","nsfg","logo/cdc-nchs.jpg","https://www.cdc.gov/nchs/nsfg/index.htm?CDC_AA_refVal=https%3A%2F%2Fwww.cdc.gov%2Fnchs%2Fnsfg.htm","The National Survey of Family Growth (NSFG) gathers information on pregnancy and births, marriage and cohabitation, infertility, use of contraception, family life, and general and reproductive health. The survey results are used by the U.S. Department of Health and Human Services and others to plan health services and health education programs, and to do statistical studies of families, fertility, and health.","1","2023-12-06 08:49:39","2023-12-06 08:51:01","NSFG" -"429","altLabs","","altlabs","logo/altlabs.jpg","https://altlabs.tech/","altLabs is a research non-profit institution focused on the development and advancement of safety-promoting technologies. We collaborate with world-class researchers across diverse scientific fields to prioritize thoughtful solutions with long-term positive impact on a global scale. In a nutshell, we’re working to make the world a safer place.","1","2023-12-06 08:56:57","2023-12-06 08:59:34","" -"430","iGEM","","igem","logo/igem.jpg","https://igem.org/","iGEM educates the workforce and the leaders of the Synthetic Biology industry. The iGEM Foundation is an independent, non-profit organization dedicated to the advancement of synthetic biology, education and competition, and the development of an open, collaborative, and cooperative community.","1","2023-12-06 08:58:34","2023-12-06 08:59:36","" +"id","name","login","avatar_url","website_url","description","challenge_count","created_at","updated_at","acronym" +"1","Dialogue on Reverse Engineering Assessment and Methods","dream","logo/dream.png","https://dreamchallenges.org","DREAM Challenges use crowd-sourcing to solve complex biomedical research questions. Together, we share a vision to enable individuals and groups to collaborate openly so that the “wisdom of the crowd” provides the greatest impact on science and human health.","71","2023-08-04 07:33:09","2023-11-21 01:18:41","DREAM" +"3","Critical Assessment of protein Function Annotation","cafa","logo/cafa.png","https://www.biofunctionprediction.org/cafa/","The Critical Assessment of protein Function Annotation algorithms (CAFA) is an experiment designed to assess the performance of computational methods dedicated to predicting protein function, often using a time challenge. Briefly, CAFA organizers provide a large number of unannotated or incompletely annotated protein sequences. The predictors then predict the function of these proteins by associating them with Gene Ontology terms or Human Phenoytpe Ontology terms. Following the prediction deadline, there is a wait period of several months during which some proteins whose functions were unknown will receive experimental verification. Those proteins constitute the benchmark set, against which the methods are tested. Other data sources include experiments by wet lab collaborators and biocuration dedicated to CAFA.","2","2023-06-23 00:00:00","2023-10-20 18:39:12","CAFA" +"4","Critical Assessment of Genome Interpretation","cagi","logo/cagi.png","https://genomeinterpretation.org/challenges.html","The Critical Assessment of Genome Interpretation (CAGI) is a community experiment to objectively assess computational methods for predicting the phenotypic impacts of genomic variation. CAGI participants are provided genetic variants and make predictions of resulting phenotypes. These predictions are evaluated against experimental data by independent assessors.","26","2023-06-23 00:00:00","2023-11-18 03:49:35","CAGI" +"7","Critical Assessment of Metagenome Interpretation","cami","logo/cami.png","https://data.cami-challenge.org/","CAMI, the initiative for the “Critical Assessment of Metagenome Interpretation” aims to evaluate methods in metagenomics independently, comprehensively and without bias. The initiative supplies users with exhaustive quantitative data about the performance of methods in all relevant scenarios. It therefore guides users in the selection and application of methods and in their proper interpretation. Furthermore it provides valuable information to developers, allowing them to identify promising directions for their future work. CAMI organized in 2015 the first community driven benchmarking challenge in metagenomics. For the second CAMI challenge (starting on January 16th, 2019) visit https://data.cami-challenge.org","2","2023-06-23 00:00:00","2023-07-26 20:13:21","CAMI" +"9","Critical Assessment of protein Structure Prediction","casp","logo/casp.png","https://predictioncenter.org/","Our goal is to help advance the methods of identifying protein structure from sequence. The Center has been organized to provide the means of objective testing of these methods via the process of blind prediction. The Critical Assessment of protein Structure Prediction (CASP) experiments aim at establishing the current state of the art in protein structure prediction, identifying what progress has been made, and highlighting where future effort may be most productively focused.","3","2023-06-23 00:00:00","2023-10-20 18:39:35","CASP" +"12","Medical Image Computing and Computer Assisted Intervention Society","miccai","logo/miccai.png","http://www.miccai.org/special-interest-groups/challenges/miccai-registered-challenges/","The Medical Image Computing and Computer Assisted Intervention Society (the MICCAI Society) is dedicated to the promotion, preservation and facilitation of research, education and practice in the field of medical image computing and computer assisted medical interventions including biomedical imaging and medical robotics. The Society achieves this aim through the organization and operation of annual high quality international conferences, workshops, tutorials and publications that promote and foster the exchange and dissemination of advanced knowledge, expertise and experience in the field produced by leading institutions and outstanding scientists, physicians and educators around the world. The MICCAI Society is committed to maintaining high academic standards and independence from any personal, political or commercial interests.","15","2023-06-23 00:00:00","2023-07-26 20:13:24","MICCAI" +"13","precisionFDA","pfda","logo/precisionfda.png","https://precision.fda.gov/challenges","A secure, collaborative, high-performance computing platform that builds a community of experts around the analysis of biological datasets in order to advance precision medicine.","18","2023-06-23 00:00:00","2023-07-26 20:13:25","pFDA" +"15","National Institutes of Health","nih","logo/nih.png","https://www.nih.gov/","The National Institutes of Health (NIH), a part of the U.S. Department of Health and Human Services, is the nation's medical research agency — making important discoveries that improve health and save lives.","11","2023-06-23 00:00:00","2023-10-14 06:44:12","NIH" +"16","Allen Institute","allen-institute","logo/allen-institute.svg","https://alleninstitute.org/","The Allen Institute is an independent nonprofit bioscience research institute aimed at unlocking the mysteries of human biology through foundational science that fuels the discovery of new treatments and cures.","2","2023-06-23 00:00:00","2023-07-26 20:13:27","" +"17","ALS Therapy Alliance","ata","logo/als-therapy-alliance.png","https://alstherapyalliance.org/","For over a decade, researchers and scientists have been relying on the ALS Therapy Alliance's expertise and funding to advance their studies of amyotrophic lateral sclerosis (ALS), or Lou Gehrig's disease. 2015 marks the 14th year of our annual Breakthrough ALS fundraising campaign (formerly known as Researching a Cure). The ALS Therapy Alliance's ongoing grant award process is overseen by the organization's board of award-winning researchers and scientists, as well as corporate executives and individuals who strive to learn more about the neurodegenerative disease, its cause and possible cure.","1","2023-06-23 00:00:00","2023-07-26 20:13:28","ATA" +"18","Alzheimer's Disease Neuroimaging Initiative","adni","logo/adni.jpg","http://adni.loni.usc.edu/","The Alzheimer's Disease Neuroimaging Initiative (ADNI) unites researchers with study data as they work to define the progression of Alzheimer's disease (AD). ADNI researchers collect, validate and utilize data, including MRI and PET images, genetics, cognitive tests, CSF and blood biomarkers as predictors of the disease. Study resources and data from the North American ADNI study are available through this website, including Alzheimer's disease patients, mild cognitive impairment subjects, and elderly controls.","2","2023-06-23 00:00:00","2023-07-26 20:13:29","ADNI" +"19","Alzheimer's Research UK","alzheimers-research-uk","logo/alzheimers-research-uk.jpg","https://www.alzheimersresearchuk.org/","Without effective treatments, one in three children born today will die with dementia. Today, there are no dementia survivors but research can change this. Alzheimer's Research UK is the UK's leading dementia research charity, dedicated to causes, diagnosis, prevention, treatment and cure. Backed by our passionate scientists and supporters, we're challenging the way people think about dementia, uniting the big thinkers in the field and funding the innovative science that will deliver a cure.","2","2023-06-23 00:00:00","2023-07-26 20:13:31","" +"20","Amazon Web Services","aws","logo/aws.svg","https://aws.amazon.com/","Whether you're looking for compute power, database storage, content delivery, or other functionality, AWS has the services to help you build sophisticated applications with increased flexibility, scalability and reliability","1","2023-06-23 00:00:00","2023-07-26 20:13:31","AWS" +"21","American Joint Committee on Cancer","ajcc","","https://www.facs.org/quality-programs/cancer/ajcc","Validating science, improving patient care.","1","2023-06-23 00:00:00","2023-07-26 20:13:32","AJCC" +"22","APOLLO network","apollo","logo/apollo.png","https://proteomics.cancer.gov/programs/apollo-network","The Applied Proteogenomics OrganizationaL Learning and Outcomes (APOLLO) network is a collaboration between NCI, the Department of Defense (DoD), and the Department of Veterans Affairs (VA) to incorporate proteogenomics into patient care as a way of looking beyond the genome, to the activity and expression of the proteins that the genome encodes. The emerging field of proteogenomics aims to better predict how patients will respond to therapy by screening their tumors for both genetic abnormalities and protein information, an approach that has been made possible in recent years due to advances in proteomic technology.","1","2023-06-23 00:00:00","2023-07-26 20:13:33","" +"23","Apple Health","apple-health","logo/wa-healthcare-authority.jpg","https://www.hca.wa.gov/","HCA is the largest purchaser of health care in the state. We lead the effort on transforming health care through programs and initiatives that range from the administration of Apple Health (Medicaid) and behavioral health activities to developing models for value-based purchasing and health technology assessments. We use data to inform our decisions and work in collaboration with local communities to ensure that Washington residents have access to better health care at a lower cost.","14","2023-06-23 00:00:00","2023-07-26 20:13:33","" +"24","Arthritis Foundation","arthritis-foundation","logo/arthritis-foundation.png","https://www.arthritis.org/","Live your best life with the help of a compassionate and caring community. Get empowering information and make meaningful connections. Online and in person, we are all working together to promote life-changing resources and research, push for change and create community connections that welcome, inform and uplift. This is what makes our community of millions thrive — and why we are all Champions of Yes.","1","2023-06-23 00:00:00","2023-07-26 20:13:35","" +"25","Arthritis Internet Registry","arthritis-internet-registry","","","This organization may no longer exist, has rebranded, or has been merged under another organization.","1","2023-06-23 00:00:00","2023-11-20 18:43:42","" +"26","AstraZeneca","astrazeneca","logo/astrazeneca.png","https://www.astrazeneca.com/","We are a global, science-led, patient-focused pharmaceutical company. We are dedicated to transforming the future of healthcare by unlocking the power of what science can do for people, society and the planet.","2","2023-06-23 00:00:00","2023-07-26 20:13:36","" +"27","Autodesk Research","autodesk","logo/autodesk-research.png","https://www.research.autodesk.com/","Autodesk is changing how the world is designed and made. At Autodesk Research, we advance this mission by exploring new possibilities where others see roadblocks. With a diverse team of scientists and industry experts, we conduct industrial research that helps customers design and make a better world for all.","1","2023-06-23 00:00:00","2023-07-26 20:13:36","" +"28","BC Cancer Research Centre","bccrc","logo/bccrc.jpg","https://www.bccrc.ca/","BC Cancer Research strives to improve the lives of patients through the integration of basic biomedical research, genomics, clinical trials, health services research, cancer surveillance, population health, and the development of innovative new technology, programs, and interventions. Organized through departments and programs with various themes, BC Cancer supports groundbreaking cancer research and personalized care approaches through world-class facilities and platforms including genomics, bioinformatics, imaging, drug development and tissue banking.","1","2023-06-23 00:00:00","2023-07-26 20:13:36","BCCRC" +"29","Bellvitge Institute for Biomedical Research","idibell","logo/idibell.jpg","https://idibell.cat/en/the-institute/","The Bellvitge Biomedical Research Institute (IDIBELL) is a research center in biomedicine promoted by the Bellvitge University Hospital and the Viladecans Hospital, both from the Catalan Health Institute, the Catalan Institute of Oncology, University of Barcelona and L'Hospitalet de Llobregat city council. In 2017, the Center for Regenerative Medicine of Barcelona (CMR[B]), now part of IDIBELL, launched the Program for Advancing the Clinical Translation of Regenerative Medicine of Catalonia (P-CMR[C]) together with IDIBELL.","1","2023-06-23 00:00:00","2023-07-26 20:13:37","IDIBELL" +"30","Berlin Institute of Health","bih","logo/bih.jpg","https://www.bihealth.org/en/","The mission of the BIH is medical translation: The BIH aims to translate findings from biomedical research into new approaches for personalised prediction, prevention and therapy and, conversely, to develop new research approaches from clinical observations.","1","2023-06-23 00:00:00","2023-10-14 06:42:38","BIH" +"31","Bill and Melinda Gates Foundation","gates-foundation","logo/gates-foundation.jpg","https://www.gatesfoundation.org/","Our mission is to create a world where every person has the opportunity to live a healthy, productive life.","1","2023-06-23 00:00:00","2023-07-26 20:13:40","" +"32","Biogen","biogen","logo/biogen.png","https://www.biogen.com/en_us/home.html","Biogen is a leading global biotechnology company that pioneers science and drives innovations for complex and devastating diseases. Biogen is advancing a pipeline of potential therapies across neurology, neuropsychiatry, specialized immunology and rare disease and remains acutely focused on its purpose of serving humanity through science while advancing a healthier, more sustainable and equitable world. Founded in 1978, Biogen has pioneered multiple breakthrough innovations including a broad portfolio of medicines to treat multiple sclerosis, the first approved treatment for spinal muscular atrophy, and two co-developed treatments to address a defining pathology of Alzheimer's disease.","1","2023-06-23 00:00:00","2023-07-26 20:13:42","" +"33","BioMarin Pharmaceutical Inc.","biomarin","logo/biomarin.jpg","https://www.biomarin.com/","Over two decades ago when we first opened our doors, we focused on giving much-needed attention to the underserved communities of those with rare diseases. These rare disease communities mostly affected children and were often ignored. At the time, BioMarin developed the only treatments for these life-altering conditions, giving hope to patients and families. Throughout our history, we've worked tirelessly to make a difference by pursuing bold science while respecting, educating, and connecting with patients. Through our expertise in genetics and molecular biology, we have been able to develop targeted therapies that address the root cause of the exact conditions we seek to treat. Our discoveries have led us to countless breakthroughs, best-in-class treatments and many ‘firsts' in the category. We are grateful to able to better the lives of those struggling with genetic diseases.","3","2023-06-23 00:00:00","2023-07-26 20:13:44","" +"34","Booz Allen Hamilton","booz-allen","logo/booz-allen.jpg","https://www.boozallen.com/","Booz Allen Hamilton has been at the forefront of strategy and technology for more than 100 years. Today, the firm provides management and technology consulting and engineering services to leading Fortune 500 corporations, governments, and not-for-profits across the globe. Booz Allen partners with public and private sector clients to solve their most difficult challenges through a combination of consulting, analytics, mission operations, technology, systems delivery, cybersecurity, engineering, and innovation expertise. \n\nWith international headquarters in McLean, Virginia, the firm employs more than 22,600 people globally and had revenue of $5.41 billion for the 12 months ended March 31, 2016.\n\nBooz Allen brings its pioneering work in advanced analytics—and the industry-leading expertise of its more than 600-member data science team—to transform our clients' data into actions that keep them competitive in today's data-driven economy. To learn about Booz Allen's data science ca...","13","2023-06-23 00:00:00","2023-07-26 20:13:45","" +"36","Breast Cancer Surveillance Consortium","bcsc","logo/bcsc.jpeg","https://www.bcsc-research.org/","The Breast Cancer Surveillance Consortium (BCSC) is a collaborative network of six active breast imaging registries and two historic registries focused on research to assess and improve the delivery and quality of breast cancer screening and related outcomes in the United States. The registries perform annual linkages to tumor and pathology registries in their geographic region and are supported by a central Statistical Coordinating Center.","1","2023-06-23 00:00:00","2023-07-26 20:13:47","BCSC" +"37","Brigham and Women's Hospital","bwh","logo/bwh.png","https://www.brighamandwomens.org/","Brigham and Women's Hospital is a world-class academic medical center based in Boston, Massachusetts. The Brigham serves patients from New England, across the United States and from 120 countries around the world. A major teaching hospital of Harvard Medical School, Brigham and Women's Hospital has a legacy of clinical excellence that continues to grow year after year.","1","2023-06-23 00:00:00","2023-07-26 20:13:47","BWH" +"38","Brigham Young University","byu","logo/byu.jpg","https://www.byu.edu/","At BYU, helping students to develop their full divine potential is central to both our teaching and our scholarship. As the flagship higher education institution of The Church of Jesus Christ of Latter-day Saints, BYU strives to emit a unique light for the benefit of the world—a light that will enable BYU to be counted among the exceptional universities in the world and an essential example for the world.","1","2023-06-23 00:00:00","2023-07-26 20:13:48","BYU" +"39","BrightFocus Foundation","brightfocus-foundation","logo/bright-focus.jpg","https://www.brightfocus.org/","BrightFocus funds exceptional scientific research worldwide to defeat Alzheimer's disease, macular degeneration, and glaucoma and provides expert information on these heartbreaking diseases.","1","2023-06-23 00:00:00","2023-07-26 20:13:49","" +"40","Bristol Myers Squibb","bms","logo/bms.jpg","https://www.bms.com/","At Bristol Myers Squibb, we work every day to transform patients' lives through science. We combine the agility of a biotech with the reach and resources of an established pharmaceutical company to create a global leading biopharma company powered by talented individuals who drive scientific innovation. We have the brightest people in the industry and believe that their diverse experiences and perspectives help to bring out our best ideas, drive innovation and achieve transformative business results.","2","2023-06-23 00:00:00","2023-07-26 20:13:50","BMS" +"41","Broad Institute","broad","logo/broad.jpg","https://www.broadinstitute.org/","We seek to better understand the roots of disease and narrow the gap between new biological insights and impact for patients.","5","2023-06-23 00:00:00","2023-07-26 20:13:51","" +"42","Brown University","brown","logo/brown.jpg","https://www.brown.edu/","Founded in 1764, Brown is a nonprofit leading research university, home to world-renowned faculty, and also an innovative educational institution where the curiosity, creativity and intellectual joy of students drives academic excellence. The spirit of the undergraduate Open Curriculum infuses every aspect of the University. Brown is a place where rigorous scholarship, complex problem-solving and service to the public good are defined by intense collaboration, intellectual discovery and working in ways that transcend traditional boundaries. As a private, nonprofit institution, the University advances its mission through support from a community invested in Brown's commitment to advance knowledge and make a positive difference locally and globally.","1","2023-06-23 00:00:00","2023-07-26 20:13:52","" +"43","California Institute of Technology","caltech","logo/caltech.jpg","https://www.caltech.edu/","Caltech is a world-renowned science and engineering institute that marshals some of the world's brightest minds and most innovative tools to address fundamental scientific questions and pressing societal challenges.","2","2023-06-23 00:00:00","2023-07-26 20:13:52","" +"44","Cancer Imaging Archive","tcia","logo/tcia.jpeg","https://www.cancerimagingarchive.net/","The Cancer Imaging Archive (TCIA) is a service which de-identifies and hosts a large publicly available archive of medical images of cancer. TCIA is funded by the Cancer Imaging Program (CIP), a part of the United States National Cancer Institute (NCI), and is managed by the Frederick National Laboratory for Cancer Research (FNLCR).","1","2023-06-23 00:00:00","2023-07-26 20:13:53","TCIA" +"45","Cancer Research UK","cancer-research-uk","logo/cancer-research-uk.jpg","https://www.cancerresearchuk.org/","Cancer Research UK was formed 20 years ago, in 2002. However, our history goes back much further, to 1902, with the founding of the Imperial Cancer Research Fund. Thanks to supporters like you, our pioneering work into how to prevent, diagnose and treat cancer has benefitted millions of lives over the past 120 years. Find out more about how our research has already made a difference to patients and what we are funding right now.","1","2023-06-23 00:00:00","2023-07-26 20:13:54","" +"46","Cancer Target Discovery and Development","ctd2","logo/ctd2.png","https://ocg.cancer.gov/programs/ctd2","The Cancer Target Discovery and Development (CTD2) Network, also known as C-T-D-Squared, is a functional genomics initiative that bridges the gap between genomics and development of effective therapeutics. The Network aims to understand tumor development, heterogeneity, drug resistance, and metastasis to develop optimal combinations of chemotherapy with immunotherapy.","4","2023-06-23 00:00:00","2023-07-26 20:13:55","CTD2" +"47","Celgene","celgene","logo/celgene.jpg","https://www.celgene.com","This organization may no longer exist, has rebranded, or has been merged under another organization.","3","2023-06-23 00:00:00","2023-08-08 17:58:26","" +"48","Center for Research Computing","crc","logo/crc.jpeg","https://crc.nd.edu/","The Center for Research Computing (CRC) at University of Notre Dame is an innovative and multidisciplinary research environment that supports collaboration to facilitate multidisciplinary discoveries through advanced computation, software engineering, artificial intelligence, and other digital research tools. The Center enhances the University's innovative applications of cyberinfrastructure, provides support for interdisciplinary research and education, and conducts computational research.","1","2023-06-23 00:00:00","2023-07-26 20:13:57","CRC" +"49","Cincinnati Children's Hospital Medical Center","cchmc","logo/cchmc.jpg","https://www.cincinnatichildrens.org/","Cincinnati Children's, a nonprofit academic medical center established in 1883, is one of the oldest and most distinguished pediatric hospitals in the United States.","2","2023-06-23 00:00:00","2023-07-26 20:13:57","CCHMC" +"50","Climb 4 Kidney Cancer","c4kc","logo/c4kc.jpg","https://climb4kc.org/","Climb 4 Kidney Cancer is a nonprofit organization that aims to raise money for kidney cancer research while bringing people together through climbing. We are physicians, scientists, survivors, and loved ones who share a passion for climbing and a passion for improving the lives of those affected by kidney cancer.","1","2023-06-23 00:00:00","2023-07-26 20:13:58","C4KC" +"51","Clinical Proteomic Tumor Analysis Consortium","cptac","logo/cptac.png","https://proteomics.cancer.gov/programs/cptac","The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) is a national effort to accelerate the understanding of the molecular basis of cancer through the application of large-scale proteome and genome analysis, or proteogenomics.","1","2023-06-23 00:00:00","2023-07-26 20:13:58","CPTAC" +"52","Columbia University","columbia","logo/columbia.jpg","https://www.columbia.edu/","Columbia University is one of the world's most important centers of research and at the same time a distinctive and distinguished learning environment for undergraduates and graduate students in many scholarly and professional fields. The University recognizes the importance of its location in New York City and seeks to link its research and teaching to the vast resources of a great metropolis. It seeks to attract a diverse and international faculty, staff, and student body, to support research and teaching on global issues, and to create academic relationships with many countries and regions. It expects all areas of the University to advance knowledge and learning at the highest level and to convey the products of its efforts to the world.","5","2023-06-23 00:00:00","2023-07-26 20:13:59","" +"53","Conceptant","conceptant","logo/conceptant.webp","https://www.conceptant.com/","We want to improve humanity and the world through technology, plain and simple. Tech has so much promise to improve lives, but we felt it was constantly overshadowed by stuffy boardrooms and corporate red tape. Which is why Conceptant takes a different path, one we created. We go against the grain using creative techniques to develop cutting edge solutions while avoiding the pot holes of slow stuffy suits.","1","2023-06-23 00:00:00","2023-07-26 20:14:00","" +"54","Consejo Superior de Investigaciones Cientificas","csic","logo/csic.jpg","https://www.csic.es/","The Higher Council for Scientific Research (CSIC) is a State Agency for scientific research and technological development, with differentiated legal personality, its own assets and treasury, functional and management autonomy, full legal capacity to act and of indefinite duration (art. 1 Statute).","1","2023-06-23 00:00:00","2023-07-26 20:14:00","CSIC" +"55","CorEvitas","corevitas","logo/corevitas.jpeg","https://www.corevitas.com/","CorEvitas is a science-led, data intelligence company that provides the life sciences industry with the objective data and clinical insights needed to demonstrate the real-world safety, effectiveness, and patient experience of therapeutics in the post-approval setting","1","2023-06-23 00:00:00","2023-07-26 20:14:02","" +"56","Corrona","corrona","logo/corrona.jpeg","https://www.corrona.org","This organization may no longer exist, has re-branded, or has been merged under another organization.","1","2023-06-23 00:00:00","2023-11-20 22:08:22","" +"57","Covert Lab","covert-lab","","https://www.covert.stanford.edu/","We're a scrappy bunch of scientists who like to do cutting-edge research with the latest technology (often home-made)! Our primary biological focus is in host-pathogen interactions, most particularly in terms of the innate immune system, and our technological foci are whole-cell modeling and live-cell imaging, as shown above. We're always looking for top talent - if you're a budding, intellectually ambidextrous scientist with a creative streak and an aptitude for team play, this could be the place for you!","1","2023-06-23 00:00:00","2023-10-16 21:26:03","" +"58","Dana-Farber Cancer Institute","dfci","logo/dfci.png","https://www.dana-farber.org/","Since its founding in 1947, Dana-Farber Cancer Institute in Boston, Massachusetts has been committed to providing adults and children with cancer with the best treatment available today while developing tomorrow's cures through cutting-edge research. Read about our history, our breakthroughs, and the resources that help us support the health of our neighborhoods and communities.","5","2023-06-23 00:00:00","2023-07-26 20:14:04","DFCI" +"59","Defense Advanced Research Projects Agency","darpa","logo/darpa.jpg","https://www.darpa.mil/","For sixty years, DARPA has held to a singular and enduring mission: to make pivotal investments in breakthrough technologies for national security. The genesis of that mission and of DARPA itself dates to the launch of Sputnik in 1957, and a commitment by the United States that, from that time forward, it would be the initiator and not the victim of strategic technological surprises. Working with innovators inside and outside of government, DARPA has repeatedly delivered on that mission, transforming revolutionary concepts and even seeming impossibilities into practical capabilities. The ultimate results have included not only game-changing military capabilities such as precision weapons and stealth technology, but also such icons of modern civilian society such as the Internet, automated voice recognition and language translation, and Global Positioning System receivers small enough to embed in myriad consumer devices.","2","2023-06-23 00:00:00","2023-10-16 21:26:51","DARPA" +"60","Department of Energy","doe","logo/doe.jpg","https://www.energy.gov/","The mission of the Energy Department is to ensure America's security and prosperity by addressing its energy, environmental and nuclear challenges through transformative science and technology solutions.","1","2023-06-23 00:00:00","2023-07-26 20:14:06","DOE" +"61","Diagnosticos da America SA","dasa","logo/dasa.jpeg","https://dasa.com.br/","We are Dasa. A new model that expands and integrates health care throughout life. We have brought together the largest diagnostic medicine network, a robust hospital group and the best care management company, so that nothing is missing and full care is provided. We connect spaces, technologies, knowledge, multiply specialties and become a complete company, alive and moving, always evolving. We develop the most innovative technology and health with new digital solutions that we seek in the market, via open innovation and in Dasa startups. Today we are more than 40,000 professionals ready to meet‌ ‌all‌ ‌‌‌your‌ health needs. We are for you. A comprehensive health network with a ‌grand purpose, which is to make sure you experience the best of your health every day.","1","2023-06-23 00:00:00","2023-07-26 20:14:06","DASA" +"62","DNAnexus","dnanexus","logo/dnanexus.png","https://www.dnanexus.com/","DNAnexus(R) has built the world's most secure cloud platform and global network for scientific collaboration and accelerated discovery. We embrace challenges and partnership to tackle the world's most exciting opportunities in human health.","11","2023-06-23 00:00:00","2023-07-26 20:14:08","" +"63","Dockstore","dockstore","logo/dockstore.jpg","https://dockstore.org/","Dockstore is a free and open source platform for sharing reusable and scalable analytical tools and workflows. It's developed by the Cancer Genome Collaboratory and used by the GA4GH.","1","2023-06-23 00:00:00","2023-07-26 20:14:08","" +"64","Duke University","duke","logo/duke.jpg","https://duke.edu/","The mission of Duke University is to provide a superior liberal education to undergraduate students, attending not only to their intellectual growth but also to their development as adults committed to high ethical standards and full participation as leaders in their communities; to prepare future members of the learned professions for lives of skilled and ethical service by providing excellent graduate and professional education; to advance the frontiers of knowledge and contribute boldly to the international community of scholarship; to promote an intellectual environment built on a commitment to free and open inquiry; to help those who suffer, cure disease, and promote health, through sophisticated medical research and thoughtful patient care; to provide wide ranging educational opportunities, on and beyond our campuses, for traditional students, active professionals and life-long learners using the power of information technologies; and to promote a deep appreciation for the r...","3","2023-06-23 00:00:00","2023-07-26 20:14:09","" +"65","Early Signal, LLC","easi","","http://www.earlysignal.org","This organization may no longer exist, has rebranded, or has been merged under another organization.","1","2023-06-23 00:00:00","2023-11-20 18:47:19","EaSi" +"66","Eck Institute for Global Health","eigh","logo/eigh.jpg","https://globalhealth.nd.edu/","The University of Notre Dame's Eck Institute for Global Health (EIGH) serves as a university-wide enterprise that recognizes health as a fundamental human right and works to promote research, training, and service to advance health standards and reduce health disparities for all. The EIGH brings together multidisciplinary teams to understand and address health challenges that disproportionately affect the poor and to train the next generation of global health leaders.","1","2023-06-23 00:00:00","2023-07-26 20:14:10","EIGH" +"67","Eli Lilly and Company","lilly","logo/lilly.png","https://www.lilly.com/","Lilly was founded in 1876 by Colonel Eli Lilly, a man committed to creating high-quality medicines that met real needs in an era of unreliable elixirs peddled by questionable characters. His charge to the generations of employees who have followed was this: ""Take what you find here and make it better and better."" More than 145 years later, we remain committed to his vision through every aspect of our business and the people we serve starting with those who take our medicines, and extending to health care professionals, employees and the communities in which we live.","3","2023-06-23 00:00:00","2023-10-16 21:27:12","" +"68","Elixir","elixir","logo/elixir.jpg","https://www.elixirsolutions.com/","Elixir is a pharmacy benefits and services company with the scale, flexibility and expertise to help our clients achieve their unique business goals. We have been purposely built and own all the assets needed to optimize the full pharmacy care experience, including: a) An industry leading adjudication platform, offering flexibility, efficiency and data privacy protection; b) Accredited mail and specialty pharmacies, creating an exceptional member experience, waste reduction and cost savings; c) Population health services through our sister company, Health Dialog; and d) Prescription discount programs for uninsured and under-insured and Medicare Part D plans for individuals, associations and groups.","1","2023-06-23 00:00:00","2023-10-16 21:27:25","" +"69","Encyclopedia of DNA Elements Data Coordinating Center","encode","logo/encode.png","https://www.encodeproject.org/","The ENCODE Data Coordination Center (DCC)'s primary task is to curate, uniformly process and validate the data generated and submitted by ENCODE Consortium members in preparation for release to the scientific community.","1","2023-06-23 00:00:00","2023-07-26 20:14:13","ENCODE" +"70","ENIGMA Consortium","enigma","logo/enigma.jpg","http://enigma.ini.usc.edu/","The ENIGMA Consortium brings together researchers in imaging genomics to understand brain structure, function, and disease, based on brain imaging and genetic data. We welcome brain researchers, imagers, geneticists, methods developers, and others interested in cracking the neuro-genetic code!","1","2023-06-23 00:00:00","2023-07-26 20:14:13","ENIGMA" +"71","ETH Zurich","eth","logo/eth.jpg","https://ethz.ch/en.html","Freedom and individual responsibility, entrepreneurial spirit and open-​​mindedness: ETH Zurich stands on a bedrock of true Swiss values.","2","2023-06-23 00:00:00","2023-10-16 21:27:44","ETH" +"72","Eunice Kennedy Shriver National Institute","nichd","logo/nichd.jpg","https://www.nichd.nih.gov/","NICHD was founded in 1962 to investigate human development throughout the entire life process, with a focus on understanding disabilities and important events that occur during pregnancy. Since then, research conducted and funded by NICHD has helped save lives, improve wellbeing, and reduce societal costs associated with illness and disability. NICHD's mission is to lead research and training to understand human development, improve reproductive health, enhance the lives of children and adolescents, and optimize abilities for all.","1","2023-06-23 00:00:00","2023-07-26 20:14:15","NICHD" +"73","European Bioinformatics Institute","embl-ebi","logo/embl-ebi.jpg","https://www.ebi.ac.uk/","At EMBL's European Bioinformatics Institute (EMBL-EBI), we help scientists realise the potential of big data in biology, exploiting complex information to make discoveries that benefit humankind.","8","2023-06-23 00:00:00","2023-07-26 20:14:15","EMBL-EBI" +"74","European Medicines Agency","ema","logo/ema.jpg","https://www.ema.europa.eu/en","The mission of the European Medicines Agency (EMA) is to foster scientific excellence in the evaluation and supervision of medicines, for the benefit of public and animal health in the European Union (EU).","1","2023-06-23 00:00:00","2023-07-26 20:14:16","EMA" +"75","European Union","eu","logo/eu.png","https://europa.eu/european-union/index_en","The common principles and values that underlie life in the EU: freedom, democracy, equality and the rule of law, promoting peace and stability.","2","2023-06-23 00:00:00","2023-10-16 21:27:57","EU" +"76","Evidation Health","evidation","logo/evidation.png","https://evidation.com/","We believe everyday health data is the most compelling force in medicine—because under rigorous study, it's proving to be a new and exceptionally powerful lens on health. These novel discoveries—emanating from data generated and controlled by individuals—can be turned into tools they use to take control of their health. By connecting our member community to research and innovation partners across the health ecosystem, we're creating a new platform for medical advancements and innovation.","1","2023-06-23 00:00:00","2023-07-26 20:14:17","" +"77","Fehling Instruments","fehling-instruments","logo/fehling-instruments.jpeg","https://www.fehling-instruments.de/en/","Fehling Instruments is a traditional family owned and family run company with more than thirty years of experience in the medical business. Fehling Instruments is constantly striving for excellence in function and economy of products. This objective is achieved by continuous innovation in materials, mechanics and design. Customer satisfaction is the prevailing goal of our business. Therefore, Fehling Instruments provides outstanding service in addition to quality products. Fehling Instruments develops, manufactures, and distributes surgical instruments, implants and single use products for use mainly in the OR. FI also provides all corresponding repair service. The most important target markets for Fehling Instruments are neuro surgery (spine and brain) and thoracic, cardiac and vascular surgery.","1","2023-06-23 00:00:00","2023-07-26 20:14:18","" +"78","Feinstein Institutes for Medical Research","feinstein-institute","logo/feinstein-institute.png","https://feinstein.northwell.edu/","The Feinstein Institutes for Medical Research is the home of research at Northwell Health. In conjunction with our partners in government, academia, industry and philanthropy, we strive to advance knowledge and make innovative therapies a reality. Our researchers work to transform the treatment of conditions like lupus, arthritis, sepsis, cancer, psychiatric illness and Alzheimer's disease. As the global headquarters of bioelectronic medicine, we're exploring ways to raise the standard of medical innovation and are using electronic medical devices to signal the body to heal itself.","1","2023-06-23 00:00:00","2023-07-26 20:14:19","" +"79","Francis Crick Institute","francis-crick-institute","logo/francis-crick-institute.jpeg","https://www.crick.ac.uk/","The Francis Crick Institute is a biomedical research institute working with organisations across academia, medicine and industry to make discoveries about how life works.","1","2023-06-23 00:00:00","2023-07-26 20:14:20","" +"80","Fred Hutchinson Cancer Research Center","fred-hutch","logo/fred-hutch.jpg","https://www.fredhutch.org/","Fred Hutchinson Cancer Center unites innovative research and compassionate care to prevent and eliminate cancer and infectious disease. We're driven by the urgency of our patients, the hope of our community and our passion for discovery to pursue scientific breakthroughs and healthier lives for every person in every community.","1","2023-06-23 00:00:00","2023-07-26 20:14:21","" +"81","Genome Canada","genome-canada","logo/genome-canada.png","https://www.genomecanada.ca/","Genome Canada is an independent, federally funded not-for-profit organization and a national leader for Canada's genomics ecosystem. Working in partnership, and across sectors, we invest in, and coordinate, genomics research, innovation, data and talent to generate solutions to today's biggest challenges.","3","2023-06-23 00:00:00","2023-07-26 20:14:21","" +"82","George Washington University","gwu","logo/gwu.jpg","https://www.gwu.edu/","Since our capital city's first days, people have traveled here for many reasons. They come to explore the past and to chart new futures. They come to ask questions and to seek expert answers. They come to start discourse and to remember in silence. They come to demand change and to be that change. They come to grow. They come to learn. They come to make history and join the ranks alongside many monumental GW alumni.","2","2023-06-23 00:00:00","2023-07-26 20:14:23","GWU" +"83","Georgetown University","georgetown","logo/georgetown.png","https://www.georgetown.edu/","We're a leading research university with a heart. Founded in the decade that the U.S. Constitution was signed, we're the nation's oldest Catholic and Jesuit university. Today we're a forward-looking, diverse community devoted to social justice, restless inquiry and respect for each person's individual needs and talents.","1","2023-06-23 00:00:00","2023-07-26 20:14:23","" +"84","German Cancer Research Center","dkfz","logo/dkfz.jpg","https://www.dkfz.de/en/index.html","More than 450,000 people are diagnosed with cancer each year in Germany. Cancer is a disease that poses enormous challenges to research, because every cancer is different and its course can vary immensely even from one patient to the next. To perform research into cancer is the task of the German Cancer Research Center (Deutsches Krebsforschungszentrum, DKFZ) according to its statutes. DKFZ is the largest biomedical research institute in Germany and a member of the Helmholtz Association of National Research Centers. In more than 100 divisions and research groups, our more than 3,000 employees, of which more than 1,200 are scientists, are investigating the mechanisms of cancer, are identifying cancer risk factors and are trying to find strategies to prevent people from getting cancer.They are developing novel approaches to make tumor diagnosis more precise and treatment of cancer patients more successful.","2","2023-06-23 00:00:00","2023-07-26 20:14:24","DKFZ" +"85","Global Alliance for Genomics and Health","ga4gh","logo/ga4gh.png","https://www.ga4gh.org/","The Global Alliance for Genomics and Health (GA4GH) is an international, nonprofit alliance formed in 2013 to accelerate the potential of research and medicine to advance human health. Bringing together 600+ leading organizations working in healthcare, research, patient advocacy, life science, and information technology, the GA4GH community is working together to create frameworks and standards to enable the responsible, voluntary, and secure sharing of genomic and health-related data. All of our work builds upon the Framework for Responsible Sharing of Genomic and Health-Related Data.","1","2023-06-23 00:00:00","2023-07-26 20:14:24","GA4GH" +"86","H. Lee Moffitt Cancer Center and Research Institute","moffitt","logo/moffitt.png","https://moffitt.org/","At Moffitt Cancer Center, we are working tirelessly in the areas of patient care, research and education to advance one step further in fighting this disease. We are committed to the health and safety of our patients and dedicated to providing expert cancer care.","1","2023-06-23 00:00:00","2023-07-26 20:14:25","" +"87","H3ABioNet","h3abionet","logo/h3abionet.png","https://h3abionet.org/","H3ABioNet is a Pan African Bioinformatics network comprising 28 Nodes distributed amongst 17 countries, 16 of which are African. H3ABioNet was developed to support H3Africa research projects through the development of bioinformatics capacity on the continent. Specifically H3ABioNet aims to: a) Implement a Pan African informatics infrastructure; b) Develop an H3Africa data coordinating center; c) Provide high quality informatics support to H3Africa; d) Enable and enhance innovative translational research; and e) Address outreach, development and sustainability.","1","2023-06-23 00:00:00","2023-10-16 21:28:28","" +"88","Harvard University","harvard","logo/harvard.jpg","https://www.harvard.edu/","As a research university and nonprofit institution, Harvard is focused on creating educational opportunities for people from many lived experiences.","3","2023-06-23 00:00:00","2023-07-26 20:14:26","" +"89","Heidelberg University","heidelberg-university","logo/heidelberg-university.jpg","https://www.heidelberg.edu/","A day at Heidelberg University is filled with connection. Whether it's walking to class, receiving one-on-one instruction from excellent faculty, or perfecting new skills at practice, students are uplifted every moment. Each time a Student Prince makes their own success, they know they have a dedicated community standing behind them.","10","2023-06-23 00:00:00","2023-07-26 20:14:27","" +"90","HistoSonics Inc.","histosonics","logo/histosonics.jpg","https://histosonics.com/","Minimally invasive isn't minimal enough. HistoSonics(R) is developing a non-invasive, sonic beam therapy platform capable of destroying tissue at a sub-cellular level.","1","2023-06-23 00:00:00","2023-07-26 20:14:28","" +"91","Hospital for Sick Children","sickkids","logo/sickkids.jpg","https://www.sickkids.ca/Research/","SickKids Research Institute (RI) is where over 2,000 researchers, trainees, and staff are working together to take on the toughest challenges in child health. As Canada's largest, hospital-based child health research institute, we conduct and translate groundbreaking research to improve child health outcomes, policy, and clinical care, train the next generation of researchers, and support global scientific communities with knowledge and state-of-the-art facilities. Innovation and collaboration across our seven distinct research programs have led to a number of incredible discoveries at SickKids, uncovering the mechanisms and outcomes of childhood disease. And with every research question in the lab, we are driving clinical changes.","4","2023-06-23 00:00:00","2023-07-26 20:14:28","" +"92","Human Protein Atlas","hpa","logo/hpa.png","www.proteinatlas.org","The Human Protein Atlas is a Swedish-based program initiated in 2003 with the aim to map the expression and spatial distribution of all human proteins in cells and tissues using an integration of various omics technologies, including antibody-based imaging, mass spectrometry-based proteomics, transcriptomics and systems biology. The data is freely available in the Protein Atlas database (www.proteinatlas.org) to allow scientists both in academia and industry to freely access the data for exploration of the human proteome with the mission to accelerate life science research and drug discovery.The database is used by over 200,000 users per month and nearly 10 publications per day use data from the Protein Atlas.\n\nThe image data in the challenge comes from the HPA Cell Atlas, led by Dr. Emma Lundberg.","1","2023-06-23 00:00:00","2023-07-26 20:14:29","HPA" +"93","International Business Machines Corporation","ibm","logo/ibm.svg","https://www.research.ibm.com/","At IBM Research we live by the scientific method. It's at the core of everything we do. We choose impact over market cycles, vision over vanity. We deeply believe that creative freedom, excellence, and integrity are essential to any breakthrough. We operate with a backbone. We don't cut corners. We take responsibility for technology and its role in society. We make decisions with a conscience — for a future that we believe is worth living in. We recognize the immense power and potential of computing — not as a commodity, but as an agent of progress and connection. This is the future, built right.","37","2023-06-23 00:00:00","2023-07-26 20:14:30","IBM" +"94","Innovative Medicines Initiative","imi","logo/imi.png","http://www.imi.europa.eu/","At the Innovative Medicines Initiative (IMI), we are working to improve health by speeding up the development of, and patient access to, innovative medicines, particularly in areas where there is an unmet medical or social need. We do this by facilitating collaboration between the key players involved in health research, including universities, research centres, the pharmaceutical and other industries, small and medium-sized enterprises (SMEs), patient organisations, and medicines regulators. IMI is the world's biggest public-private partnership (PPP) in the life sciences. It is a partnership between the European Union (represented by the European Commission) and the European pharmaceutical industry (represented by EFPIA, the European Federation of Pharmaceutical Industries and Associations). Through the IMI2 programme, we have a €3.3 billion budget for the period 2014-2020.","1","2023-06-23 00:00:00","2023-07-26 20:14:30","IMI" +"95","Institut Curie","institut-curie","logo/institut-curie.jpg","https://institut-curie.org/","Institut Curie is the leading cancer research and treatment centre in France and has been a recognised public utility foundation since 1921. Since its creation by Marie Curie, Institut Curie has worked on three missions: Care, Reserach, Transmission.","2","2023-06-23 00:00:00","2023-10-16 21:28:47","" +"96","Institute for Molecular Medicine Finland","fimm","logo/fimm.png","https://www.helsinki.fi/en/hilife-helsinki-institute-life-science/units/fimm","FIMM - Institute for Molecular Medicine Finland is a translational research institute focusing on human genomics and precision medicine as part of the Helsinki Institute of Life Science HiLIFE at the University of Helsinki. FIMM has a driving mission to perform innovative research on patients and populations targeted towards understanding drivers of health and disease. We aim at delivering improvements to the safety, efficacy, and efficiency of healthcare in Finland and beyond.","1","2023-06-23 00:00:00","2023-10-16 21:28:54","FIMM" +"97","Institute of Translational Health Sciences","iths","logo/iths.jpg","https://www.iths.org/","The Institute of Translational Health Sciences is dedicated to speeding science to the clinic for the benefit of patients and communities throughout Washington, Wyoming, Alaska, Montana, and Idaho.","1","2023-06-23 00:00:00","2023-07-26 20:14:34","ITHS" +"98","Intel Corporation","intel","logo/intel.svg","https://www.intel.com/content/www/us/en/homepage.html","Intel(R) Software sits at the intersection of hardware, interoperability, and amazing customer experiences. We partner with the global technology ecosystem to make development EASY, OPEN, and SCALABLE so developers can do what they do best: deliver groundbreaking applications and end-to-end solutions on Intel technologies. Visit the Intel(r) Nervana(TM) AI Academy to gain access to tools, Intel optimized frameworks, libraries, technical experts and training, getting started guides, and more.","3","2023-06-23 00:00:00","2023-11-20 22:08:58","" +"99","International Cancer Genome Consortium","icgc","logo/icgc.jpg","https://dcc.icgc.org/","The ICGC Data Portal provides many tools for visualizing, querying, and downloading cancer data, which is released on a quarterly schedule.","5","2023-06-23 00:00:00","2023-07-26 20:14:38","ICGC" +"100","International Flavors and Fragrances Inc.","iff","logo/iff.png","https://www.iff.com/","We apply science and creativity for a better world. With the beauty of art and the precision of science, we are an international collective of thinkers who partner with customers to bring scents, tastes, experiences, ingredients and solutions for products the world craves. As a global leader in food, beverage, health, biosciences and sensorial experiences, we do a lot and continually innovate to do it better. For more than 130 years we've been focused on finding the most innovative solutions to help bring “better for you” products to market. While we have grown over the years, we remain agile in our approach and put our customers' needs at the forefront of our thinking. We offer end-to-end service that few can deliver on. Our unparalleled product portfolio is the most robust in the industry and we have leadership positions across key taste, texture, scent, nutrition, enzymes, cultures, soy proteins and probiotics categories.","1","2023-06-23 00:00:00","2023-07-26 20:14:38","IFF" +"101","International Genome Sample Resource","igsr","logo/igsr.jpg","https://www.internationalgenome.org/home","The 1000 Genomes Project created a catalogue of common human genetic variation, using openly consented samples from people who declared themselves to be healthy. The reference data resources generated by the project remain heavily used by the biomedical science community. The International Genome Sample Resource (IGSR) maintains and shares the human genetic variation resources built by the 1000 Genomes Project. We also update the resources to the current reference assembly, add new data sets generated from the 1000 Genomes Project samples and add data from projects working with other openly consented samples.","1","2023-06-23 00:00:00","2023-07-26 20:14:39","IGSR" +"102","International Society for Computational Biology","iscb","logo/iscb.png","https://www.iscb.org/cms_addon/conferences/ismbeccb2021/tracks/function","Society membership reflects commitment toward the advancement of computational biology. The ISCB is an international non-profit organization whose members come from the global bioinformatics and computational biology communities. The ISCB serves its global membership by providing high-quality meetings, publications, and reports on methods and tools; by disseminating key information about bioinformatics resources and relevant news from related fields; and by actively facilitating training, education, employment, career development, and networking. We advocate and provide leadership for resources and policies in support of scientific endeavors and to benefit society at large.","2","2023-06-23 00:00:00","2023-07-26 20:14:40","ISCB" +"103","Intuitive Surgical Inc.","intuitive","logo/intuitive.jpg","https://www.intuitive.com/en-us","Intuitive advances minimally invasive care by innovating at the point of possibility. For nearly three decades we've created products and services born of inspiration and intelligence—from robotic-assisted surgical systems to data generation that unlocks the potential to benefit care systems worldwide. We work closely and collaboratively with our customers to help achieve better outcomes, better care team experiences, better patient experiences, and lower cost of care. Together, we envision a future of care that's less invasive, profoundly better, and where diseases are identified early and treated quickly so patients can get back to what matters most.","1","2023-06-23 00:00:00","2023-07-26 20:14:41","" +"104","Iowa State University","iowa-state-university","logo/iowa-state-university.png","https://www.iastate.edu/","Iowa State is a large university with a small feel. Forge lifelong friendships and earn a degree that will take you anywhere.","2","2023-06-23 00:00:00","2023-07-26 20:14:42","" +"105","Kaggle","kaggle","logo/kaggle.png","https://www.kaggle.com/","Kaggle is a community of data scientists and data enthusiasts. Our platform enables you to learn from and mentor each other on your personal, academic, and professional data science journeys. \n\nTo get involved, you can [enter a machine learning competition](https://www.kaggle.com/competitions), [publish an open dataset](https://www.kaggle.com/datasets), or [share code in our reproducible data science environment](https://www.kaggle.com/kernels). \n\nKaggle's headquarters is located in San Francisco, but we have team members working from across the US and Australia. [Join our team](https://www.kaggle.com/careers) from wherever you call home.","3","2023-06-23 00:00:00","2023-11-20 22:11:41","" +"106","Kaiser Permanente Washington Health Research Institute","kpwhri","logo/kpwhri.jpg","https://www.kpwashingtonresearch.org/","Kaiser Permanente Washington Health Research Institute (KPWHRI) is the non-proprietary, public-interest research center within Kaiser Permanente Washington, a nonprofit health system based in Seattle. Kaiser Permanente Washington provides coverage and care for more than 710,170 people in Washington. Our research produces timely, relevant findings that help people everywhere stay healthy and get the care they need. From testing new vaccines to helping people quit smoking to finding ways to delay or prevent Alzheimer's disease, our discoveries have helped millions of people worldwide lead healthier, happier lives.","1","2023-06-23 00:00:00","2023-07-26 20:14:44","KPWHRI" +"107","King's College London","kcl","logo/kcl.jpg","https://www.kcl.ac.uk/","King's College London is an internationally renowned university delivering exceptional education and world-leading research. We are dedicated to driving positive and sustainable change in society and realising our vision of making the world a better place.","2","2023-06-23 00:00:00","2023-07-26 20:14:44","KCL" +"108","Knowledge Engine for Genomics","knoweng","logo/knoweng.png","https://knoweng.org/","KnowEnG, The Knowledge Engine for Genomics, will transform the way biomedical researchers analyze their genome-wide data by integrating multiple analytical methods derived from the most advanced data mining and machine learning research. Embedded with the breadth of existing knowledge of genes, and an intuitive and professionally designed user interface, the Knowledge Engine platform provides advanced capabilities in data analytics. The KnowEnG environment is deployed in a cloud infrastructure and will be fully available to the research community, as will be the software developed by the Center.","1","2023-06-23 00:00:00","2023-07-26 20:14:45","" +"109","Koch Institute","koch-institute","logo/koch-institute.jpg","https://ki.mit.edu/","At the Koch Institute for Integrative Cancer Research, we take a uniquely MIT approach to solving some of the most difficult problems in cancer. Our research combines MIT's rich traditions of interdisciplinary inquiry and technological innovation with the most advanced investigation into the fundamental biology of cancer. With an unprecedented commitment to cross-disciplinary collaboration, we are accelerating the discovery and application of new ways to detect, monitor, treat, and prevent the disease.","1","2023-06-23 00:00:00","2023-07-26 20:14:46","" +"110","Laura and John Arnold Foundation","arnold-ventures","logo/arnold-ventures.jpg","https://www.arnoldventures.org/people/laura-arnold-john-arnold/","Arnold Ventures is a philanthropy working to improve the lives of all Americans by pursuing evidence-based solutions to our nation's most pressing problems. We fund research to better understand the root causes of broken systems that limit opportunity and create injustice. Our focus areas include Criminal Justice, Higher Education, Health, and Public Finance. In each area, we advocate for policy reforms that will lead to lasting, scalable change.","1","2023-06-23 00:00:00","2023-07-26 20:14:46","" +"111","Lausanne University Hospital","chuv","logo/chuv.jpg","https://www.lausanneuniversityhospital.com/home","Lausanne University Hospital is one of the five university hospitals in Switzerland, with Geneva, Bern, Basel and Zurich. With its 16 clinical and medico-technical departments and their numerous services, the CHUV is renowned for its academic achievements in health care, research, and teaching. The CHUV is also a well-known center of medical education and research thanks to its collaboration with the Faculty of Biology and Medicine of the University of Lausanne and the Swiss Federal Institute of Technology in Lausanne (EPFL). Together, these institutions form a vast campus in the Lake Geneva region.","1","2023-06-23 00:00:00","2023-07-26 20:14:47","CHUV" +"112","Leukemia and Lymphoma Society","lls","logo/lls.jpg","https://www.lls.org/","The Leukemia & Lymphoma Society (LLS) is at the forefront of the fight to cure blood cancer. We are the largest nonprofit dedicated to creating a world without blood cancers. Since 1949, we've invested more than $1.6 billion in groundbreaking research, pioneering many of today's most innovative approaches. LLS is a global leader in the fight against blood cancer.","1","2023-06-23 00:00:00","2023-07-26 20:14:48","LLS" +"113","Ligue Nationale Contre le Cancer","ligue-cancer","logo/ligue-cancer.jpg","https://www.ligue-cancer.net/","Since 1918, the League has been fighting against cancer by being the first independent funder of research","1","2023-06-23 00:00:00","2023-07-26 20:14:48","" +"114","London's Global University","ucl","logo/ucl.jpg","https://www.ucl.ac.uk/","Founded in 1826 in the heart of London, UCL is London's leading multidisciplinary university, with more than 16,000 staff and 50,000 students from over 150 different countries. We are a diverse community with the freedom and courage to challenge, to question and to think differently.","2","2023-06-23 00:00:00","2023-07-26 20:14:49","UCL" +"115","Ludwig Maximilian University of Munich","lmu","logo/lmu.jpg","https://www.lmu.de/en/index.html","Ludwig-Maximilians-Universitat Munchen is a leading research university in Europe. Since its founding in 1472 it has been committed to the highest international standards of excellence in research and teaching.","2","2023-06-23 00:00:00","2023-07-26 20:14:51","LMU" +"116","Mahidol Oxford Tropical Medicine Research Unit","moru","logo/moru.jpeg","https://www.tropmedres.ac/","The MORU Tropical Health Network, which hosts the ‘Thailand Wellcome Africa and Asia Programme', conducts targeted clinical and public health research that aims to discover and develop appropriate, practical, affordable interventions that measurably improve the health of people living in resource-limited parts of the world.","1","2023-06-23 00:00:00","2023-07-26 20:14:51","MORU" +"117","March of Dimes","march-of-dimes","logo/march-of-dimes.jpg","https://www.marchofdimes.org/","March of Dimes is a nonprofit organization committed to ending preventable maternal health risks and death, ending preventable preterm birth and infant death and closing the health equity gap for all families.","1","2023-06-23 00:00:00","2023-07-26 20:14:51","" +"118","Massachusetts General Hospital","mass-general","logo/mass-general.png","https://www.massgeneral.org/","In the delivery of our care, through our research and within our communities, Mass General is committed to the well-being of our patients locally and globally.","3","2023-06-23 00:00:00","2023-07-26 20:14:54","" +"119","Massachusetts Institute of Technology","mit","logo/mit.jpg","https://www.mit.edu/","The MIT community is driven by a shared purpose: to make a better world through education, research, and innovation. We are fun and quirky, elite but not elitist, inventive and artistic, obsessed with numbers, and welcoming to talented people regardless of where they come from.","8","2023-06-23 00:00:00","2023-10-16 21:29:42","MIT" +"120","MathWorks","mathworks","logo/mathworks.jpg","https://www.mathworks.com/","We at MathWorks believe in the importance of engineers and scientists. They increase human knowledge and profoundly improve our standard of living. We created MATLAB and Simulink to help them do their best work.","2","2023-06-23 00:00:00","2023-07-26 20:14:56","" +"121","Max Delbruck Center for Molecular Medicine","mdc","logo/mdc.jpg","https://www.mdc-berlin.de/","The Max Delbruck Center is an internationally renowned biomedical research center in Berlin. It is named after Max Delbrück, one of the founders of modern genetics and molecular biology.","1","2023-06-23 00:00:00","2023-07-26 20:14:56","MDC" +"122","MD Anderson Cancer Center","md-anderson","logo/md-anderson.jpg","https://www.mdanderson.org/","At MD Anderson, we understand how hard it can be to choose a hospital for cancer treatment. You've just received life-changing news, and now you have to decide how to handle it. Here are some of the reasons why MD Anderson is your best hope for cancer care.","1","2023-06-23 00:00:00","2023-07-26 20:14:57","" +"124","Memorial Sloan Kettering Cancer Center","msk","logo/msk.jpg","https://www.mskcc.org/","The people of Memorial Sloan Kettering Cancer Center (MSK) are united by a singular mission: ending cancer for life. Our specialized care teams provide personalized, compassionate, expert care to patients of all ages. Informed by basic research done at our Sloan Kettering Institute, scientists across MSK collaborate to conduct innovative translational and clinical research that is driving a revolution in our understanding of cancer as a disease and improving the ability to prevent, diagnose, and treat it. MSK is dedicated to training the next generation of scientists and clinicians, who go on to pursue our mission at MSK and around the globe. One of the world's most respected comprehensive centers devoted exclusively to cancer, we have been recognized as one of the top two cancer hospitals in the country by U.S. News & World Report for more than 30 years.","3","2023-06-23 00:00:00","2023-10-16 21:30:31","MSK" +"125","Merck Co.","merck","logo/merck.jpg","https://www.merck.com/","Our purpose: We use the power of leading-edge science to save and improve lives around the world. For more than 130 years, we have brought hope to humanity through the development of important medicines and vaccines. We aspire to be the premier research-intensive biopharmaceutical company in the world — and today, we are at the forefront of research to deliver innovative health solutions that advance the prevention and treatment of diseases in people and animals. We foster a diverse and inclusive global workforce and operate responsibly every day to enable a safe, sustainable and healthy future for all people and communities.","1","2023-06-23 00:00:00","2023-10-16 21:30:50","" +"126","Michael J. Fox Foundation","mjff","logo/mjff.jpg","https://www.michaeljfox.org/","The Michael J. Fox Foundation is dedicated to finding a cure for Parkinson's disease through an aggressively funded research agenda and to ensuring the development of improved therapies for those living with Parkinson's today.","4","2023-06-23 00:00:00","2023-07-26 20:15:00","MJFF" +"127","MINES ParisTech","mines-paristech","","http://www.mines-paristech.eu/","250 years of history for the Graduate School. 1 500 students. 17 research centres, 230 talented research professors, 1st school for collaborative research, a unique link with companies. Values built over the years, which we are proud to display, to maintain, to share.","1","2023-06-23 00:00:00","2023-07-26 20:15:00","" +"128","Mount Sinai","mt-sinai","logo/mt-sinai.jpg","https://www.mountsinai.org/","The Mount Sinai Health System is an integrated health care system providing exceptional medical care to our local and global communities. Encompassing the Icahn School of Medicine at Mount Sinai and eight hospital campuses in the New York metropolitan area, as well as a large, regional ambulatory footprint, Mount Sinai is internationally acclaimed for its excellence in research, patient care, and education across a range of specialties. The Mount Sinai Health System was created from the combination of the Mount Sinai Medical Center and Continuum Health Partners, which both agreed unanimously to combine the two entities in July 2013.","28","2023-06-23 00:00:00","2023-07-26 20:15:01","" +"129","Multiple Myeloma Research Foundation","mmrf","logo/mmrf.jpg","https://themmrf.org/","The MMRF is the largest nonprofit in the world focused on accelerating the cure for multiple myeloma. Our work is not done until each and every multiple myeloma patient has the answers they need. With our exceptional leadership, strategic collaboration and uniquely innovative approach, we are on the path to finding a cure for multiple myeloma.","1","2023-06-23 00:00:00","2023-07-26 20:15:03","MMRF" +"130","Nathan S. Kline Institute for Psychiatric Research","nki","logo/nki.png","https://www.nki.rfmh.org/","As one of the nation's most respected research centers focused on mental health, investigators at the Nathan S. Kline Institute for Psychiatric Research (NKI) study the causes, treatment, prevention, and rehabilitation of severe and persistent mental illnesses. As a facility of the New York State Office of Mental Health, founded in 1952, NKI has earned a reputation for its landmark contributions in psychiatric research, especially in the areas of psychopharmacological treatments for schizophrenia and major mood disorders, dementia research, clinical trials methodology, neuroimaging, therapeutic drug monitoring, and the application of computer technology to mental health services.","1","2023-06-23 00:00:00","2023-07-26 20:15:03","NKI" +"131","National Cancer Institute","nci","logo/nci.jpg","https://www.cancer.gov/","The National Cancer Institute (NCI) is the federal government's principal agency for cancer research and training. NCI leads, conducts, and supports cancer research across the nation to advance scientific knowledge and help all people live longer, healthier lives.","11","2023-06-23 00:00:00","2023-07-26 20:15:04","NCI" +"132","National Center for Advancing Translational Sciences","ncats","logo/ncats.jpg","https://ncats.nih.gov/","The National Center for Advancing Translational Sciences (NCATS) — one of 27 Institutes and Centers at the National Institutes of Health (NIH) — was established to transform the translational process so that new treatments and cures for disease can be delivered to patients faster.","1","2023-06-23 00:00:00","2023-07-26 20:15:05","NCATS" +"133","National Center for Data to Health","cd2h","","https://cd2h.org/","The National Center for Data to Health (CD2H) accelerates advancements in informatics by using findable, accessible, interoperable, and reusable (FAIR) principles to promote collaboration across the Clinical and Translational Science Awards (CTSA) Program community. CD2H tools and resources make it simple and valuable for CTSA Program members to get engaged, connect with peers, and contribute. By promoting collaboration, CD2H fosters a robust translational science informatics ecosystem that collectively develops solutions to solve clinical problems faster, more efficiently, and more effectively. CTSA Program members are poised to lead this charge by harnessing collective expertise and strengths to solve key informatics challenges. With this team science approach, advancements in translational research can ultimately improve patient care.","2","2023-06-23 00:00:00","2023-07-26 20:15:05","CD2H" +"134","National Institute of Environmental Health Sciences","niehs","logo/niehs.png","https://www.niehs.nih.gov/","The National Institute of Environmental Health Sciences (NIEHS) is expanding and accelerating its contributions to scientific knowledge of human health and the environment, and to the health and well-being of people everywhere.","1","2023-06-23 00:00:00","2023-07-26 20:15:06","NIEHS" +"135","National Institute of General Medical Sciences","nigms","logo/nigms.jpg","https://www.nigms.nih.gov/","The National Institute of General Medical Sciences (NIGMS) supports basic research that increases our understanding of biological processes and lays the foundation for advances in disease diagnosis, treatment, and prevention. NIGMS-funded scientists investigate how living systems work at a range of levels—from molecules and cells to tissues and organs—in research organisms, humans, and populations. Additionally, to ensure the vitality and continued productivity of the research enterprise, NIGMS provides leadership in training the next generation of scientists, enhancing the diversity of the scientific workforce, and developing research capacity throughout the country.","3","2023-06-23 00:00:00","2023-07-26 20:15:07","NIGMS" +"136","National Institute of Standards and Technology","nist","logo/nist.png","https://www.nist.gov/","The National Institute of Standards and Technology (NIST) was founded in 1901 and is now part of the U.S. Department of Commerce. NIST is one of the nation's oldest physical science laboratories. Congress established the agency to remove a major challenge to U.S. industrial competitiveness at the time — a second-rate measurement infrastructure that lagged behind the capabilities of the United Kingdom, Germany and other economic rivals. From the smart electric power grid and electronic health records to atomic clocks, advanced nanomaterials and computer chips, innumerable products and services rely in some way on technology, measurement and standards provided by the National Institute of Standards and Technology.","3","2023-06-23 00:00:00","2023-07-26 20:15:08","NIST" +"137","National Science Foundation","nsf","logo/nsf.jpg","https://www.nsf.gov/","The U.S. National Science Foundation is an independent federal agency that supports science and engineering in all 50 states and U.S. territories. NSF was established in 1950 by Congress to: a) Promote the progress of science. b) Advance the national health, prosperity and welfare. c) Secure the national defense.","1","2023-06-23 00:00:00","2023-10-16 21:31:24","NSF" +"138","Natural Sciences and Engineering Research Council","nserc","logo/nserc.jpg","https://www.nserc-crsng.gc.ca/index_eng.asp","The Natural Sciences and Engineering Research Council of Canada funds visionaries, explorers and innovators who are searching for the scientific and technical breakthroughs that will benefit our country. We are Canada's largest supporter of discovery and innovation. We work with universities, colleges, businesses and not-for-profits to remove barriers, develop opportunities and attract new expertise to make Canada's research community thrive. We give Canadian scientists and engineers the means to go further because we believe in research without borders and beyond frontiers.","3","2023-06-23 00:00:00","2023-07-26 20:15:09","NSERC" +"139","Neosoma Inc.","neosoma","logo/neosoma.jpg","https://www.neosomainc.com/","Every brain cancer patient is unique, and so is every brain tumor. Neuro-oncology teams need new tools and insights to advance the state of care. At Neosoma, our mission is to help clinicians improve outcomes by providing novel disease insights to physicians and clinical trials through innovative AI technology.","2","2023-06-23 00:00:00","2023-07-26 20:15:10","" +"140","Neurological Clinical Research Institute","ncri","","https://www.massgeneral.org/ncri","The Neurological Clinical Research Institute (NCRI) at Mass General is an academic research organization composed of innovative researchers experienced and passionate about designing, developing, facilitating, and conducting multicenter clinical trials in neurological diseases. Our goal is to develop new treatments for the patients we care for and for patients around the globe. We have particular expertise in ALS, Parkinson's disease and other neurodegenerative diseases.","1","2023-06-23 00:00:00","2023-07-26 20:15:11","NCRI" +"141","New York University","nyc","logo/nyu.png","https://www.nyu.edu/","Since its founding in 1831, NYU has been an innovator in higher education, reaching out to an emerging middle class, embracing an urban identity and professional focus, and promoting a global vision that informs its 20 schools and colleges. Today, that trailblazing spirit makes NYU one of the most prominent and respected research universities in the world, featuring top-ranked academic programs and accepting fewer than one in eight undergraduates. Anchored in New York City and with degree-granting campuses in Abu Dhabi and Shanghai as well as 12 study away sites throughout the world, NYU is a leader in global education, with more international students and more students studying abroad than any other US university.","1","2023-06-23 00:00:00","2023-07-26 20:15:12","NYC" +"142","Northeast ALS Consortium","neals","logo/neals.jpg","https://www.neals.org/","The mission of the Northeast Amyotrophic Lateral Sclerosis Consortium(R) (NEALS) is to rapidly translate scientific advances into clinical research and new treatments for people with Amyotrophic Lateral Sclerosis (ALS) and motor neuron disease.","2","2023-06-23 00:00:00","2023-07-26 20:15:12","NEALS" +"143","Northeastern University","neu","logo/neu.jpg","https://www.northeastern.edu/","At Northeastern, experience is our essence and ethos. It's what you gain when you make the world your classroom, your laboratory, and your platform to create change or grow your enterprise. Throughout our university network, experience draws you into society and compels you to solve its complex challenges. It makes you agile and able to reinvent yourself. To find ways of doing things differently, and better. And to seize opportunities as they unfold—anytime, anywhere.","2","2023-06-23 00:00:00","2023-07-26 20:15:13","NEU" +"144","Northwestern University","nu","logo/nu.jpg","https://www.northwestern.edu/","Northwestern is committed to excellent teaching, innovative research and the personal and intellectual growth of its students in a diverse academic community.","2","2023-06-23 00:00:00","2023-07-26 20:15:14","NU" +"145","Novo Nordisk","novo-nordisk","logo/novo-nordisk.jpg","https://www.novonordisk-us.com/","For more than 100 years, we have been translating the unmet medical needs of people living with a serious chronic disease into innovative medicines and delivery systems. Our treatments today are helping millions of people living with diabetes, obesity, rare bleeding disorders and growth hormone-related disorders. From our labs to our factory floors, we are discovering and developing innovative biological medicines and making them accessible to patients throughout the world.","1","2023-06-23 00:00:00","2023-07-26 20:15:15","" +"146","Numerate","numerate","","","This organization may no longer exist, has rebranded, or has been merged under another organization.","1","2023-06-23 00:00:00","2023-08-08 17:59:10","" +"147","NVIDIA","nvidia","logo/nvidia.png","https://www.nvidia.com/en-us/","NVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Our work in AI and the metaverse is transforming the world's largest industries and profoundly impacting society.","3","2023-06-23 00:00:00","2023-07-26 20:15:16","" +"148","Ohio State University","osu","logo/osu.png","https://www.osu.edu/","Discover the Ohio State difference. We create unrivaled experiences that bring together expertise, ideas and resources that improve communities locally and globally.","2","2023-06-23 00:00:00","2023-07-26 20:15:17","OSU" +"149","Ontario Institute for Cancer Research","oicr","logo/oicr.svg","https://oicr.on.ca/","The Ontario Institute for Cancer Research helps close the gap between groundbreaking cancer discoveries and life-changing patient outcomes. OICR is a research institute that collaborates with partners across Ontario and around the world to accelerate the development of new cancer research discoveries and propel them from the lab to the clinic, bringing health and economic benefits to the people of Ontario.","6","2023-06-23 00:00:00","2023-07-26 20:15:18","OICR" +"150","Oregon Health and Science University","ohsu","logo/ohsu.jpg","https://www.ohsu.edu/","OHSU is Oregon's only public academic health center. We are a system of hospitals and clinics across Oregon and southwest Washington. We are an institution of higher learning, with schools of medicine, nursing, pharmacy, dentistry and public health - and with a network of campuses and partners throughout Oregon. We are a national research hub, with thousands of scientists developing lifesaving therapies and deeper understanding. We are a statewide economic engine and Portland's largest employer. And as a public organization, we provide services for the most vulnerable Oregonians, and outreach to improve health in communities across the state.","11","2023-06-23 00:00:00","2023-10-16 21:31:47","OHSU" +"151","Oslo University Hospital","ous","logo/ous.png","https://oslo-universitetssykehus.no/oslo-university-hospital","​Oslo University Hospital (OUS) ​is a highly specialised hospital in charge of extensive regional and local hospital assignments and the provision of high quality services for the citizens of Oslo. The hospital also has a nationwide responsibility for a number of national and multi-regional assignments and has several national centres of competence.","1","2023-06-23 00:00:00","2023-07-26 20:15:21","OUS" +"152","Pacific Northwest National Laboratory","pnnl","logo/pnnl.png","https://www.pnnl.gov/","Pacific Northwest National Laboratory is a different kind of national lab. PNNL advances the frontiers of knowledge, taking on some of the world's greatest science and technology challenges. Distinctive strengths in chemistry, Earth sciences, biology, and data science are central to our scientific discovery mission. Our research lays a foundation for innovations that advance sustainable energy through decarbonization and energy storage and enhance national security through nuclear materials and threat analyses. PNNL collaborates with academia in fundamental research and with industry to transition technologies to market.","2","2023-06-23 00:00:00","2023-07-26 20:15:22","PNNL" +"153","Pfizer Inc.","pfizer","logo/pfizer.jpg","https://www.pfizer.com/","We're in relentless pursuit of breakthroughs that change patients' lives. We innovate every day to make the world a healthier place. It was Charles Pfizer's vision at the beginning and it holds true today.","1","2023-06-23 00:00:00","2023-07-26 20:15:22","" +"154","Prize4Life","prize4life","logo/prize4life.jpeg","","Prize4Life seeks to create breakthroughs in effective treatments for Amyotrophic Lateral Sclerosis (ALS, or Lou Gehrig's Disease) using the leverage of large inducement prizes. Instead of recognizing historical accomplishments, Prize4Life has a simple formula for transformational change. We design and launch prizes that we believe are achievable in a 2-3 year timeframe and then recruit teams to compete for the prize purse. The first team to find and demonstrate the required breakthrough wins the prize.","2","2023-06-23 00:00:00","2023-11-21 01:21:14","" +"155","Project Data Sphere","project-data-sphere","logo/project-data-sphere.jpg","https://www.projectdatasphere.org/","At Project Data Sphere®, we believe in breaking down barriers to cancer clinical trial data sharing — barriers that historically have kept valuable trial data from ultimately benefitting the patients who so selflessly participate in them. By aggregating trial data from biopharmaceutical companies, academic medical centers, and government organizations and making it freely available on our open-access platform, we have established ourselves as a premier resource for the global oncology research community. Our deep relationships with renowned oncology experts allow us to convene research collaborations that leverage the power of pooled clinical trial data and which ultimately position PDS to be a catalyst for the discovery of urgently needed new treatments while helping to make cancer trials faster, more effective, and less expensive.","1","2023-06-23 00:00:00","2023-07-26 20:15:26","" +"156","Prostate Cancer Canada","prostate-cancer-canada","logo/prostate-cancer-canada.png","https://cancer.ca/en/","At the Canadian Cancer Society, we are committed to improving and saving lives. That's why we are always looking for new ways to prevent cancer, find it early and treat it more successfully. It's why we're always ready to give people with cancer the help and support they need to lead more fulfilling lives.","2","2023-06-23 00:00:00","2023-07-26 20:15:27","" +"157","Prostate Cancer Foundation","pcf","logo/pcf.jpg","https://www.pcf.org/","The Prostate Cancer Foundation (PCF) funds the world's most promising research to improve the prevention, detection, and treatment of prostate cancer and ultimately cure it for good.","1","2023-06-23 00:00:00","2023-07-26 20:15:28","PCF" +"158","Providence Health and Services","providence","logo/providence.jpg","https://www.providence.org/en","At Providence we see more than patients, we see the life that pulses through us all. That's why we're dedicated to a holistic approach to medicine that employs not only the most advanced treatments to improve outcomes, but also puts compassion and humanity at the heart of every interaction.","1","2023-06-23 00:00:00","2023-07-26 20:15:29","" +"159","QIMR Berghofer Medical Research Institute","qimr-berghofer","logo/qimr-berghofer.jpg","https://www.qimrberghofer.edu.au/","From humble beginnings in 1945, the Queensland Institute of Medical Research, now known as QIMR Berghofer, is one of Australia's most successful medical research institutes, translating discoveries from bench to bedside for a better future of health.","1","2023-06-23 00:00:00","2023-07-26 20:15:30","" +"160","Queen's University","queensu","logo/queensu.jpg","https://www.queensu.ca/","We stand on a strong history of scholarship, discovery, and innovation. nOur education transforms Queen's students. Our diversity enriches the community. Our research changes the world. Together, we are tackling humanity's greatest challenges.","1","2023-06-23 00:00:00","2023-07-26 20:15:31","" +"161","Radboud University Medical Center","radboud-umc","logo/radboud-umc.jpeg","https://www.radboudumc.nl/en/research","Radboud university medical center specializes in patient care, scientific research, teaching and training. Our mission is to have a significant impact on health care. We aim to be pioneers in shaping the health care of the future. We do this in a person-centered and innovative way.","10","2023-06-23 00:00:00","2023-07-26 20:15:31","" +"162","Radiological Society of North America","rsna","logo/rsna.png","https://www.rsna.org/","The Radiological Society of North America (RSNA(R)) is an international society of radiologists, medical physicists and other medical professionals with more than 53,400 members from 136 countries across the globe. RSNA hosts the world's premier radiology forum, drawing approximately 55,000 attendees annually to McCormick Place in Chicago, and publishes two top peer-reviewed journals: *Radiology*, the highest-impact scientific journal in the field, and *RadioGraphics*, the only journal dedicated to continuing education in radiology. The Society is based in Oak Brook, Ill.","3","2023-06-23 00:00:00","2023-10-16 21:32:38","RSNA" +"164","Ray and Dagmar Dolby Family Fund","dolby-family-ventures","logo/dolby-family-ventures.jpg","http://www.dolbyventures.com/","Dolby Family Ventures is an early stage venture firm focused on building great technology companies. We partner with best-in-class innovators and strong investment syndicate partners at the seed stage of a company's development. The fund honors the legacy of Ray Dolby and his commitment to engineers and their vision to solve the world's toughest problems. Dolby Family Ventures formalizes the Dolby family's ongoing multi-generational commitment to supporting talented entrepreneurs. We work actively with entrepreneurs to implement best practices in operational finance, strategy, and board development processes.","1","2023-06-23 00:00:00","2023-07-26 20:15:34","" +"165","Rice University","rice","logo/rice.jpg","https://www.rice.edu/","Located in an urban environment on a 300-acre tree-lined campus, Rice University seizes its advantageous position to pursue pathbreaking research and create innovative collaboration opportunities that contribute to the betterment of our world.","1","2023-06-23 00:00:00","2023-07-26 20:15:35","" +"166","Robert Wood Johnson Foundation","rwjf","logo/rwjf.jpg","https://www.rwjf.org/","RWJF works in collaboration with policymakers, business leaders, community groups and many others. Together, we share a common interest in addressing the many harmful obstacles to wellbeing, including poverty, powerlessness, and discrimination, and advancing health equity for all. We focus on identifying, illuminating, and addressing barriers to health, particularly those caused by structural racism and its intersection with other forms of discrimination, including sexism, ableism, and prejudice based on sexual orientation. We lean on evidence to advance health equity. We cultivate leaders who work individually and collectively across sectors to address health equity. We promote policies, practices, and systems change to dismantle the structural barriers to wellbeing created by racism. And we work to amplify voices to shift national conversations and attitudes about health and health equity.","1","2023-06-23 00:00:00","2023-07-26 20:15:35","RWJF" +"167","Rockefeller University","rockefeller","logo/rockefeller.jpg","https://www.rockefeller.edu/","The world's leading biomedical research university, Rockefeller draws top scientists and graduate students from around the world in pursuit of one mission: to conduct science for the benefit of humanity.","1","2023-06-23 00:00:00","2023-10-16 21:33:09","" +"168","Rosenberg Alzheimer's Project","rosenberg-alzheimers-project","","","This organization may no longer exist, has rebranded, or has been merged under another organization.","1","2023-06-23 00:00:00","2023-08-08 17:59:30","" +"169","Rush University Medical Center","rush","logo/rush.jpg","https://www.rush.edu/","Rush University System for Health is consistently recognized for our outstanding patient care, education, research and community partnerships. Learn more about our mission, history, policies and leadership.","1","2023-06-23 00:00:00","2023-07-26 20:15:38","RUSH" +"170","RWTH Aachen University","rwth-aachen","logo/rwth-aachen.png","https://www.rwth-aachen.de/go/id/a/?lidx=1","RWTH Aachen University is a place where the future of our industrialised world is thought out. The University is proving to be a hotspot with increasing international recognition where innovative answers to global challenges are developed.","8","2023-06-23 00:00:00","2023-07-26 20:15:39","" +"171","Sage Bionetworks","sage","logo/sage-bionetworks.png","https://sagebionetworks.org/","Sage Bionetworks is a nonprofit health research organization that is speeding the translation of science into medicine. We believe that high-quality, well-annotated data acts as the foundation of modern biomedical innovation. We dream of a world where people work together across institutional boundaries to meaningfully address major medical research problems. We incubate new ways for diverse groups of people to practice research together. We advance our practices using an integrated and iterative design cycle that plays out between our scientific teams and our core service teams. As our innovations become norms, we develop them into robust core capabilities that can be put into practice across our portfolio of research programs. This portfolio includes publicly funded programs that create data resources and knowledge bases, pre-competitive collaborations across industry partners, and federated networks of healthcare data providers. In turn, these projects provide an active p...","48","2023-06-23 00:00:00","2023-10-05 15:22:50","" +"172","Sanofi","sanofi","logo/sanofi.jpg","https://www.sanofi.com/","We are Sanofi. We are an innovative global healthcare company, driven by one purpose: we chase the miracles of science to improve people's lives. Our teams across the world strive to transform the practice of medicine, turning the impossible into the possible for patients. We provide potentially life-changing treatments and the protection of life-saving vaccines to millions of people, and affordable access to our medicines in some of the world's poorest countries.","2","2023-06-23 00:00:00","2023-10-16 22:32:10","" +"173","Sapienza University of Rome","sapienza","logo/sapienza.png","https://www.uniroma1.it/en/pagina-strutturale/home","Founded in 1303, Sapienza is the oldest university in Rome and the largest in Europe. Its mission is to contribute to the development of a knowledge society through research, excellence, quality education and international cooperation.","3","2023-06-23 00:00:00","2023-07-26 20:15:43","" +"174","Sartorius AG","sartorius","logo/sartorius.jpg","https://www.sartorius.com/en","Sartorius AG is an international pharmaceutical and laboratory equipment supplier, covering the segments of Bioprocess Solutions and Lab Products & Services.","1","2023-06-23 00:00:00","2023-07-26 20:15:42","" +"175","Seattle Cancer Care Alliance","scca","logo/fred-hutch.jpg","https://www.seattlecca.org/","SCCA is now Fred Hutchinson Cancer Center, an independent, nonprofit cancer care and research center that also serves as the cancer program for UW Medicine. The superior care you have come to expect will continue uninterrupted.","1","2023-06-23 00:00:00","2023-07-26 20:15:43","SCCA" +"176","Semmelweis University","semmelweis-university","logo/semmelweis-university.png","https://semmelweis.hu/english/","Semmelweis University is a leading institution of higher education in Hungary and the Central European region within the area of medicine and health sciences. Its main commitment is based on the integrity of education, research and healing, which make Semmelweis University an internationally renowned centre of knowledge.","2","2023-06-23 00:00:00","2023-07-26 20:15:43","" +"177","Sentieon","sentieon","logo/sentieon.jpg","https://www.sentieon.com/","Sentieon(R), incorporated in July 2014, develops highly-optimized algorithms for bioinformatics applications, using the team's expertise in algorithm, software, and system optimization. Sentieon(R) is a team of professionals experienced in image processing, telecom, computational lithography, large-scale data mining, and bioinformatics. Using our accumulated expertise in modeling, optimization, machine learning, and high-performance computing, we strive to enable precision data for precision medicine.","1","2023-06-23 00:00:00","2023-07-26 20:15:44","" +"178","Siemens Healthineers","siemens-healthineers","logo/siemens-healthineers.jpg","https://www.siemens-healthineers.com/","We pioneer breakthroughs in healthcare. For everyone. Everywhere.","1","2023-06-23 00:00:00","2023-07-26 20:15:45","" +"179","Stanford University","stanford","logo/stanford.jpg","https://www.stanford.edu/","Stanford was founded almost 150 years ago on a bedrock of societal purpose. Our mission is to contribute to the world by educating students for lives of leadership and purposeful contribution; advancing fundamental knowledge and cultivating creativity; and accelerating solutions and amplifying their impact.","18","2023-06-23 00:00:00","2023-07-26 20:15:46","" +"180","Swiss Initiative in Systems Biology","systemsx","logo/systemsx.jpg","http://www.systemsx.ch/","SystemsX.ch is the largest ever public research initiative in Switzerland and focuses specifically on a broad topical area of basic research. The initiative advances systems biology in our country with the claim of belonging to the best in the world in this area of research.","1","2023-06-23 00:00:00","2023-07-26 20:15:47","" +"181","Takeda","takeda","logo/takeda.jpg","https://www.takeda.com/en-us/","Takeda is a patient-focused, values-based, R&D-driven global biopharmaceutical company committed to bringing Better Health and a Brighter Future to people worldwide. Our passion and pursuit of potentially life-changing treatments for patients are deeply rooted in over 230 years of distinguished history in Japan.","2","2023-06-23 00:00:00","2023-07-26 20:15:48","" +"182","Texas Biomedical Research Institute","texas-biomedical-research-institute","logo/texas_biomed.png","https://www.txbiomed.org/","Texas Biomedical Research Institute is pioneering and sharing scientific breakthroughs to protect you, your families and our global community from the threat of infectious diseases. The Institute has an 80-year history of success that includes work on the first COVID-19 vaccine and therapies, the first Ebola treatment, the first Hepatitis-C therapy, and thousands of developmental discoveries. Texas Biomed helps create healthier communities with science that inspires new generations through STEM education programs, delivers jobs and economic impact in our community and heals through innovative research. Learn more about how you can #Stand4Science.","1","2023-06-23 00:00:00","2023-07-26 20:15:50","" +"183","The University of California-Davis","uc-davis","logo/uc_davis.png","https://www.ucdavis.edu/","We grow California. UC Davis was founded in 1908 to serve the state of California. We do and we always will. And today, the seed that was planted those years ago has grown into one of the world's top universities.","2","2023-06-23 00:00:00","2023-07-26 20:15:51","" +"184","The University of Texas at Austin","ut","logo/ut-austin.svg","https://www.utexas.edu/","Like the state it calls home, The University of Texas at Austin is a bold, ambitious leader supporting some 52,000 diverse students, 3,000 teaching faculty, and top national programs across 18 colleges and schools. As Texas' leading research university, UT attracts more than $650 million annually for discovery. Amid the backdrop of Austin, Texas, a city recognized for its creative and entrepreneurial spirit, the university provides a place to explore countless opportunities for tomorrow's artists, scientists, athletes, doctors, entrepreneurs and engineers.","1","2023-06-23 00:00:00","2023-07-26 20:15:52","UT" +"185","Thomas Jefferson University Hospital","jefferson-health","logo/jefferson.jpeg","https://hospitals.jefferson.edu/","We are Jefferson. At Jefferson Health, we are reimagining health care through our service-minded and diverse community of providers and specialists. Our mission is to improve lives. We strive to be bold and innovative, while putting your health and safety first. Each day, we are focused on you.","2","2023-06-23 00:00:00","2023-07-26 20:15:52","" +"186","TracInnovations","tracinnovations","logo/tracinnovations.webp","https://tracinnovations.com/","TracInnovations is a Danish company established in 2015 focusing on innovative solutions for image based diagnosis and treatment. TracInnovations has developed the Tracoline system, which is a MRI Markerless Motion Tracker and Monitor System that unnoticed records patient's head movements during brain scans.","1","2023-06-23 00:00:00","2023-07-26 20:15:53","" +"187","Trinity College Institute of Neuroscience","tcd-neuroscience","logo/tcd.png","https://www.tcd.ie/Neuroscience/","The Trinity College Institute of Neuroscience (TCIN) is a Trinity Research Institute (TRI) with 50 Principal Investigators and 250 researchers from a wide range of disciplines including Psychology, Psychiatry, Physiology, Pharmacology, Medicine, Biochemistry, Engineering, and Genetics, among others. These diverse disciplinary origins contribute to its core activities: promoting and supporting interdisciplinary basic and translational research, as well as teaching, public engagement, and national leadership in Neuroscience.","1","2023-06-23 00:00:00","2023-10-16 22:41:29","" +"188","Tulane University","tulane","logo/tu_new_shield.svg","https://tulane.edu/","Tulane's motto - non sibi, sed suis - embodies who we are and what we stand for. We are entrepreneurs on the front lines of life-changing technologies, as well as hometown heroes. Tulanians see challenges as opportunities, and strive to improve the lives of others in our own community and around the globe.","1","2023-06-23 00:00:00","2023-10-16 22:41:38","" +"189","U.S. Food and Drug Administration","fda","logo/fda.svg","https://www.fda.gov/home","The Food and Drug Administration is responsible for protecting the public health by ensuring the safety, efficacy, and security of human and veterinary drugs, biological products, and medical devices; and by ensuring the safety of our nation's food supply, cosmetics, and products that emit radiation. FDA also has responsibility for regulating the manufacturing, marketing, and distribution of tobacco products to protect the public health and to reduce tobacco use by minors. FDA is responsible for advancing the public health by helping to speed innovations that make medical products more effective, safer, and more affordable and by helping the public get the accurate, science-based information they need to use medical products and foods to maintain and improve their health. FDA also plays a significant role in the Nation's counterterrorism capability. FDA fulfills this responsibility by ensuring the security of the food supply and by fostering development of medical products to r...","12","2023-06-23 00:00:00","2023-07-26 20:15:55","FDA" +"190","UNC Eshelman School of Pharmacy","unc-eshelman-school-of-pharmacy","logo/unc.png","https://pharmacy.unc.edu/","Everything we do begins and ends with a patient in mind. Developing leaders in pharmacy education, pharmacy practice and pharmaceutical sciences who make a difference in human health worldwide.","1","2023-06-23 00:00:00","2023-07-26 20:15:56","" +"191","University of Alabama","ua","logo/ua.png","https://www.ua.edu/","We are dedicated to excellence in teaching, research and service. We provide a robust campus environment where our students can reach their greatest potential while learning from the best and brightest faculty and making a positive difference in the community, the state and the world.","1","2023-06-23 00:00:00","2023-07-26 20:15:57","UA" +"192","University of Alabama at Birmingham","uab","logo/uab.jpg","https://www.uab.edu/home/","At UAB, we have never settled on merely finding what's next—we have helped build the future through new ideas and initiatives in the classroom, the laboratory, the studio and the clinic.","1","2023-06-23 00:00:00","2023-07-26 20:15:58","UAB" +"193","University of Arkansas for Medical Sciences","uams","logo/uams.jpg","https://www.uams.edu/","By 2029, the University of Arkansas for Medical Sciences (UAMS) will lead Arkansas to be the healthiest state in the region through its synergies of education, clinical care, research and purposeful leadership. With this bold statement, UAMS resolved that in the coming decade its status as Arkansas' only academic health system will allow it to deliver dramatic and lasting health and health care improvements to its home state. Aiding in this vision will be its statewide network of campuses for public education and clinical outreach, along with cores of expertise in medical specialties, population health, digital health, health informatics and translational research.","1","2023-06-23 00:00:00","2023-07-26 20:15:59","UAMS" +"194","University of Basel","university-of-basel","logo/uni_basel.svg","https://www.unibas.ch/en.html","As a comprehensive university offering a wide range of high-quality educational opportunities, the University of Basel attracts students from Switzerland and the entire world, offering them outstanding studying conditions as they work towards their bachelor's, master's or PhD degrees. Today, the University of Basel has around 13,000 students from over a hundred nations, including 2,900 PhD students. The University of Basel has seven faculties covering a wide spectrum of academic disciplines. At the same time, the university has positioned itself amidst the international competition in the form of five strategic focal areas: Life Sciences, Visual Studies, Nanosciences, Sustainability and Energy Research and European and Global Studies. In international rankings, the University of Basel is regularly placed among the 100 top universities in the world thanks to its research achievements. The University of Basel has deep roots in the economically powerful and culturally rich Basel re...","3","2023-06-23 00:00:00","2023-10-16 21:34:12","" +"195","University of California, San Diego","ucsd","logo/ucsd.png","https://ucsd.edu/","We make changemakers. Recognized as one of the top 15 research universities worldwide, our culture of collaboration sparks discoveries that advance society and drive economic impact. Everything we do is dedicated to ensuring our students have the opportunity to become changemakers, equipped with the multidisciplinary tools needed to accelerate answers to our world's most pressing issues.","3","2023-06-23 00:00:00","2023-08-08 18:48:47","UCSD" +"196","University of California, San Francisco","ucsf","logo/ucsf.svg","https://www.ucsf.edu/","At UC San Francisco, we are driven by the idea that when the best research, the best teaching and the best patient care converge, we can deliver breakthroughs that help heal the world. Excellence is in our DNA. From genomics and immunology to specialty care for women and children, UCSF brings together the world's leading experts in nearly every area of health. We are home to five Nobel laureates who have advanced the understanding of cancer, neurodegenerative diseases, aging and stem cells. Our hospitals and educational programs consistently rank among the best in the country, according to the latest surveys by U.S. News & World Report. We are the leading university dedicated exclusively to the health sciences.","12","2023-06-23 00:00:00","2023-08-08 18:48:39","UCSF" +"197","University of California, Santa Cruz","ucsc","logo/uc-santa-cruz-2021.svg","https://www.ucsc.edu/","An inspired, global, public research university leading at the intersection of innovation and justice.","8","2023-06-23 00:00:00","2023-08-08 18:48:44","UCSC" +"198","University of Cincinnati","uc","logo/uc.png","https://www.uc.edu/","The University of Cincinnati offers students a balance of educational excellence and real-world experience. UC is a public research university with an enrollment of nearly 48,000 students and is ranked No. 4 in the nation for co-ops and internships by U.S. News & World Report (No. 1 among public institutions). Today, more than 315,000 living alumni count themselves as Bearcats — united not just by their loyalty to our nationally known sports teams, but by their common love of the place, the people and the ideas that make up the University of Cincinnati.","1","2023-06-23 00:00:00","2023-07-26 20:16:03","UC" +"199","University of Colorado Anschutz Medical Campus","cu-anschutz","logo/cu_anschutz.svg","https://www.cuanschutz.edu/","The ​University of Colorado Anschutz Medical Campus is the largest academic health center in the Rocky Mountain region at the forefront of transformative education, science, medicine and healthcare. The campus includes the University of Colorado health professional schools, multiple centers and institutes and two nationally ranked hospitals, UCHealth University of Colorado Hospital and Children's Hospital Colorado, which treat nearly 2 million patients each year. All interconnected, these organizations collaboratively improve the quality of patient care they deliver, research they conduct and health professionals they train.","4","2023-06-23 00:00:00","2023-07-26 20:16:03","" +"200","University of Connecticut","uconn","logo/uconn.png","https://uconn.edu/","Learning and academics are about exploring the things that interest you, growing with that knowledge, and finding the path on which you'll be most successful. With 14 schools and colleges and more than 115+ undergraduate majors, you'll find what you're looking for at UConn. And what if you come up with something unique to study? You can create your own major. Whether you want to learn from the past by studying history or you want to set the course for the future with groundbreaking scientific research, learning opportunities here abound. Challenge yourself to reach new academic heights in rigorous courses taught by our expert faculty. Take advantage of undergraduate research awards including the Summer Undergraduate Research Fund or UConn IDEA Grants; study in a lab; or pursue a creative endeavor. Push yourself further, supplementing traditional coursework with enrichment such as Education Abroad or our acclaimed Honors Program. Whatever you choose, we're here to help you find y...","1","2023-06-23 00:00:00","2023-07-26 20:16:05","UCONN" +"201","University of Houston","uh","logo/uh-primary.svg","https://www.uh.edu/","At the University of Houston, we spur innovation by encouraging the very spark of an idea to the transfer of knowledge and technology. The UH innovation ecosystem has a rich history of advancing Houston's innovation economy.","1","2023-06-23 00:00:00","2023-07-26 20:16:06","UH" +"202","University of Illinois Urbana-Champaign","uiuc","logo/wordmark_horizontal.png","https://illinois.edu/","Illinois students, scholars, and alumni are a community with the power to change the world. With our land-grant heritage as a foundation, we pioneer innovative research that tackles global problems and expands the human experience. Our transformative learning experiences, in and out of the classroom, are designed to produce alumni who desire to make a significant, societal impact.","1","2023-06-23 00:00:00","2023-07-26 20:16:07","UIUC" +"203","University of Kent","kent","logo/ukent.jpeg","https://www.kent.ac.uk/","Welcome to the university of ambition where desire meets determination. We stand for ambition, with our diverse community of staff and students committed to making a difference at regional, national and global level. It's something we're very proud of.","1","2023-06-23 00:00:00","2023-07-26 20:16:07","" +"204","University of Kentucky","uk","logo/uky.png","http://www.uky.edu/","The University of Kentucky has a broad range of resources centered on a single campus in the heart of the Bluegrass. Our wide array of programs allows us to excel in multidisciplinary studies and fosters an environment of cooperative engagement across all colleges, programs, and research endeavors. Because of the lives we touch and teach, we remain anchored in our mission to Kentucky- to educate, innovate, heal, and serve. To be sure, our complex, multi-faceted mission looks different today in many ways than it did in 1865. However, our sense of responsibility to our communities on campus and across the region is resolute. The mission has evolved and grown. The vision of service to our Commonwealth and the world beyond remains the same. They remain our compass -the soul of the University of Kentucky.","1","2023-06-23 00:00:00","2023-10-16 21:36:22","UK" +"205","University of Lausanne","unil","logo/unil-logo.svg","https://www.unil.ch/central/en/home.html","The University of Lausanne is a higher teaching and research institution composed of seven faculties with approximately 17,100 students and about 4,400 research, teaching and technical staff. Its research activities focus on three main themes: human and social sciences, life sciences and medicine, and environmental sciences. UNIL lays great store by the quality and innovation of its teaching. This is characterised by a highly interdisciplinary approach which is even reflected in the organisation of its faculties.","2","2023-06-23 00:00:00","2023-10-16 21:36:30","UNIL" +"206","University of Lisbon","ulisboa","logo/ulisboa.png","https://www.ulisboa.pt/en","Universidade de Lisboa (ULisboa) is the largest and most prestigious university in Portugal and is one of Europe's leading universities. Heir to a university tradition that spans over seven centuries, ULisboa acquired its current status in July 2013, following the merger of the former Universidade Técnica de Lisboa and Universidade de Lisboa. ULisboa brings together various areas of knowledge and has a privileged position for facilitating the contemporary evolution of science, technology, arts and humanities. The quality of teaching, research, innovation and culture of ULisboa is attracting an ever increasing amount of talent from around the world.","2","2023-06-23 00:00:00","2023-07-26 20:16:10","" +"207","University of London","uol","logo/uol.jpg","https://london.ac.uk/","The University of London is the UK's leading provider of digital and blended distance education internationally, offering programmes to 45,000 students in 190 countries around the world. Although proudly rooted in London, our community and impact are global. We are a national leader in the humanities, and we promote their value to society and the economy through knowledge creation and exchange. We are also a federation of 17 esteemed higher education institutions, with collaboration at the heart of our ethos. The University of London federation is a collective community of more than 240,000 learners and 50,000 staff, delivering world-leading research across all disciplines. Our passion for increasing access to education and mobilising the collective power and expertise of the federation is central to our ability to transform lives around the world and address the global challenges of the future.","2","2023-06-23 00:00:00","2023-07-26 20:16:10","UoL" +"208","University of Luxembourg","university-of-luxembourg","logo/university-of-luxembourg.png","https://wwwen.uni.lu/","Founded in 2003, the University of Luxembourg is the only public university of the Grand Duchy of Luxembourg. Multilingual, international and research-oriented, it is also a modern institution with a personal atmosphere.","1","2023-06-23 00:00:00","2023-07-26 20:16:11","" +"209","University of Maryland","umd","logo/umd.png","https://www.umd.edu/","The University of Maryland, College Park is the state's flagship university and one of the nation's preeminent public research universities. A global leader in research, entrepreneurship and innovation, the university is home to more than 40,700 students, 14,000 faculty and staff, and nearly 400,000 alumni all dedicated to the pursuit of Fearless Ideas. Located just outside Washington, D.C., we discover and share new knowledge every day through our renowned research enterprise and programs in academics, the arts and athletics. And we are committed to social entrepreneurship as the nation's first “Do Good” campus.","5","2023-06-23 00:00:00","2023-07-26 20:16:12","UMD" +"210","University of Michigan","umich","logo/block-m-maize.png","https://umich.edu/","Welcome to the University of Michigan, a place with deep traditions focused on creating brighter futures. We invite you to explore the diverse and vibrant community that makes us the home of Leaders & Best. More than any other university, we have the potential to be so much more than the sum of our many excellent parts. It's this potential to have a positive impact on the society we serve that represents our greatest value as a university.","1","2023-06-23 00:00:00","2023-07-26 20:16:14","" +"211","University of North Carolina at Chapel Hill","unc","logo/univ-unc.png","https://www.unc.edu/","The nation's first public university is at the heart of what's next, preparing a diverse student body to become creators, explorers, innovators and leaders in North Carolina and throughout the world. Carolina's nationally recognized, innovative teaching, campus-wide spirit of inquiry and dedication to public service continue the legacy that began in 1795 when the University first opened its doors to students. In Chapel Hill, students develop a voice for critical thought and the courage to guide change. They connect to the future they're already shaping. Carolina is committed to access for all, providing life-changing opportunities such as the Carolina Covenant, which promises a debt-free education to low-income students. In its third century - an era of groundbreaking study and research -UNC-Chapel Hill is harnessing the very best of our fast-changing world. We're proud to advance knowledge for this and each generation to come.","4","2023-06-23 00:00:00","2023-10-16 21:37:47","UNC" +"213","University of Padova","university-of-padova","logo/university-of-padua.jpg","https://www.unipd.it/en/","The University of Padua is one of Europe's oldest and most prestigious seats of learning. As a multi-disciplinary institute of higher education, the University aims to provide its students with professional training and a solid cultural background. The qualification received from the University of Padua act as a symbol of the ambitious objectives respected and coveted by both students and employers alike. Founded in 1222, Padua's Studium Patavinum was a place of study that readily welcomed Italian students and scholars, as well as those from various European countries searching for cultural freedom and expression. This freedom continues to define and express the essence of the University through its motto as Universa universis patavina libertas.","5","2023-06-23 00:00:00","2023-07-26 20:16:16","" +"214","University of Padua","university-of-padua","logo/university-of-padua.jpg","https://www.unipd.it/en/","The University of Padua is one of Europe's oldest and most prestigious seats of learning. As a multi-disciplinary institute of higher education, the University aims to provide its students with professional training and a solid cultural background. The qualification received from the University of Padua act as a symbol of the ambitious objectives respected and coveted by both students and employers alike. Founded in 1222, Padua's Studium Patavinum was a place of study that readily welcomed Italian students and scholars, as well as those from various European countries searching for cultural freedom and expression. This freedom continues to define and express the essence of the University through its motto as Universa universis patavina libertas.","1","2023-06-23 00:00:00","2023-07-26 20:16:17","" +"215","University of Pennsylvania","upenn","logo/upenn.png","https://www.upenn.edu/","Penn's academics are boosted by its inherent culture and ecosystem of innovation. You name it, if it's cutting-edge, the University's faculty—and students—have their hands in it. Grounded in the liberal arts and sciences and enriched by the integrated resources of four undergraduate and 12 graduate schools, Penn offers students an unparalleled education informed by inclusivity, intellectual rigor, research, and the impetus to create new knowledge to the benefit of individuals and communities around the world.","6","2023-06-23 00:00:00","2023-07-26 20:16:17","" +"216","University of Rochester","rochester","logo/rochester.jpeg","https://www.rochester.edu/","One of the world's leading research universities, Rochester has a long tradition of breaking boundaries—always pushing and questioning, learning and unlearning. We transform ideas into enterprises that create value and make the world ever better.","2","2023-06-23 00:00:00","2023-07-26 20:16:18","" +"217","University of South Florida","usf","logo/usf.png","https://www.usf.edu/","Welcome to the University of South Florida. Though a relatively young university, founded in 1956, we have rich traditions - traditions of access and opportunity for students, of academic excellence, of groundbreaking research, of serving our communities.","1","2023-06-23 00:00:00","2023-10-16 21:43:44","USF" +"218","University of Southampton","university-of-southampton","logo/university-of-southampton.png","https://www.southampton.ac.uk/","As a global top 100 university, our expert academics and wide range of study options will help you achieve your goals.","1","2023-06-23 00:00:00","2023-07-26 20:16:21","" +"219","University of Texas Southwestern Medical Center","ut-southwestern","logo/ut-swestern.gif","https://www.utsouthwestern.edu/","UT Southwestern, one of the premier academic medical centers in the nation, integrates pioneering biomedical research with exceptional clinical care and education. The institution's faculty includes many distinguished members, including six who have been awarded Nobel Prizes since 1985. The faculty of more than 2,800 is responsible for groundbreaking medical advances and is committed to translating science-driven research quickly to new clinical treatments. UT Southwestern physicians provide medical care in about 80 specialties to more than 105,000 hospitalized patients, nearly 370,000 emergency room cases, and oversee approximately 3 million outpatient visits a year.","2","2023-06-23 00:00:00","2023-07-26 20:16:21","" +"220","University of Toronto","u-of-t","logo/utoronto.png","https://www.utoronto.ca/","We are proud to be one of the world's top research-intensive universities, bringing together top minds from every conceivable background and discipline to collaborate on the world's most pressing challenges. Our community is a catalyst for discovery, innovation and progress, creating knowledge and solutions that make a tangible difference around the globe. And we prepare our students for success through an outstanding global education rooted in excellence, inclusion and close-knit learning communities. The ideas, innovations and contributions of more than 660,000 graduates advance U of T's impact on communities across the globe. Together, we continue to defy gravity by taking on what might seem unattainable today and generating the ideas and talent needed to build a more equitable, sustainable and prosperous future.","10","2023-06-23 00:00:00","2023-07-26 20:16:21","U of T" +"221","University of Vermont","uvm","logo/the-university-of-vermont.png","https://www.uvm.edu/","UVM is a top research university of ideal size, large enough to offer a breadth of ideas, resources, and opportunities, yet scaled to enable close faculty-student mentorship across all levels of study, from bachelor's to doctoral programs.","1","2023-06-23 00:00:00","2023-07-26 20:16:22","UVM" +"222","University of Verona","university-of-verona","logo/university-of-verona.png","https://www.univr.it/en/international","The University of Verona strives for excellence in teaching, research and innovation. It has 22,000 students and 1,500 staff including lecturers, researchers, technical and administrative personnel who work to continually improve and grow the university. A forward-thinking institution which continuously seeks to strengthen the link between its degree courses and the real world of work, the university's main objective for the near future is to become progressively more welcoming and adapted to student needs.","1","2023-06-23 00:00:00","2023-10-27 20:11:57","" +"223","University of Virginia","uva","logo/uva_primary_logo.jpg","https://www.virginia.edu/","The University is an iconic public institution of higher education, boasting nationally ranked schools and programs, diverse and distinguished faculty, a major academic medical center and proud history as a renowned research university. The community and culture of the University are enriched by active student self-governance, sustained commitment to the arts and a robust NCAA Division I Athletics program.","1","2023-06-23 00:00:00","2023-07-26 20:16:24","UVA" +"224","University of Washington","uw","logo/uw.svg","https://www.washington.edu/","Since our founding in 1861, the University of Washington has been a hub for learning, innovation, problem solving and community building. Driven by a mission to serve the greater good, our students, faculty and staff tackle today's most pressing challenges with courage and creativity, making a difference across Washington state — and around the world.","8","2023-06-23 00:00:00","2023-07-26 20:16:25","UW" +"225","University of Wisconsin-Madison","uw-madison","logo/uw-logo.png","https://www.wisc.edu/","Since its founding in 1848, this campus has been a catalyst for the extraordinary. As a public land-grant university and major research institution, our students, staff, and faculty engage in a world-class education while solving real-world problems. With public service — or as we call it, the Wisconsin Idea — as our guiding principle, Badgers are creating a better future for everyone.","1","2023-06-23 00:00:00","2023-07-26 20:16:26","" +"226","University of Zurich","uzh","logo/uzh.png","https://www.uzh.ch/en.html","With its 28,000 enrolled students, the University of Zurich is Switzerland's largest university. Founded in the year 1833, UZH was Europe's first university to be established by a democratic political system. Made up of seven faculties covering some 100 different subject areas, the University offers a wide variety of Bachelor's, Master's and PhD programs.","4","2023-06-23 00:00:00","2023-07-26 20:16:26","UZH" +"227","Urban Green Energy","uge","logo/ugei-logo.svg","https://www.ugei.com/","Since 2008 when our journey began, we've been focused on expanding utilization of renewable energy. In our early days, we worked on finding use cases for clean energy technologies before they were widely adopted, building projects ranging from wind and solar microgrids in remote locations, to lighting the Eiffel Tower with 100% renewable energy in 2014. Over time we turned our focus entirely to solar and battery storage in the U.S. where we're building a growing portfolio of distributed energy assets, Leaning on more than a decade of experience across 700 projects totaling more than 500 megawatts, we're proud to be making a significant impact on the world's transition to clean energy, and we're just getting started.","1","2023-06-23 00:00:00","2023-07-26 20:16:28","UGE" +"228","US Army Medical Research Institute of Infectious Diseases","usamriid","logo/usarmy.png","https://usamriid.health.mil/","To provide leading edge medical capabilities to deter and defend against current and emerging biological threat agents.","1","2023-06-23 00:00:00","2023-11-21 01:01:14","USAMRIID" +"229","VA Durham Health Care","va-durham-health-care","logo/va-logo-white.png","https://www.durham.va.gov/","Since 1953, Durham Veterans Affairs Medical Center has been improving the health of the men and women who have so proudly served our nation. We consider it our privilege to serve your healthcare needs in any way we can. Services are available to more than 200,000 Veterans living in a 27-county area of central and eastern North Carolina. The VA Durham Healthcare System provides you with outstanding health care, trains America's future health care providers, and conducts important medical research.","2","2023-06-23 00:00:00","2023-07-26 20:16:29","" +"230","Verily","verily","logo/verily.jpeg","https://verily.com/","True, comprehensive health is expanding exponentially. Massive increases in health information & computing power are coinciding with health challenges of a scale & magnitude we've never seen—creating urgency for value-based care and improved outcomes for all. Precision health represents a fundamental shift to health and to care that is more individualized, accessible, and affordable.","1","2023-06-23 00:00:00","2023-07-26 20:16:29","" +"231","VHA Innovation Ecosystem","vha-ie","logo/vaInnovation.jpeg","https://www.innovation.va.gov/ecosystem/views/home.html","VHA Innovation Ecosystem (VHA IE) is the catalyst for enabling the discovery and spread of mission-driven health care innovation that exceeds expectations, restores hope, and builds trust within the Veteran community. VHA IE leverages the collective power of innovation champions from across VA, academia, non-profit and industry to operationalize innovation in the Nation's largest integrated health care system.","3","2023-06-23 00:00:00","2023-07-26 20:16:31","VHA IE" +"232","Washington University in St. Louis","wustl","logo/wustl.png","https://wustl.edu/","At WashU, we generate, disseminate, and apply knowledge. We foster freedom of inquiry and expression of ideas in our research, teaching and learning. We aim to create an environment that encourages and supports wide-ranging exploration at the frontier of discovery by embracing diverse perspectives from individuals of all identities and backgrounds. We promote higher education and rigorous research as a fundamental component of an open, vibrant society. We strive to enhance the lives and livelihoods not only of our students, patients, and employees but also of the people of the greater St. Louis community and beyond. We do so by addressing scientific, social, economic, medical, and other challenges in the local, national, and international realms.","1","2023-06-23 00:00:00","2023-10-14 06:11:40","WUStL" +"233","Wayne State University","wayne-state-university","logo/wayne-state-university.png","https://wayne.edu/","Our mission is to create and advance knowledge, prepare a diverse student body to thrive, and positively impact local and global communities. Our guiding values cut across organizational boundaries, bind us culturally, and permeate our strategic and tactical initiatives. They are the defining traits of the WSU community.","1","2023-06-23 00:00:00","2023-10-14 06:11:38","" +"234","Weizmann Institute of Science","weizmann-institute-of-science","logo/wiz.jpeg","https://www.weizmann.ac.il/pages/","The Weizmann Institute of Science is one of the world's leading multidisciplinary basic research institutions in the natural and exact sciences. It is located in Rehovot, Israel, just south of Tel Aviv. It was initially established as the Daniel Sieff Institute in 1934, by Israel and Rebecca Sieff of London in memory of their son Daniel. In 1949, it was renamed for Dr. Chaim Weizmann, the first President of the State of Israel and Founder of the Institute.","3","2023-06-23 00:00:00","2023-11-20 22:20:49","" +"235","Wellcome Sanger Institute","sanger","logo/sanger.jpeg","https://www.sanger.ac.uk/","We tackle some of the most difficult challenges in genomic research. This demands science at scale; a visionary and creative approach to research that pushes the boundaries of our understanding in ever new and exciting ways.","2","2023-06-23 00:00:00","2023-10-14 06:11:36","" +"236","White House Office of Science and Technology Policy","ostp","logo/ostp.png","https://www.whitehouse.gov/ostp/","President Biden often says, 'America is the only nation that can be defined by a single word: possibilities.' The White House Office of Science and Technology (OSTP) works to bring that idea to life by harnessing the power of science, technology, and innovation to achieve America's greatest aspirations. OSTP's mission includes-a) Providing advice to the President and the Executive Office of the President on matters related to science and technology; b) Strengthening and advancing American science and technology; c) Working with federal departments and agencies and with Congress to create bold visions, unified strategies, clear plans, wise policies, and effective, equitable programs for science and technology; d) Engaging with external partners, including industry, academia, philanthropic organizations, and civil society; state, local, Tribal and territorial governments; and other nations; and, e) Ensuring equity, inclusion, and integrity in all aspects of science and technology.","1","2023-06-23 00:00:00","2023-10-16 21:45:02","OSTP" +"237","InChI Trust","inchi","logo/inchi.png","https://www.inchi-trust.org/","InChI: open-source chemical structure representation algorithm. InChI is a structure-based chemical identifier, originally developed by IUPAC. As a standard identifier for chemical databases, InChI is essential for enabling effective information management across chemistry. InChI with InChIKey are non-proprietary open standards. InChI turns chemical structures into unique machine readable strings, used for describing, storing and searching chemical structures. All associated algorithms and software are open source.","1","2023-06-23 00:00:00","2023-10-16 21:45:06","" +"238","National Center for Toxicological Research","nctr","","https://www.fda.gov/about-fda/office-chief-scientist/national-center-toxicological-research","The National Center for Toxicological Research (NCTR), is the only FDA Center located outside the Washington D.C. metropolitan area. The one-million square foot research campus in Jefferson, Arkansas plays a critical role in the missions of FDA and the Department of Health and Human Services to promote and protect public health. Regulatory science researchers, academia, and other regulatory science research organizations and groups from around the world investigate, learn, and train at the Federal facility. NCTR, FDA's internationally recognized research center, plays a critical role in FDA's mission. The unique scientific expertise of NCTR is critical in supporting FDA product centers and their regulatory roles.","2","2023-06-23 00:00:00","2023-10-14 06:11:34","NCTR" +"239","McGill University","mcgill","logo/mcgill.jpg","https://www.mcgill.ca/","McGill University is one of Canada's best-known institutions of higher learning and one of the leading universities in the world. International students from more than 150 countries make up nearly 30% of McGill's student body ‒ the highest proportion of any Canadian research university.","1","2023-06-23 00:00:00","2023-10-14 06:11:32","" +"240","Medical Artificial Intelligence Lab","mai-lab","logo/mai-lab.jpg","https://mailab.io/","We are a leading ecosystem for data science and artificial intelligence (AI) innovations in medical diagnostic imaging. Our lab is dedicated to creating AI solutions and data science applications to transform the healthcare landscape of countries in Africa. We are a team of scientists from around the world working locally to disrupt healthcare challenges in resourced limited settings by implementing AI innovations in Africa where it has the most potential.","1","2023-06-23 00:00:00","2023-10-14 06:11:31","" +"241","Duke University Medical Center","duke-health","logo/duke-health.jpg","https://www.dukehealth.org/locations/duke-university-medical-center","Duke University Medical Center is the name given to the group of patient care, education and medical research facilities on the medical campus of Duke University in Durham, North Carolina.","1","2023-06-23 00:00:00","2023-10-14 06:11:30","" +"242","Yale University","yale","logo/yale.jpg","https://www.yale.edu/","Since its founding in 1701, Yale has been dedicated to expanding and sharing knowledge, inspiring innovation, and preserving cultural and scientific information for future generations. Yale’s reach is both local and international. It partners with its hometown of New Haven, Connecticut to strengthen the city’s community and economy. And it engages with people and institutions across the globe in the quest to promote cultural understanding, improve the human condition, delve more deeply into the secrets of the universe, and train the next generation of world leaders.","3","2023-06-23 00:00:00","2023-10-14 06:11:26","" +"243","Missouri University","mizzou","logo/mizzou.jpg","https://missouri.edu/","Top 5 reasons to choose Mizzou: 1) U.S. News & World Report ranked Mizzou the #1 Best Value among Midwest flagships; 2) 95% of Mizzou graduates are successful within six months of graduation; 3) Mizzou offers all undergraduate students real-life experiences and hands-on learning in their field; 4) Mizzou’s graduation rate is 75%; 5) Columbia, Missouri, is consistently ranked one of the best college towns in the country","1","2023-06-23 00:00:00","2023-11-21 01:00:27","" +"244","Yale School of Medicine","ysm","logo/ysm.png","https://medicine.yale.edu/","Yale School of Medicine educates and nurtures creative leaders in medicine and science, promoting curiosity and critical inquiry in an inclusive environment enriched by diversity. We advance discovery and innovation fostered by partnerships across the university, our local community, and the world. We care for patients with compassion, and commit to improving the health of all people.","1","2023-06-23 00:00:00","2023-11-21 00:59:51","YSM" +"245","Children's National Hospital","childrens-national","logo/childrens-national.jpg","https://childrensnational.org/","Children's National Hospital is ranked #5 in the nation by U.S. News & World Report. We're ranked #1 for newborns and we're the best pediatric hospital for neurology and neurosurgery in the Mid-Atlantic. What's more, we ranked in all 10 specialties, with top 10 honors in neurology and neurosurgery, cancer, nephrology, orthopedics, pulmonology and lung surgery, and diabetes and endocrinology. This recognition of our commitment to bringing health and well-being to all children continues to inspire our teams.","1","2023-06-23 00:00:00","2023-07-26 20:16:42","" +"246","Helmholtz AI","helmholtz-ai","logo/helmholtz-ai.jpg","https://www.helmholtz.ai/","We are a research-driven hub for applied artificial intelligence (AI) that: a) fosters cross-field creativity by stimulating collaborative research projects; b) identifies and leverages similarities between applications to advance generalised AI / machine learning (ML) methods; c) integrates field-specific excellence and AI/ML prowess; d) improves the quality, scalability and timely availability of emerging methods and tools; and e) empowers and trains the current and next generation of scientists, to enable the efficient and agile development and implementation of AI/ML assets across the whole Helmholtz Association.","1","2023-06-23 00:00:00","2023-11-21 01:03:10","" +"247","Mayo Clinic","mayo-clinic","logo/mayo-clinic.png","https://www.mayoclinic.org/","Mayo Clinic is a nonprofit organization committed to clinical practice, education and research, providing expert, whole-person care to everyone who needs healing.","6","2023-06-23 00:00:00","2023-07-26 20:16:43","" +"248","Technical University of Munich","tum","logo/tum.jpg","https://www.tum.de/en/","TUM has once again been named a University of Excellence and is thus the only technical university to continuously retain this status since 2006. The title is awarded as a part of the Excellence Strategy of the German federal and state governments, in strategic international support of German cutting-edge research. We are using this funding to realize the future concept TUM Agenda 2030. We are expanding technically-oriented humanities and social sciences and are reorganizing previous internal structures to be more innovation-oriented: The constraining, discipline-based Faculty structure is being replaced by seven Schools which are linked to one another by integrative research institutes. In the sense of an ""open marketplace of knowledge"", we support talented individuals in all their diversity, at all levels and across substantive subject boundaries. We work in alliances with international partners to re-orient towards Europe as well as to the southern global hemisphere in order t...","2","2023-06-23 00:00:00","2023-10-16 21:46:32","TUM" +"249","Center for Devices and Radiological Health","cdrh","logo/fda.svg","https://www.fda.gov/about-fda/fda-organization/center-devices-and-radiological-health","In keeping with our mission, the Center for Devices and Radiological Health (CDRH) is responsible for protecting and promoting the public health. We assure that patients and providers have timely and continued access to safe, effective, and high-quality medical devices and safe radiation-emitting products. We provide consumers, patients, their caregivers, and providers with understandable and accessible science-based information about the products we oversee. We facilitate medical device innovation by advancing regulatory science, providing industry with predictable, consistent, transparent, and efficient regulatory pathways, and assuring consumer confidence in devices marketed in the U.S. We seek to continually improve our effectiveness in fulfilling our mission by planning strategically and regularly monitoring our progress.","2","2023-06-23 00:00:00","2023-08-10 21:36:27","CDRH" +"250","Lagos State University Teaching Hospital","lasuth","logo/lasuth.jpg","https://www.lasuth.org.ng/","To provide high quality Healthcare Services in a friendly Environment where patients' satisfaction is the ultimate. Guided by the needs of our patients and their families, we aim to deliver the very best health care in a safe and compassionate environment; to advance care through innovative research and education; and to improve the health and well-being of the diverse communities we serve.","1","2023-06-23 00:00:00","2023-07-26 20:16:45","LASUTH" +"251","NSIA-Kano Diagnostic Center","nkdc","logo/nkdc.jpeg","https://www.nhdic.ng/facility/nkdc/","The NKDC medical diagnostics facility opened its doors to the public on the 16th of March, 2020, in Kano - Northern Nigeria’s commercial centre. This state-of-the-art facility is home to a group of enthusiastic, passionate and patient-centric medical professionals who continuously aim to improve patient experiences. We offer 24/7 radiology and medical laboratory services all year round.","1","2023-06-23 00:00:00","2023-10-16 21:47:10","NKDC" +"252","Nationwide Children's Hospital","nationwide-childrens","logo/nationwide-childrens.jpg","https://www.nationwidechildrens.org/","At Nationwide Children’s Hospital, our vision remains unchanged. We aspire to create the best outcomes for children everywhere. This means families come to Nationwide Children’s from around the globe knowing they will get the highest quality care. It means we will reach to cure rare diseases. It means we will sequence a child’s tumor to select the best care pathway. It means we will strive to make an entire population healthier, not just through their physical health, but also in their mental health. It means we will redefine the role of the children’s hospital in the achievement of optimal health.","1","2023-06-23 00:00:00","2023-07-26 20:16:46","" +"253","Dana-Farber Brigham Cancer Center","dana-farber-brigham-cancer-center","logo/bwh.png","https://www.brighamandwomens.org/cancer","At Dana-Farber Brigham Cancer Center, all we do is cancer. Because no two people are the same, our approach to treatment and care is personalized - with a deep understanding of your cancer and how to get you well. Through our 12 specialized disease treatment centers, experts from our two organizations, Dana-Farber Cancer Institute and Brigham and Women’s Hospital, work together as one team to offer the most advanced treatments with compassion and care that makes all the difference.","1","2023-06-23 00:00:00","2023-10-16 21:47:47","" +"254","Lacunda Fund","lacunda-fund","logo/lacuna-fund.jpg","https://lacunafund.org/","Lacuna Fund is the world’s first collaborative effort to provide data scientists, researchers, and social entrepreneurs in low- and middle-income contexts globally with the resources they need to produce labeled datasets that address urgent problems in their communities.","1","2023-06-23 00:00:00","2023-10-16 21:55:03","" +"255","MLCommons","mlcommons","logo/mlc.jpg","https://mlcommons.org/en/","The mission of MLCommons(R) is to accelerate machine learning innovation and increase its positive impact on society. Together with its 50+ founding Members and Affiliates, including startups, leading companies, academics, and non-profits from around the globe, MLCommons will help grow machine learning from a research field into a mature industry through benchmarks, public datasets and best practices. Every major technological advance follows a similar trajectory towards universal adoption and impact. The arc from research to broad accessibility generally takes from 30-40 years: from early automobiles to the family car, from development of ARPANET to the mainstream World Wide Web, from the first cellular phones to an smartphone in every pocket. Each of these examples started with technological breakthroughs, but for decades was limited by expertise, access, and expense. Machine learning is no different. ML and artificial intelligence have been around for decades, but even today ...","1","2023-06-23 00:00:00","2023-10-16 21:55:21","" +"256","Harvard Medical School","hms","logo/hms.jpg","https://hms.harvard.edu/","Since the School was established in 1782, faculty members have improved human health by innovating in their roles as physicians, mentors and scholars. They’ve piloted educational models, developed new curricula to address emerging needs in health care, and produced thousands of leaders and compassionate caregivers who are shaping the fields of science and medicine throughout the world with their expertise and passion.","8","2023-08-04 06:00:47","2023-08-04 23:38:09","HMS" +"257","Centre for Structural Systems Biology","cssb","logo/cssb.jpeg","https://www.cssb-hamburg.de/","CSSB is a joint initiative of nine research partners from Northern Germany, including three universities and six research institutes that devotes itself to infection biology research.","1","2023-08-04 22:00:31","2023-10-16 20:44:20","CSSB" +"258","University Medical Center Groningen","umcg","logo/umcg.jpg","https://www.umcg.nl/","The University Medical Center Groningen (UMCG) is one of the largest hospitals in the Netherlands and is the largest employer in the Northern Netherlands. The more than 12,000 employees work together on care, research, training and education with the common goal: building the future of health.","1","2023-08-04 22:07:45","2023-10-16 21:55:55","UMCG" +"259","Eindhoven University of Technology","tue","logo/tue.jpeg","https://www.tue.nl/en/","We educate students and advance knowledge in science & technology for the benefit of humanity. We integrate education and research to enable our students and scientists to become thought leaders and to design and achieve the unimaginable. In close collaboration with our public and private partners, we translate our basic research into meaningful solutions.","2","2023-08-04 22:12:40","2023-10-16 20:47:30","TU/e" +"260","Wageningen University & Research","wur","logo/wur.jpeg","https://www.wur.nl/en.htm","Wageningen University & Research is a collaboration between Wageningen University and the Wageningen Research foundation. ""To explore the potential of nature to improve the quality of life"". That is the mission of Wageningen University & Research. Over 7,600 employees, 13,100 students and over 150.000 participants to WUR’s Life Long Learning from more than hundred countries work everywhere around the world in the domain of healthy food and living environment for governments and the business community-at-large. The strength of Wageningen University & Research lies in its ability to join the forces of specialised research institutes and the university. It also lies in the combined efforts of the various fields of natural and social sciences. This union of expertise leads to scientific breakthroughs that can quickly be put into practice and be incorporated into education. This is the Wageningen Approach. Collaboration with other parties such as government, business and NGOs is indi...","1","2023-08-04 22:15:19","2023-11-21 00:58:32","WUR" +"261","University Medical Center Utrecht","umc-utrecht","logo/umc-utrecht.jpeg","https://www.umcutrecht.nl/en/research","In the UMC Utrecht research is concentrated in six strategic programs with each a limited number of disease targets. Patient care is integrated in these programs. A relentless multidisciplinary approach guarantees patients benefit from the latest available expertise and innovative technological solutions.","6","2023-08-04 22:16:49","2023-10-16 20:48:54","" +"262","Amsterdam University Medical Centers","amsterdam-umc","logo/amsterdam-umc.jpeg","https://www.amsterdamumc.org/en.htm","Amsterdam UMC is a leading medical center that combines complex high-quality patient care, innovative scientific research, and education of the next generation health care professionals. We believe that health care practice, research and education belong together, with each shaping and informing the other.","1","2023-08-04 22:19:22","2023-10-16 20:55:48","" +"263","Maastricht University","um","logo/um.jpg","https://www.maastrichtuniversity.nl/","Maastricht University (UM) is the most international university in the Netherlands and, with nearly 22,000 students and 4,400 employees, is still growing. The university distinguishes itself with its innovative education model, international character and multidisciplinary approach to research and education.","1","2023-08-04 22:24:47","2023-11-20 21:09:18","UM" +"264","Delft University of Technology","tu-delft","logo/tu-delft.jpg","https://www.tudelft.nl/en/","Top education and research are at the heart of the oldest and largest technical university in the Netherlands. Our 8 faculties offer 16 bachelor's and more than 30 master's programmes. Our more than 25,000 students and 6,000 employees share a fascination for science, design and technology. Our common mission: impact for a better society.","1","2023-08-04 23:14:17","2023-11-20 21:09:23","" +"265","Alliance of TU/e, WUR, UU and UMC Utrecht","ewuu","logo/ewuu.jpg","https://ewuu.nl/en/","In 2019 Eindhoven University of Technology, Wageningen University & Research, Utrecht University and University Medical Centre Utrecht decided to form an alliance and to work together. The motto of this strategic collaboration is challenging future generations. Young researchers, lecturers and students are at the helm and work together right across disciplines. The challenges future generations will face are large but so are the possibilities for meeting those challenges. The institutions combine their expertise in order to contribute to social transitions in energy, sustainability, health and food.","1","2023-08-04 23:17:20","2023-11-20 21:09:39","EWUU" +"266","Utrecht University","uu","logo/uu.jpeg","https://www.uu.nl/en","We are Utrecht University. The place for new collaborations and cross-pollination. Students, academic and administrative staff, policymakers, members of the public, professionals and business owners; you are invited to contribute to a better world.","1","2023-08-04 23:19:33","2023-11-20 21:09:43","UU" +"267","Surgical Science","surgical-science","logo/surgical-science.png","https://surgicalscience.com/","Training without putting patients at risk. This is why we exist - to give surgeons an excellent platform to train in the fundamental technical skills before entering the operation room. For over 20 years, we have been committed to providing state-of-the-art medical training simulators that focus on ease of use and validation. The simple idea is to learn the practical techniques of instrument handling in a realistic but safe environment so that you can pay full attention to the patient when you begin the operation.","1","2023-08-04 23:51:56","2023-11-20 21:09:49","" +"268","Wellcome/EPSRC Centre for Interventional and Surgical Sciences","weiss","logo/weiss.jpg","https://www.ucl.ac.uk/interventional-surgical-sciences","At the Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), engineers, clinicians and scientists work together to develop technologies that enable safer and more effective treatments for patients across a wide range of conditions. The Centre is based at Charles Bell House, a building that brings together researchers from a wide range of departments at UCL, including Medical Physics and Biomedical Engineering, Computer Science and Mechanical Engineering. These academic researchers work in partnership with clinical researchers from areas such as the UCL Division of Surgery & Interventional Sciences and leading hospitals. At WEISS, research is being developed with a wide range of clinical applications in mind, including cardiovascular, paediatric, ophthalmic, neurological and urological surgical interventions. In particular, the Centre aims to advance engineering sciences in intraoperative imaging and sensing, data fusion and extraction, human-technology interfa...","1","2023-08-05 00:00:44","2023-11-20 21:09:54","WEISS" +"269","Medtronic","medtronic","logo/medtronic.png","https://www.medtronic.com/us-en/index.html","Health tech for a better future. From AI to connected care and beyond, our technology is building a bridge to better health for more people.","1","2023-08-05 00:02:47","2023-11-20 21:09:56","" +"270","King's College Hopistal","kch","logo/kch.jpg","https://www.kch.nhs.uk/","We are one of London’s largest and busiest teaching hospitals. We provide a strong profile of local hospital services for people living in the boroughs of Lambeth, Southwark, Lewisham, and Bromley. Our specialist services are also available to patients from a wider area. We providing nationally and internationally recognised treatment and care in liver disease and transplantation, neurosciences, haemato-oncology, and fetal medicine. Our vision is to be bold, and our new Trust values - Kind, Respectful Team - help ensure we bring a positive attitude to the way we interact with patients, relatives, and the many people who use our services.","2","2023-08-05 00:08:37","2023-11-20 21:44:33","KCH" +"271","Western University","western","logo/western.jpg","https://www.uwo.ca/index.html","We are a leading research-intensive university and global community of individuals focused on making change in the world, today.","1","2023-08-05 00:10:52","2023-11-21 00:57:43","" +"272","Robarts Research Institute","robarts","logo/robarts.jpg","https://www.robarts.ca/","Opened in 1986, Robarts Research Institute at Western University is a medical research facility in London, Ontario, with more than 600 people working to investigate some of the most debilitating diseases of our time, from heart disease and stroke to diabetes, Alzheimer’s and many forms of cancer. We believe we’ve got a winning formula to accelerate medical discovery: attract the brightest and best people, give them the freedom to think big and set the bar high. From our roots under the scientific leadership of renowned neurologist Dr. Henry Barnett - whose work with Aspirin as a preventive therapy for heart attack and stroke remains one of the most important developments in 20th century medicine - the Institute has applied that formula to become a national leader in biological, clinical and imaging research.","1","2023-08-05 00:12:27","2023-11-20 21:44:48","" +"273","British Acoustic Neuroma Association","bana-uk","logo/bana-uk.jpeg","https://www.bana-uk.com/","BANA was formed in 1992 by a group of patients and their partners. They were introduced to each other by ENT and Neurosurgeon Consultants from the Queen’s Medical Centre Hospital in Nottingham and from the very beginning, mutual support was their primary aim. They also wanted to provide reliable information to those diagnosed and to promote research into Acoustic Neuromas and the effects associated with them. More than two decades on, these fledgling intentions remain the charitable objectives that drive the charity forward on behalf of all those affected.","1","2023-08-05 00:15:03","2023-11-21 01:19:09","BANA" +"274","Ninewells Hospital","ninewells-hospital","logo/nhs-tayside.png","https://www.nhstayside.scot.nhs.uk/GoingToHospital/OurPremisesA-Z/NinewellsHospital/index.htm","","1","2023-08-05 00:20:05","2023-11-20 21:45:07","" +"275","Universal Protein Resource","uniprot","logo/uniprot.jpg","https://www.uniprot.org/","The Universal Protein Resource (UniProt) is a comprehensive resource for protein sequence and annotation data. The UniProt databases are the UniProt Knowledgebase (UniProtKB), the UniProt Reference Clusters (UniRef), and the UniProt Archive (UniParc). The UniProt consortium and host institutions EMBL-EBI, SIB and PIR are committed to the long-term preservation of the UniProt databases.","1","2023-08-05 05:21:46","2023-11-20 21:45:11","" +"276","Charing Cross Hospital","charing-cross-hospital","logo/imperial-nhs.jpg","https://www.imperial.nhs.uk/our-locations/charing-cross-hospital","Charing Cross Hospital provides a range of acute and specialist services, a 24/7 accident and emergency department and hosts the hyper acute stroke unit for the region. It is also a growing hub for integrated care in partnership with local GPs and community providers.","1","2023-08-05 05:27:03","2023-11-20 21:45:20","" +"277","Elisabeth-TweeSteden Hospital","etz","logo/etz.jpg","https://www.etz.nl/","The ETZ (Elisabeth-TweeSteden Hospital) is a top clinical teaching hospital and trauma center. With three locations in Tilburg and Waalwijk, ETZ is the hospital for all residents of the Central Brabant region, but also (far) beyond.","1","2023-08-05 05:28:21","2023-11-20 21:45:23","ETZ" +"278","InVitro Cell Research","icr","logo/icr.png","https://invitrocellresearch.com/","Founded in 2015, InVitro Cell Research, LLC (ICR) is a privately funded company focused on regenerative and preventive personalized medicine. We are dedicated to discovering and developing interventions to slow and reverse biological aging and prevent major age-related diseases. While our offices and labs in the greater New York City area offer over 15,000 square feet of state-of-the-art research space, our scientists set us apart and make us special. They help guide and define our mission. What is our mission? Researching how to repair aging people, fast.","1","2023-08-05 05:33:19","2023-11-20 21:45:29","ICR" +"279","Accelerating Medicines Partnership(R) Parkinson's Disease","amp-pd","logo/amp-pd.png","https://www.amp-pd.org/","The Accelerating Medicines Partnership(R) (AMP(R)) program is a public-private partnership between the National Institutes of Health (NIH), multiple biopharmaceutical and life sciences companies, and non-profit organizations. Managed through the Foundation for the NIH (FNIH), AMP aims to identify and validate the most promising biological targets for therapeutics. Disease areas covered by AMP at the launch of this site include Alzheimer’s disease, type 2 diabetes, the autoimmune disorders of rheumatoid arthritis and systemic lupus erythematosus (lupus) and Parkinson’s disease. Additional disease areas are being evaluated for addition to AMP.","1","2023-08-05 05:39:55","2023-11-20 21:45:38","AMP-PD" +"280","Vanderbilt University","vanderbilt","logo/vanderbilt.jpg","https://www.vanderbilt.edu/","From its founding in 1873 as an institution devoted to “strengthening the ties which should exist between all sections of our common country,” Vanderbilt University has forged a tradition of academic excellence infused with a unique spirit of collaboration and collegiality. Our mission lies in the quest to bring out the best in humanity—pushing new ideas into the frontiers of discovery, challenging the limits of what’s possible and working diligently in the service of others. Vanderbilt’s closely connected park-like campus, set in the heart of the rapidly growing city of Nashville, Tennessee, is representative of the enduring bonds that unite us as One Vanderbilt community.","1","2023-08-07 20:28:32","2023-11-20 21:45:45","" +"281","Basque Center On Cognition, Brain and Language","bcbl","logo/bcbl.jpg","https://www.bcbl.eu/en","Our research aims to unravel the neurocognitive mechanisms involved in the acquisition, comprehension and production of language, with special emphasis on bilingualism and multilingualism. We study processes involved in normal child language acquisition and second language learning in adults, as well as learning disorders, language disorders, language-related effects of aging and neurodegeneration and language use in different social contexts.","1","2023-08-07 20:29:41","2023-11-20 21:45:52","BCBL" +"282","Erasmus Medical Center","emc","logo/emc.jpeg","https://www.erasmusmc.nl/en/","We are Erasmus MC. Every day our staff, volunteers, and students work with dedication and commitment and are passionate about everything that we stand for.","3","2023-08-07 20:31:10","2023-11-20 21:45:58","EMC" +"283","Indiana University","iu","logo/iu.jpg","https://www.iu.edu/index.html","IU is home to top-ranked business and music schools. We’re home to the world’s first school of philanthropy, the nation’s first school of informatics, and the country’s largest medical school. Our hundreds of academic programs are among the world’s best, and we’re always looking toward the horizon, thinking about what’s next. To better prepare our students for the careers of tomorrow, we’ve launched or reconfigured 10 schools in the last decade, and we’re constantly adding new academic programs, like IU Bloomington’s Intelligent Systems Engineering program and IU Online’s 100% virtual Master of Science in Educational Technology for Learning.","2","2023-08-08 17:26:11","2023-11-20 21:46:01","IU" +"284","Science for Life Laboratory","scilifelab","logo/scilifelab.jpg","https://www.scilifelab.se/","SciLifeLab, Science for Life Laboratory, is an institution for the advancement of molecular biosciences in Sweden. We are funded as a national research infrastructure by the Swedish government. Our organization leverages the unique strengths of individual researchers across Sweden into a focused resource for the life science community. We provide access for thousands of researchers to the cutting-edge instrumentation and deep scientific expertise necessary to be internationally competitive in bioscience research. This infrastructure is supported and developed by our research community, including internationally recognized experts in life science and technology. Our units and expertise create a unique environment for carrying out health and environmental research at the highest level. SciLifeLab started out in 2010 as a joint effort between four universities: Karolinska Institutet, KTH Royal Institute of Technology, Stockholm University and Uppsala University. Today, we support re...","1","2023-08-08 17:26:35","2023-11-20 22:13:23","" +"285","Uppsala University","uppsala","logo/uppsala.jpg","https://www.uu.se/en","Uppsala University was founded in 1477. Today it is a strong, comprehensive research university ranked among the best in the world, with 50,000 students and close to 5,000 researchers.","1","2023-08-08 17:28:30","2023-11-21 01:19:20","UU" +"286","Google LLC","google","logo/google.jpg","https://about.google/","Our mission is to organize the world’s information and make it universally accessible and useful.","3","2023-08-08 17:29:33","2023-11-20 22:25:44","" +"287","Precision Value & Health","precision-value-&-health","logo/precision-value-health.jpeg","https://www.precisionvaluehealth.com/","Across the commercialization continuum, Precision Value & Health teams are focused on transforming data for health and leveraging evidence and insights to tailor communications for every stakeholder. From payers to health systems, scientists to healthcare providers, and consumers to advocates, our results are designed to shift the trajectory and accelerate your success. Precision Value & Health’s teams include PRECISIONadvisors (global pricing and market access strategy), PRECISIONeffect (branding and launch experts), PRECISIONheor (evidence generation and strategy), PRECISIONscientia (medical communications), PRECISIONvalue (managed markets marketing), and PRECISIONxtract (data-driven solutions and engagement).","1","2023-08-08 17:37:16","2023-11-20 22:25:52","" +"288","STLogics","stlogics","logo/stlogics.jpg","https://www.stlogics.com/index.html","The STLogics Team has over 60 years of combined business experience to share. This broad business savvy enables our team to provide mentorship to those seeking to enhance the velocity of their trajectory to success. We can assist from small start-up initiatives to large corporations with our keen management skills and futuristic thinking capabilities. If your organization desires growth optimization or is entertaining the thought of acquisition consultation or a merger, STLogics can propel your revolutionary vision to reality. STLogics Holding Company provides operational and strategic advice to our affiliates in an effort to enhance their effectiveness and growth. We simply support and nurture our family of companies to enable them to maximize service to their clients. Our goal is to expand and diversify over various verticals, thus allowing us to foster innovation and create optimal results for client needs.","1","2023-08-08 17:41:14","2023-11-20 22:25:56","" +"289","Conference Ventures","conference-ventures","","http://conferenceventures.com/","This organization may no longer exist, has rebranded, or has been merged under another organization.","1","2023-08-08 17:44:00","2023-11-20 22:26:05","" +"290","Google Brain","google-brain","logo/google-ai.jpg","https://research.google/teams/brain/","This organization may no longer exist, has rebranded, or has been merged under another organization.","1","2023-08-08 17:56:04","2023-11-20 22:26:10","" +"291","Princeton University","princeton","logo/princeton.jpg","https://www.princeton.edu/","Princeton is about people. Our University is enriched by the wide range of experiences and perspectives of our students, faculty, staff and alumni.","1","2023-08-08 18:02:09","2023-11-20 22:26:14","" +"292","Prairie View A&M University","pvamu","logo/pvamu.jpg","https://www.pvamu.edu/","Welcome to Prairie View A&M University, home of the Panthers. Our HBCU, affectionately known as “The Hill,” is deeply rooted in culture & tradition and provides an undeniable educational experience to more than 9,000 diverse students on one of the most beautiful campuses in the state of Texas. Our award-winning faculty work diligently to create challenging and rewarding experiences that inspire you to dream big and soar to new heights. Are YOU ready to EXPERIENCE PVAMU?","1","2023-08-08 18:17:53","2023-11-20 22:26:19","PVAMU" +"293","University of California, Berkeley","berkeley","logo/berkeley.png","https://www.berkeley.edu/","From a group of academic pioneers in 1868 to the Free Speech Movement in 1964, Berkeley is a place where the brightest minds from across the globe come together to explore, ask questions and improve the world.","4","2023-08-08 18:48:17","2023-11-20 22:26:32","" +"294","Center for Genetically Engineered Materials","c-gem","logo/c-gem.jpg","https://gem-net.net/","C-GEM is establishing a fundamentally new way to program chemical matter and transform the way scientists design and produce materials and medicines. Using computation and experiment, C-GEM is repurposing nature’s protein synthesizing machine–the ribosome and its associated translation factors–to biosynthesize genetically encoded, sequence-defined chemical polymers with unprecedented functions and activities. Our combined activities span the fields of chemical biology, synthetic biology, synthetic chemistry, structural biology, computational biology, and molecular biology, and are highly collaborative. To catalyze these efforts, C-GEM implemented GEM-NET, a sophisticated data management system to promote data sharing within and outside the team, and with industry, the NSF, and the public. By fostering innovation at the chemical-biology-materials frontier, C-GEM is establishing a diverse chemical workforce, perfecting the integration of research with training, and captivating scien...","1","2023-08-08 19:14:43","2023-11-20 22:26:35","C-GEM" +"295","Oregon State University","oregon-state","logo/oregon-state.jpg","https://oregonstate.edu/","Oregon State University is a dynamic community of dreamers, doers, problem-solvers and change-makers. We don’t wait for challenges to present themselves — we seek them out and take them on. We welcome students, faculty and staff from every background and perspective into a community where everyone feels seen and heard. We have deep-rooted mindfulness for the natural world and all who depend on it, and together, we apply knowledge, tools and skills to build a better future for all.","1","2023-08-08 19:23:28","2023-11-21 01:19:26","OSU" +"296","Laboratory for Innovation Science at Harvard","lish","logo/lish.jpg","https://lish.harvard.edu/","The Laboratory for Innovation Science at Harvard (LISH) is spurring the development of a science of innovation through a systematic program of solving real-world innovation challenges while simultaneously conducting rigorous scientific research and analysis. LISH is a Harvard-wide research program led by faculty co-directors Karim Lakhani, Harvard Business School; Eva Guinan, Harvard Medical School; David Parkes, Harvard School of Engineering and Applied Sciences; and Kyle Myers, Harvard Business School; with support from the Institute for Quantitative Social Science. With our partners in both academia and industry, LISH conducts research on innovation within three areas of application: Crowdsourcing & Open Innovation; Data Science & AI Development; and Science of Science; addressing questions under three main research tracks-Incentives & Governance; Creativity & Problem-Solving; and Organization & Processes.","1","2023-08-08 19:24:59","2023-11-20 22:26:44","LISH" +"297","NIH Common Funds Library of Integrated Network-Based Cellular Signatures","lincs","logo/lincs-program.jpg","https://lincsproject.org/LINCS/","The LINCS project is based on the premise that disrupting any one of the many steps of a given biological process will cause related changes in the molecular and cellular characteristics, behavior, and/or function of the cell - the observable composite of which is known as the cellular phenotype. Observing how and when a cell’s phenotype is altered by specific stressors can provide clues about the underlying mechanisms involved in perturbation and, ultimately, disease.","1","2023-08-08 19:25:32","2023-11-20 22:26:48","LINCS" +"298","Recursion Pharmaceuticals","recursion","logo/recursion.jpg","https://www.recursion.com/","From our earliest days, our story was unlikely. We are a company started by two graduate students and a professor, headquartered in Salt Lake City, Utah. Our humble and unlikely beginnings are foundational to what we’ve built today. We were underdogs, and felt that way. Now we are leaders in this space, and we vow to stay hungry and focused on our mission. We are a biotechnology company scaling more like a technology company, and we are just getting started.","1","2023-08-08 19:41:20","2023-11-20 22:26:53","" +"299","Google Cloud","google-cloud","logo/google-cloud.jpg","https://cloud.google.com/?hl=en","Google Cloud is widely recognized as a global leader in delivering a secure, open and intelligent enterprise cloud platform. Our technology is built on Google’s private network and is the product of nearly 20 years of innovation in security, network architecture, collaboration, artificial intelligence and open source software. We offer a simply engineered set of tools and unparalleled technology across Google Cloud Platform and G Suite that help bring people, insights and ideas together. Customers across more than 150 countries trust Google Cloud to modernize their computing environment for today’s digital world.","1","2023-08-08 19:43:02","2023-11-20 22:26:58","" +"300","DoiT International","doit","logo/doit.png","https://www.doit.com/","You have the cloud and we have your back. For nearly a decade, we’ve been helping businesses build and scale cloud solutions with our world-class cloud engineering support. We help our customers with technical support and consulting on building and operating complex large-scale distributed systems, developing better machine learning models and setting up big data solutions using Google Cloud, Amazon AWS and Microsoft Azure.","1","2023-08-08 19:43:17","2023-11-20 22:27:03","" +"301","Lambda","lambda","logo/lambda.jpg","https://lambdalabs.com/","Our workstations, servers, laptops, and cloud services power engineers and researchers at the forefront of human knowledge. Our customers include Intel, Microsoft, Amazon Research, Kaiser Permanente, MIT, Stanford, Harvard, Caltech, and the Department of Defense. With Lambda, you simply plug the system into the wall and get started making business and scientific breakthroughs. That's why the greatest companies and research labs in the world work with Lambda.","1","2023-08-08 19:43:31","2023-11-20 22:27:11","" +"302","Center for the Study of Movement, Cognition, and Mobility","cmcm","logo/tasmc.jpeg","https://rnd.tasmc.org.il/laboratories/center-for-the-study-of-movement-cognition-and-mobility-prof-jeff-hausdorff/","As the baby boomers age, the number of adults who suffer from frequent falls, gait disorders, cognitive impairment, dementia, and other neurological diseases continues to increase dramatically. New understandings and therapeutic approaches are needed. Our research aims to improve the personalized treatment of age-related movement, cognition, and mobility disorders and to alleviate the burden associated with them.`","1","2023-08-08 19:54:16","2023-11-20 22:27:18","CMCM" +"303","Research Group for Neurorehabilitation","enrgy","logo/ku-leuven.jpg","https://gbiomed.kuleuven.be/english/research/50000743/research/research-units/enrgy","The mission of the Neurorehabilitation Research Group (eNRGy) is to advance the evidence-base of neurorehabilitation of child and adult populations with acute and chronic neurological conditions. In doing so, our research activities tackle both fundamental and translational research questions aimed at increasing our understanding of neurobehavioral and neuromuscular mechanisms, relevant for innovation and refinement of rehabilitation interventions. The clinical challenge of eNRGy lies in addressing the complexity of the brain and its role in neuromotor function, including deficits in the motor, sensory, social and cognitive domain.","1","2023-08-08 19:55:53","2023-11-20 22:39:07","eNRGy" +"304","Hinda and Arthur Marcus Institute for Aging","marcus-institute","logo/hebrew-seniorlife.jpg","https://www.marcusinstituteforaging.org/","Since 1966, the Hinda and Arthur Marcus Institute for Aging Research has challenged conventional wisdom to better understand how we age. The questions we ask - and the answers we uncover - directly impact standards of care and help seniors live more vital, meaningful lives. The Marcus Institute is one of the largest gerontological research facilities in a clinical setting in the U.S. Our decades-long relationship with Harvard Medical School attracts expert teaching staff and outstanding research fellows. Our research portfolio increased 90% from 2010 to 2022 and ranks us in the top 10% of institutions funded by the National Institutes of Health.","1","2023-08-08 19:59:31","2023-11-20 22:39:17","" +"305","University Hospital Zurich","usz","logo/usz.jpg","https://www.usz.ch/en/","The University Hospital Zurich (USZ) is open to all patients every day and provides fundamental medical care and cutting-edge medicine in a central location in Zurich. We use our superior academic knowledge to treat a wide range of health issues, taking a personal touch and utilizing highly specialized and up-to-date research.","1","2023-08-09 22:21:15","2023-11-20 22:39:22","USZ" +"306","Zurich University of Applied Sciences","zhaw","logo/zhaw.jpg","https://www.zhaw.ch/en/university/","The ZHAW is one of the leading universities of applied sciences in Switzerland. It offers teaching, research, continuing education and other services that are both practice-oriented and science-based. Research & development at the ZHAW focuses on key societal challenges, with a particular emphasis on energy and societal integration. With its expertise in sustainable development and digital transformation, the ZHAW imparts forward-looking knowledge and takes an active part in shaping the digital and ecological transformation. With locations in Winterthur, Zurich and Wädenswil, the ZHAW is firmly anchored in its region whilst collaborating with international partners.","1","2023-08-09 22:22:32","2023-11-20 22:39:28","ZHAW" +"307","Helmholtz Munich","helmholtz-munich","logo/helmholtz-munich.jpg","https://www.helmholtz-munich.de/en","We are Helmholtz Munich. We discover breakthrough solutions for better health in a rapidly changing world. Our world is constantly changing. This impacts our health. Many widespread diseases such as diabetes, allergies and lung diseases are on the rise. Climate change is causing new diseases to emerge. We develop solutions for a healthier future. Our cutting-edge research is the springboard for medical innovations. Together with our partners, we accelerate the transfer from ideas to applications, from labs to startups, from science to society.","1","2023-08-09 22:23:10","2023-11-20 22:39:34","" +"308","Imperial College London","imperial","logo/imperial.jpg","https://www.imperial.ac.uk/","Imperial is a global top ten university with a world-class reputation in science, engineering, business and medicine. Together, we are Imperial.","1","2023-08-09 22:24:26","2023-11-20 22:39:40","" +"309","Geneva University Hospitals","hug","logo/hug.png","https://www.hug.ch/","The result of a centuries-old tradition of excellence in medicine and science, the HUG was created in 1995. Bringing together the eight Geneva public hospitals and, since July 1, 2016, two clinics (Joli-Mont and Crans-Montana), they represent the leading university hospital in Switzerland. They also have 30 outpatient consultations, spread throughout the canton of Geneva.","1","2023-08-09 22:26:11","2023-11-20 22:39:43","HUG" +"310","National University Hospital","nuh","logo/nuh.jpeg","https://www.nuh.com.sg/Pages/Home.aspx","The National University Hospital (NUH) is Singapore’s leading university hospital. While the hospital at Kent Ridge first received its patients on 24 June 1985, our legacy started from 1905, the date of the founding of what is today the NUS Yong Loo Lin School of Medicine. NUH is the principal teaching hospital of the medical school. Our unique identity as a university hospital is a key attraction for healthcare professionals who aspire to do more than practise tertiary medical care. We offer an environment where research and teaching are an integral part of medicine, and continue to shape medicine and transform care for the community we care for. We are an academic medical centre with over 1,200 beds, serving more than one million patients a year with over 50 medical, surgical and dental specialties. NUH is the only public and not-for-profit hospital in Singapore to provide trusted care for adults, women and children under one roof, including the only paediatric kidney and live...","1","2023-08-09 22:27:16","2023-11-20 22:39:47","NUH" +"311","Princess Maxima Center for Pediatric Oncology","princess-maxima-center","logo/princess-maxima-center.jpg","https://www.prinsesmaximacentrum.nl/en","When a child is seriously ill with cancer, only one thing comes first: cure. That is why at the Princess Máxima Center for pediatric oncology we work together every day in a groundbreaking and passionate way to improve the survival rate and quality of life of children with cancer. Now, and in the longer term. Because children still have a whole life ahead of them. The Princess Máxima Center is not an ordinary hospital, but a research hospital. All children with cancer in the Netherlands are treated here. This makes the Princess Máxima Center the largest pediatric cancer center in Europe. Over 450 researchers and 900 healthcare professionals work closely with Dutch and international hospitals on better treatments and new perspectives on cures. In this way, we give the child of today the very best care and take important steps to improve the chances of survival for the children who are not yet cured.","1","2023-08-09 22:29:04","2023-11-20 22:39:55","" +"312","CHAIMELEON Consortium","chaimeleon","logo/chaimeleon.svg","https://chaimeleon.eu/#partners","The interdisciplinary CHAIMELEON consortium is made up of 18 partners from 9 countries: Fundación para la Investigación del Hospital Universitario la Fe de la Comunidad Valenciana (ES), Universita di Pisa (IT), Universita Degli Studi di Roma la Sapienza (IT), Centro Hospitalar Universitário de Santo António (PT), ICCS Policlinico San Donato (IT), College des Enseignants de Radiologie (FR), Universiteit Masstricht (NL), Charité Universitätsmedizin Berlin (DE), Imperial College London (UK), Ben-Gurion University of the Negev (IL), Universitat Politècnica de Valencia (ES), GE Healthcare (DE), Quibim (ES), Medexprim (FR), Bahia (ES), Matical Innovation (ES), European Institute of Biomedical Imaging Research (AT), Universitat de Valencia (ES). It constitutes a pan-European ecosystem of knowledge, infrastructures, biobanks and technologies on oncology, AI/in-silico and cloud computing addressed to health. The CHAIMELON project also collaborates with other European projects and initiatives.","1","2023-08-09 22:48:43","2023-11-20 22:40:01","" +"313","Office of Digital Transformation","odt","logo/fda.svg","https://www.fda.gov/about-fda/office-commissioner/office-digital-transformation","The Office of Digital Transformation (ODT) provides the vision and leadership in information technology (IT), data, and cybersecurity needed to advance FDA’s mission and strategic priorities. ODT is led by the Chief Information Officer and reports to the FDA Commissioner. ODT directs and coordinates enterprise strategic planning, policy, and resource management to ensure that Agency IT, data, and cybersecurity investments and activities provide maximum value to FDA. ODT is comprised of the Office of Information Management and Technology (OIMT), Office of Data, Analytics, and Research (ODAR), and the Office of Information Security (OIS), under the direction of the Chief Technology Officer (CTO), Chief Data Officer (CDO), and Chief Information Security Officer (CISO). ODT is committed to delivering trusted technology and data solutions that enable FDA to reimagine the possible. Watch this video to learn more about our organization and how we are striving to make an impact at FDA.","2","2023-08-10 21:37:33","2023-08-10 21:39:34","ODT" +"314","Office of Minority Health and Health Equity","omhhe","logo/fda.svg","https://www.fda.gov/about-fda/office-commissioner/office-minority-health-and-health-equity","The FDA Office of Minority Health and Health Equity (OMHHE) serves to promote and protect the health of diverse populations through research and communication of science that addresses health disparities.","1","2023-08-10 21:37:42","2023-08-10 21:40:30","OMHHE" +"315","Office of Data, Analytics, and Research","odar","logo/fda.svg","https://www.fda.gov/about-fda/office-digital-transformation/office-data-analytics-and-research-odar","The Office of Data, Analytics, and Research (ODAR) manages and improves FDA’s ability to leverage data as a strategic asset by establishing enterprise data strategy and priorities.","2","2023-08-10 21:37:44","2023-08-10 21:38:28","ODAR" +"316","Medicines and Healthcare products Regulatory Agency","mhra","logo/mhra.jpg","https://www.gov.uk/government/organisations/medicines-and-healthcare-products-regulatory-agency","We are the regulator of medicines, medical devices and blood components for transfusion in the UK. We put patients first in everything we do, right across the lifecycle of the products we regulate. We rigorously use science and data to inform our decisions, enable medical innovation and to make sure that medicines and healthcare products available in the UK are safe and effective.","1","2023-08-10 22:10:11","2023-11-20 22:40:12","MHRA" +"317","MDClone","mdclone","logo/mdclone.jpg","https://www.mdclone.com/","MDClone is a technology firm focused on unlocking healthcare data and empowering exploration, discovery, and collaboration to improve patients' health. At MDClone, we are a growing startup with big aspirations. We are determined to make an impact on healthcare worldwide with tools, processes, and services focused on turning data into better outcomes. MDClone is focused on empowering healthcare institutions, enabling stronger and more secure relationships between healthcare providers and life science companies, and developing regional and global collaboration with privacy-enabled shared data sets.","1","2023-08-10 22:11:58","2023-11-20 22:40:25","" +"318","Washington Business Dynamics, LLC","wbd","logo/wbd.jpeg","https://www.wbdynamics.com/","Since our founding, WBD has sought to be a management consulting provider of choice for the federal government and the private sector. We are privileged to count many of the world’s foremost institutions and organizations among our client list. We partnered with these organizations’ senior leaders and immediately began uncovering value. Our staff brings a superior analytic capability, time-tested best practices, and a logical approach to solve problems and position organizations for future success.","1","2023-08-10 22:12:50","2023-11-20 22:40:38","WBD" +"319","Medical College of Wisconsin","mcw","logo/medical-college-wisconsin-logo.svg","https://www.mcw.edu/","The Medical College of Wisconsin is a private medical school, pharmacy school, and graduate school of sciences headquartered in Milwaukee, Wisconsin. The school was established in 1893 and is the largest research center in eastern Wisconsin.","5","2023-09-09 01:40:31","2023-09-09 03:10:17","MCW" +"320","Boston University","bu","logo/bu.jpg","https://www.bu.edu/","Boston University is no small operation. With over 36,000 students from more than 130 countries, over 10,000 faculty and staff, 17 schools and colleges and the Faculty of Computing & Data Sciences, and more than 300 programs of study, our three campuses are always humming, always in high gear. Get to know the people and teams that keep the University running smoothly.","1","2023-09-12 23:58:11","2023-11-20 22:40:44","BU" +"321","Telethon Institute of Genetics and Medicine","tigem","logo/tigem.jpg","https://www.tigem.it/","The Telethon Institute of Genetics and Medicine (TIGEM), a Telethon Foundation organization, was founded in 1994 as a leading European research center. TIGEM is a Telethon Foundation research centre in Pozzuoli, Italy. TIGEM comprises several research groups and over 200 staff members, all dedicated to understanding the molecular mechanisms behind rare genetic diseases and developing novel treatments. These diseases, often overlooked by pharmaceutical industries, are most common in children and adolescents. TIGEM’s research falls into three main themes: Cell Biology and Disease Mechanisms, Genomic Medicine, and Molecular Therapy. Our research is supported by a number of in-house highly specialised facilities, as well as significant international support in the form of funding and collaborative opportunities.","1","2023-09-13 00:01:07","2023-11-20 22:40:49","TIGEM" +"322","Genome Institute of Singapore","gis","logo/gis.jpg","https://www.a-star.edu.sg/gis","When the Genome Institute of Singapore (GIS) was established in 2000, the science of genomics was still in its infancy. Since then, genomics has proved its relevance to all aspects of biology and medicine. It is now possible to sequence entire populations and communities, resolve organs at the single-cell level, and develop treatments guided by genomic data. We are now able to edit genomes at will, synthesise chromosomes, and perform complex experiments in silico by harnessing the ever-growing reservoir of public-access data. Importantly, while much has been done, much remains to be discovered as our knowledge of genomes, both human and non-human, remains incomplete. Through it all, GIS has maintained its leadership and relevance in genomic science by focusing on its three core strengths - asking the right biological questions, applying and developing cutting-edge technology platforms, and embracing multi-disciplinary team science. These core strengths have served us well, and wi...","1","2023-09-13 00:05:51","2023-11-20 22:48:16","GIS" +"323","University of Rostock","university-of-rostock","logo/university-of-rostock.jpg","https://www.uni-rostock.de/en/","Founded in 1419, the University of Rostock is the oldest in the Baltic Sea Region. True to the motto “Traditio et Innovatio”, the University of Rostock has constantly further developed. The multitude of new buildings represents the university’s modernity.","1","2023-09-13 00:22:55","2023-11-20 22:59:13","" +"324","FlowCAP","flowcap","","","This organization may no longer exist, has rebranded, or has been merged under another organization.","1","2023-09-13 00:36:41","2023-09-13 00:37:01","" +"325","University of California, Santa Barbara","ucsb","logo/uc-santa-barbara.jpg","https://www.ucsb.edu/","At UC Santa Barbara, we offer a dynamic environment that prizes academic inquiry and interpersonal connection to inspire scholarly ambition, creativity, and discoveries with wide-ranging impact. We’re inquisitive and curious, community-driven and globally-focused. Across our campus, you’ll find independent thinkers and consensus builders, Nobel Laureates and leaders chasing noble causes. But no matter how you define us, we are above all Gauchos — diverse in our pursuits, yet connected in our collective drive toward excellence.","2","2023-09-13 16:57:59","2023-11-21 01:16:04","UCSB" +"326","GlaxoSmithKline","gsk","logo/gsk.jpg","https://www.gsk.com/en-gb/","We are a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together. We aim to positively impact the health of 2.5 billion people by the end of 2030. Our bold ambitions for patients are reflected in new commitments to growth and a step-change in performance. We are a company where outstanding people can thrive.","2","2023-09-13 17:17:03","2023-11-20 22:59:33","" +"327","Carnegie Mellon University","cmu","logo/cmu.jpg","https://www.cmu.edu/","Carnegie Mellon University challenges the curious and passionate to imagine and deliver work that matters. A private, global research university, Carnegie Mellon stands among the world's most renowned educational institutions, and sets its own course. Start the journey here. Over the past 10 years, more than 400 startups linked to CMU have raised more than $7 billion in follow-on funding. Those investment numbers are especially high because of the sheer size of Pittsburgh’s growing autonomous vehicles cluster - including Uber, Aurora, Waymo and Motional - all of which are here because of their strong ties to CMU. With cutting-edge brain science, path-breaking performances, innovative startups, driverless cars, big data, big ambitions, Nobel and Turing prizes, hands-on learning, and a whole lot of robots, CMU doesn't imagine the future, we create it.","1","2023-09-13 23:36:25","2023-11-20 22:59:39","CMU" +"328","ContextVision","contextvision","logo/contextvision.png","https://www.contextvision.com/","Our cutting-edge technology helps doctors accurately interpret medical images, a crucial foundation for better diagnosis and treatment. Healthcare providers worldwide face the same key challenge - a challenge that ContextVision is helping to solve: how to increase patient care while coping with limited resources. ContextVision provides intelligent technology that improves healthcare service and outcomes for more people. The company specializes in image analysis and artificial intelligence.","2","2023-09-15 17:21:50","2023-11-20 22:59:45","" +"329","Karolinska Institute","ki","logo/ki.jpg","https://ki.se/en","Karolinska Institutet is one of the world’s leading medical universities. Our vision is to advance knowledge about life and strive towards better health for all. Karolinska Institutet accounts for the single largest share of all academic medical research conducted in Sweden and offers the country’s broadest range of education in medicine and health sciences. The Nobel Assembly at Karolinska Institutet selects the Nobel laureates in Physiology or Medicine.","1","2023-09-15 17:24:17","2023-11-20 22:59:48","KI" +"330","Research to the People","research-to-the-people","logo/research-to-the-people.png","https://www.researchtothepeople.org/","Research to the People is a patient-partnered research program for open Oncology and Rare Disease Cases.","1","2023-09-28 21:15:01","2023-10-06 20:58:33","" +"333","University of Utah","u-of-u","logo/u-of-u.jpg","https://www.utah.edu/","Imagine what you want to accomplish, then really making it happen. Imagine designing and publishing a video game before earning your diploma, starting a business while studying business, and doing all this in a setting that begs you to get out and do something. Imagine, then Do. Opportunity awaits and all things are possible at a place we call Imagine U. The University of Utah.","3","2023-10-06 20:17:06","2023-11-20 23:00:08","" +"336","University of California, Irvine","uci","logo/uci.jpg","https://uci.edu/","In 1965, the University of California, Irvine was founded with a mission to catalyze the community and enhance lives through rigorous academics, cutting-edge research, and dedicated public service. Today, we draw on the unyielding spirit of our pioneering faculty, staff and students who arrived on campus with a dream to inspire change and generate new ideas. We believe that true progress is made when different perspectives come together to advance our understanding of the world around us. And we enlighten our communities and point the way to a better future. At UCI, we shine brighter.","1","2023-10-06 20:26:57","2023-11-20 23:00:27","UCI" +"337","Harvard Personal Genome Project","harvard-pgp","logo/harvard-pgp.png","https://pgp.med.harvard.edu/","Starting in 2005 as a pilot experiment with 10 individuals, the Harvard Personal Genome Project (Harvard PGP) pioneered a new form of genomics research. The main goal of the project is to allow scientists to connect human genetic information (human DNA sequence, gene expression, associated microbial sequence data, etc) with human trait information (medical information, biospecimens and physical traits) and environmental exposures. Project participants consent to provide biological samples from themselves in order to perform whole genome sequencing, and use of these materials for biological research. The project now has over 5,000 participants.","3","2023-10-06 20:31:44","2023-11-20 23:37:54","" +"339","Johns Hopkins University","jhu","logo/johns-hopkins.jpg","https://www.jhu.edu/","“What are we aiming at?” That’s the question our university’s first president, Daniel Coit Gilman, asked at his inauguration in 1876. What is this place all about, exactly? His answer: “The encouragement of research . . . and the advancement of individual scholars, who by their excellence will advance the sciences they pursue, and the society where they dwell.” Gilman believed that teaching and research go hand in hand—that success in one depends on success in the other—and that a modern university must do both well. He also believed that sharing our knowledge and discoveries would help make the world a better place. In 145 years, we haven’t strayed from that vision. This is still a destination for excellent, ambitious scholars and a world leader in teaching and research. Distinguished professors mentor students in the arts and music, humanities, social and natural sciences, engineering, international studies, education, business, and the health professions. Those same faculty...","3","2023-10-06 20:32:36","2023-11-20 23:01:10","JHU" +"342","University of Kansas Medical Center","kumc","logo/kumc.jpg","https://www.kumc.edu/","The University of Kansas Medical Center's mission is to improve lives and communities in Kansas and beyond through innovation in education, research and health care.","1","2023-10-06 20:34:22","2023-11-20 23:01:07","KUMC" +"343","Rare Genomes Project","rgp-project","logo/rgp-project.svg","https://raregenomes.org/how-it-works","The Rare Genomes Project at the Broad Institute of MIT and Harvard is a team of researchers, physicians, software developers, genetic counselors, and study coordinators who believe that the latest advances in genomic sequencing are changing medicine and should be more broadly available to families with rare and undiagnosed conditions.","1","2023-10-06 20:36:09","2023-11-20 23:38:05","" +"344","Invitae","invitae","logo/invitae.jpg","https://www.invitae.com/en?gad=1&gclid=CjwKCAjw4P6oBhBsEiwAKYVkq6rR_TeHQ4BDrXBBmTUELJgcJvCoj6dlNobNg2hbY4wzcRdk5P6-IxoCCj4QAvD_BwE","At Invitae, we believe that good health is possible—and that genetic information has the ability to transform the way medicine is practiced, making what once seemed impossible possible, as we empower people to make decisions about their health through the power of genetics.","1","2023-10-06 20:38:01","2023-11-20 23:38:12","" +"346","Seattle Children's Hospital","seattle-childrens","logo/seattle-childrens.jpg","https://www.seattlechildrens.org/","This isn’t about beating the odds. This is about changing them. We fight relentlessly to make sure there’s no such thing as “out of options” and to make sure kids who “didn't have a chance” can have the childhoods they deserve. At Seattle Children’s, we’re united by a compelling mission: We provide hope, care and cures to help every child live the healthiest and most fulfilling life possible. Consistently ranked one of the nation’s best children’s hospitals.Together, we deliver superior patient care, advance new discoveries and treatments through pediatric research and serve as the pediatric and adolescent academic medical center for Washington, Alaska, Montana and Idaho – the largest region of any children’s hospital in the country. U.S. News & World Report has recognized Seattle Children’s as a top children’s hospital every year since it began ranking medical facilities more than 30 years ago. This means your child will be cared for by the very best.","1","2023-10-06 20:39:31","2023-11-20 23:38:25","" +"347","Christian-Albrechts-Universität zu Kiel","cau","logo/cau.png","https://www.uni-kiel.de/en/","Kiel University (CAU) was founded back in 1665. It is Schleswig-Holstein's oldest, largest and best-known university, with 27,000 students and around 3,700 members of staff. It is also the only fully-fledged university in the state. Seven Nobel prize winners have worked here. The CAU has been successfully taking part in the Excellence Initiative since 2006.","3","2023-10-06 20:40:42","2023-11-20 23:38:31","CAU" +"348","CACHE","cache","logo/cache.png","https://cache-challenge.org/","CACHE will help define the state-of-the-art in molecular design by providing unbiased, high quality experimental feedback on computational hit-finding predictions. To this end, CACHE will initiate a new hit-finding benchmarking exercise every four months. These public competitions (challenges) will have the added benefit of identifying new chemical starting points for biologically interesting targets. Each competition will focus on a new protein target representing one of five possible challenges in hit-finding, based on the type of target data available. Participants will use their computational method to predict hits that will be tested experimentally by CACHE. Each challenge will involve two cycles of predictions in order to give participants the opportunity to incorporate learnings from the first round into their designs. At the end of each challenge, CACHE will release all data, including chemical structures, to the public.","4","2023-10-06 21:25:30","2023-11-20 23:15:21","" +"349","National Institute of Diabetes and Digestive and Kidney Diseases","niddk","logo/nih.png","https://www.niddk.nih.gov/","NIDDK research creates knowledge about and treatments for diseases that are among the most chronic, costly, and consequential for patients, their families, and the Nation.","1","2023-10-18 17:07:25","2023-10-27 20:25:54","NIDDK" +"350","Jeroen Bosch Ziekenhuis","jbz","logo/jbz.jpg","https://www.jeroenboschziekenhuis.nl/","Our starting point is that you deserve the care that suits you. Together with you, we determine what you need and from whom, so that you can live the life you want for as long as possible. We use all our medical expertise to achieve this and work together, for example with your family and friends, your GP, the municipality and home care. Here you can read how we have been working since 2016 on care that suits you and work that suits you. Simply because you matter.","1","2023-11-02 15:42:18","2023-11-20 23:39:18","JBZ" +"351","Diagnostic Image Analysis Group","diagnostic-image-analysis-group","logo/radboud-umc.jpeg","https://www.diagnijmegen.nl/","The Diagnostic Image Analysis Group is part of the Departments of Imaging, Pathology, Radiation Oncology, Cardiology, and Neurology of Radboud University Medical Center. We develop computer algorithms to interpret and process medical images.","3","2023-11-02 18:12:04","2023-11-20 23:39:14","" +"352","Center for Applied Medical Research, University of Navarre","cima","logo/cima.jpg","https://cima.cun.es/en/","We are a research center committed to excellence in translational research, based on novel biological knowledge and aimed at finding therapeutic solutions to patients' needs. We are the biomedical research center of the Universidad de Navarra. With our academic status we work on a non-profit basis to reinvest the surpluses in the progress of our research and to fulfill our mission of service to patients and society.","1","2023-11-08 20:21:05","2023-11-20 23:39:25","CIMA" +"353","London School of Hygiene and Tropical Medicine","lshtm","logo/lshtm.jpg","https://www.lshtm.ac.uk/","The London School of Hygiene & Tropical Medicine is renowned for its research, postgraduate studies and continuing education in public and global health. We have an annual research income of more than £190 million and are one of the highest-rated research institutions in the UK.","1","2023-11-08 20:22:27","2023-11-20 23:39:33","LSHTM" +"354","Quantib","quantib","logo/quantib.jpg","https://www.quantib.com/","The Quantib story started 9 years ago as a spin-off of Erasmus MC, a globally leading academic center. That's how Quantib was founded but we haven't stopped growing since. We serve customers worldwide, have offices in Europe and the US and employ over 30 bright, motivated people. Our AI solutions are FDA-cleared, CE-marked and vendor neutral. Their easy integration with PACS makes them integrate seamlessly into radiologists' workflows.","1","2023-11-08 23:06:25","2023-11-20 23:39:50","" +"355","Biomediq","biomediq","logo/biomediq.svg","http://www.biomediq.com/index.html","Biomediq is a research-based company providing software-based solutions for clinical trials and clinical practice. We perform contract research and market validated, automatic and semi-automatic analyses of: 1) knee MRI for scoring of cartilage quantity (volume, thickness, ...) and quality (surface smoothness, homogeneity, congruity, ...); and bone structure in relation to osteoarthritis; 2) mammograms for breast cancer risk; 3) atrophy and tissue structure from Brain MRI for Alzheimer's disease; and 4) synovitis and erosions from Hand MRI for rheumatoid arthritis","1","2023-11-08 23:10:13","2023-11-20 23:40:00","" +"356","International Research Laboratory on Artifical Intelligence","ipal","logo/ipal.png","https://ipal.cnrs.fr/","IPAL is a CNRS International (French-Singaporean) Research Laboratory (IRL 2955), based in Singapore. It was funded in 1998 as a special overseas CNRS Research Project in order to create a framework for collaborative research projects including CNRS, NUS, and A*Star. This first research structure moved to the status of CNRS Research Group in 2000. In 2007, IPAL became a CNRS IRL (the highest label among the CNRS international programs). The IRL agreement was signed in January 2007, for an initial period of 4 years (renewable), between the CNRS (INS2I institute), A*Star (I2R Institute), NUS (School of Computing), and the University of Grenoble-Alpes, France. The agreement was renewed in 2011 and 2015, with additional partners (Institut Mines Telecom, France, and Sorbonne University, France). In 2019, the IPAL agreement has been extended for two more years in order to prepare a new scientific program focused on Artificial Intelligence, starting in 2021. The main partners involved ...","1","2023-11-08 23:54:53","2023-11-20 23:40:09","IPAL" +"357","Centre National de la Recherche Scientifique","cnrs","logo/cnrs.jpg","https://www.cnrs.fr/en","The French National Centre for Scientific Research is among the world's leading research institutions. Its scientists explore the living world, matter, the Universe, and the functioning of human societies in order to meet the major challenges of today and tomorrow. Internationally recognised for the excellence of its scientific research, the CNRS is a reference in the world of research and development, as well as for the general public.","1","2023-11-08 23:57:51","2023-11-20 23:40:22","CNRS" +"358","Université Joseph Fourier","ujf","","www.ujf-grenoble.fr","This organization may no longer exist, has rebranded, or has been merged under another organization.","1","2023-11-09 00:02:07","2023-11-09 00:04:03","UJF" +"359","Sorbonne Université","sorbonne-university","logo/sorbonne-university.png","https://www.sorbonne-universite.fr/en","Sorbonne Université promotes excellence at the heart of each of its disciplines and runs numerous interdisciplinary programs capable of meeting the major challenges of the 21st century.","1","2023-11-09 00:05:42","2023-11-20 23:40:36","" +"360","A*STAR-I2R","a*star-i2r","","https://www.iala-aism.org/organisation/st-electronics-info-software-systems-pte-ltd/","The Institute for Infocomm Research (I^2R pronounced as i-squared-r) is a member of the Agency for Science, Technology and Research (A*STAR) family and is Singapore’s largest ICT research institute. Established in 2002, our vision is to power a vibrant and strong infocomm ecosystem in Singapore. We seek to foster world-class research and develop a deep talent pool of infocomm professionals to power a vibrant knowledge-based Singapore. At I2R, our key research areas are in Artificial Intelligence, Audio; Language & Speech, Data Analytics, Communications & Networks, Cybersecurity, Heterogeneous Analytics, Healthcare, Robotics & AV, Satellite, Smart Energy & Environment and Video & Image Analytics.","1","2023-11-09 00:10:02","2023-11-20 23:32:39","" +"361","Université Pierre-et-Marie-Curie","upmc","logo/sorbonne-university.png","https://www.sorbonne-universite.fr/en","This organization may no longer exist, has rebranded, or has been merged under another organization.","1","2023-11-09 00:13:38","2023-11-20 23:40:37","UPMC" +"363","Gentofte Hospital","gentofte-hospital","logo/gentofte-hospital.jpg","https://www.gentoftehospital.dk/English-/Pages/default.aspx","Founded in 1927, Gentofte Hospital stands as one of Denmark's oldest and most esteemed healthcare institutions. With a rich history spanning many years, our hospital has played a important role in the nation's healthcare landscape, offering specialized medical care, advanced research, and academic collaboration. On the first of January 2015, Herlev Hospital and Gentofte Hospital were merged in order to provide the best possible service to its patients. The merge doesn´t affect the individual patient, but only contributes to a more streamlined workflow for the employees.","1","2023-11-09 00:21:38","2023-11-20 23:40:53","" +"364","Rigshospitalet","rigshospitalet","logo/gentofte-hospital.jpg","https://www.rigshospitalet.dk/english/Pages/default.aspx","We are a highly specialised hospital which, with a few exceptions, covers all medical specialist areas.","1","2023-11-09 00:21:40","2023-11-20 23:41:36","" +"365","Fraunhofer Institute for Digital Medicine MEVIS`","mevis","logo/fraunhofer.jpeg","https://www.mevis.fraunhofer.de/","Embedded in a worldwide network of clinical and academic partners, Fraunhofer MEVIS develops real-world software solutions for image and data supported early detection, diagnosis, and therapy. Strong focus is placed on cancer as well as diseases of the circulatory system, brain, breast, liver, and lung. The goal is to detect diseases earlier and more reliably, tailor treatments to each individual, and make therapeutic success more measurable. In addition, the institute develops software systems for industrial partners to undertake image-based studies to determine the effectiveness of medicine and contrast agents. To reach its goals, Fraunhofer MEVIS works closely with medical technology and pharmaceutical companies, providing solutions for the entire chain of development from applied research to certified medical products.","1","2023-11-09 18:32:08","2023-11-20 23:53:32","MEVIS" +"366","Rutgers University","rutgers","logo/rutgers.png","https://www.rutgers.edu/","Rutgers, The State University of New Jersey, stands among America’s highest-ranked, most diverse public research universities. The oldest, largest, and top-ranked public university in the New York/New Jersey metropolitan area, you’ll find us at our main locations in three New Jersey cities, and our footprint can be seen around the region. We’re an academic, health, and research powerhouse and a university of opportunity.","1","2023-11-09 18:51:08","2023-11-20 23:53:40","" +"367","Philips","philips","logo/philips.jpg","https://www.usa.philips.com/healthcare","At Philips, our purpose is to improve people’s health and well-being through meaningful innovation. We aim to improve 2.5 billion lives per year by 2030, including 400 million in underserved communities. As a technology company, we – and our brand licensees – innovate for people with one consistent belief: there’s always a way to make life better.","2","2023-11-09 20:43:17","2023-11-20 23:53:53","" +"368","Translational Research IT","trait","logo/health-ri.jpg","http://trait.health-ri.nl/","The Translational Research IT (TraIT) project provides an easy-to-access and easy-to-use infrastructure for data sharing, together with a set of tools for further exploration of the collected data. It operates across the four major domains of translational research: clinical, imaging, biobanking, and experimental (any-omics). TraIT gives scientists within multi-site projects the resources needed to share and disseminate data and analyses. Importantly, the project aimed to adopt and adapt existing and proven solutions (e.g. XNAT, Ldot, cBioPortal) rather than embarking on major software development projects. As of January 2020, more than 4000 researchers from over 400 studies and dispersed over more than 500 locations are making use of one or more of TraIT’s services.","1","2023-11-09 21:21:20","2023-11-20 23:54:06","TraIT" +"369","Stichting IT Projecten","stitpro","logo/stitpro.png","https://stitpro.nl/projects/","StITPro provides subsidies to ICT projects. StITPro wants to ensure that software is developed for educational and socially relevant purposes. Conditions for this are that the software is 'open source', the use of the software extends beyond the initial target group and the software remains operational and supported for a longer period of time.","2","2023-11-09 21:31:58","2023-11-20 23:54:10","" +"370","Universidade do Porto","u-porto","logo/u-porto.jpg","https://www.up.pt/portal/en/","The University of Porto is a public foundation regulated by private law and with statutory, educational, scientific, cultural, administrative, financial, patrimonial and disciplinary autonomy. U.Porto can undertake activities with other national or international entities (public, private or cooperative). The University of Porto can create or participate in associations or societies, for-profit or non-profit, as long as the activities are compatible with its mission.","2","2023-11-09 21:35:42","2023-11-20 23:54:27","" +"371","National University of Sciences & Technology","nust","logo/nust.jpeg","https://nust.edu.pk/","Welcome to the National University of Sciences & Technology, a prestigious institute of higher learning that has become a benchmark of excellence in South Asia. As the leader of this esteemed institution, I am honored to serve and committed to advancing its mission of providing affordable, SDG-engaged, fourth-generation entrepreneurial education. Our faculty and staff are dedicated to excellence in teaching, research, and service, and I am proud of all that we have accomplished together. During the coming year, I am eager to work with all of you to continue this progress and provide a dynamic and supportive learning environment for our students. Our goal is to equip them with the necessary skills and knowledge to tackle the world's most pressing challenges, while also preparing them for the fast-changing world. I welcome you to join us in any capacity to shape the future, lead the nation's progress, and contribute to serving humanity. Let us work together to make the best of 2023,...","1","2023-11-09 21:36:47","2023-11-20 23:54:34","NUST" +"372","University of Dundee","dundee","logo/dundee.jpg","https://www.dundee.ac.uk/","To transform lives, working locally and globally through the creation, sharing, and application of knowledge.","1","2023-11-09 21:37:52","2023-11-20 23:55:27","" +"373","ISTITUTO ONCOLOGICO VENETO IRCCS","iov","logo/iov.jpg","https://www.ioveneto.it/en/","The Veneto Institute of Oncology IOV – IRCCS is the first and only medical center in the Veneto region specific for the prevention, diagnosis and treatment of cancer and for cancer research. IOV was established by the Veneto Regional Government in December 2005, becoming a highly specialized health research center of national and international importance. It is recognized by the Ministry of Health as a research hospital (IRCCS) and by the Organization of European Cancer Institutes (OECI) as a Comprehensive Cancer Center. It is a member of the network of excellence Alliance Against Cancer (ACC), the largest Italian organization of clinical and translational cancer research, and of the European Network for Rare Adult Solid Cancer EURACAN.","1","2023-11-09 21:40:36","2023-11-20 23:55:38","IOV" +"374","European Institute of Oncology","ieo","logo/ieo.jpg","https://www.ieo.it/en/","The IEO (European Institute of Oncology) is one of the world's most prestigious hospitals and the fastest growing comprehensive cancer centre in Europe. IEO integrates the various areas related to the fight against cancer such as prevention, diagnosis, treatment, training and education, basic and translational research.","1","2023-11-09 21:45:04","2023-11-20 23:55:42","IEO" +"375","Oncology Institute Francisco Gentil","ipo","logo/ipo.jpeg","https://www.ipolisboa.min-saude.pt/","IPO was born out of the dream and work of Francisco Gentil, a surgeon, far ahead of his time, who founded the Portuguese Institute for the Study of Cancer in 1923, focussed on the care to cancer patients, research, study and treatment of the disease. On the founder’s proposal, the Institute was linked, from the beginning, to Medical School of Lisbon University – only 60 years later International Union Against Cancer (UICC) and World Health Organization (WHO) recognised this model of which Portugal was a pioneer and which enabled to bring together the major goals behind the creation of the institution.","1","2023-11-09 21:45:40","2023-11-20 23:55:46","IPO" +"376","University of New South Wales","unsw-sydney","logo/unsw-sydney.jpg","https://www.unsw.edu.au/","The essence of UNSW Sydney is not found in our impressive facilities or beautiful grounds. It is found in our students, our staff, our alumni and our generous donors. Our collective difference reflects the unique perspectives of our people, place and purpose as we play our part in the creation of a just society.","1","2023-11-09 21:48:25","2023-11-20 23:55:53","UNSW Sydney" +"377","Politecnico di Torino","polito","logo/polito.jpg","https://www.polito.it/","Politecnico di Torino was the first Italian Engineering School founded in the wave of the technical and scientific innovation that gave rise to the most prestigious European polytechnic schools in the mid-19th century. Founded as School for Engineers in 1859, it then became Regio Politecnico di Torino in 1906. Engineers, architects, designers and urban planners have been trained at Politecnico di Torino for over 160 years with rigor, integrity and high-level standards. This long ever-changing history has rated Politecnico among the top European technical Universities for education and research, with 38,700 students and a teaching staff of more than 1,000. In an evolving global context disrupted by the effects of globalization, climate change, population aging, new and increasingly pervasive technologies, Universities are expected to progress in order to produce an impact on a rapidly changing society. Politecnico di Torino has therefore decided to transform itself into a “platf...","1","2023-11-09 21:52:02","2023-11-20 23:55:59","PoliTo" +"378","3DHISTECH Ltd.","3dhistech","logo/3dhistech.jpg","https://www.3dhistech.com/","3DHISTECH is dedicated to providing clinical pathologists, researchers and universities with digital pathology solutions to facilitate quick and accurate diagnostics, supporting medical discoveries and fostering education.","1","2023-11-10 16:46:05","2023-11-20 23:56:09","" +"379","3Scan","3scan","logo/3scan.jpg","www.3scan.com","This organization may no longer exist, has rebranded, or has been merged under another organization.","1","2023-11-10 16:46:07","2023-11-20 23:56:14","" +"380","MedicalPHIT","medicalphit","logo/medicalphit.jpeg","https://phit.nl/","We make hIT work'. MedicalPHIT employs experts in the field of data exchange, interoperability and IT in healthcare. The focus is on smart solutions to improve healthcare processes. 'We make hIT work' is one of our core values ​​for good reason. We score well on customer and employee satisfaction. We achieve this by being curious and sharing our knowledge. But also by operating as a close-knit team, with independence and making an impact of paramount importance.","1","2023-11-10 16:48:00","2023-11-20 23:56:35","" +"381","Roche Holding AG","roche","logo/roche.jpg","https://www.roche.com/","Throughout our 125-year history, Roche has grown into one of the world’s largest biotech companies, as well as a leading provider of in-vitro diagnostics and a global supplier of transformative innovative solutions across major disease areas. Our commitment to our people, partners, stakeholders and, most importantly, our patients remains as strong as it was on the first day of our journey.","1","2023-11-10 16:49:26","2023-11-21 00:13:31","" +"382","Sakura Finetek USA","sakura","logo/sakura.jpeg","https://www.sakuraus.com/","At Sakura Finetek, we are committed to advancing cancer diagnostics by providing integrated solutions for anatomic pathology and patients through best-in-class innovation, quality and customer care.","1","2023-11-10 16:51:21","2023-11-21 00:13:33","" +"383","Sectra","sectra","logo/sectra.jpg","https://sectra.com/","Driven by knowledge and passion, our vision is to contribute to a healthier and safer society. Sectra successfully develops and sells cutting-edge solutions in the expanding niche segments of medical IT and cybersecurity. The Sectra Group has some 800 employees worldwide.","1","2023-11-10 16:52:42","2023-11-21 00:13:37","" +"384","Pathomation","pathomation","logo/pathomation.jpeg","https://www.pathomation.com/","Pathomation is a Belgian digital pathology company. It was founded in 2012 by pathologists Mark Kockx and Wim Waelput, and data scientist – software expert Yves Sucaet.","1","2023-11-10 16:53:32","2023-11-21 00:13:44","" +"385","MedUni Wien","meduni-vienna","logo/meduni-vienna.png","https://www.meduniwien.ac.at/web/en/","The Medical University of Vienna is a leading medical center. The individual institutes, centers, departments and clinics thereby form an inseparable unity of education, research and patient care.","1","2023-11-10 17:13:34","2023-11-21 00:13:56","" +"386","Laboratory for Ophthalmic Image Analysis","optima","logo/optima.png","https://optima.meduniwien.ac.at/","Laboratory for Ophthalmic Image Analysis (OPTIMA) is an interdisciplinary research lab composed of retinal specialists, computer scientists and software engineers, developing innovative image analysis methods for precision medicine in retinal disease. Our research focus lies on the quantitative analysis of state-of-the-art ophthalmic imaging data, in particular OCT, and the development of prognostic disease models for improved patient management in leading eye diseases. The lab has access to extremely large sets of ophthalmic images and is well-equipped with a dedicated high-performance computing cluster containing the latest generation GPUs. The group keeps close collaboration with several high-performance academic research institutions, as well as partnership with imaging device and pharmaceutical companies. The Medical University of Vienna is an international center of excellence and one of the largest research institutions in Europe located at the heart of historic Vienna. ...","1","2023-11-10 17:16:57","2023-11-21 00:14:06","OPTIMA" +"387","Vienna Reading Center","vrc","logo/vrc.png","https://viennareadingcenter.meduniwien.ac.at/","The Vienna Reading Center (VRC) provides best-in-class imaging services for clinical, pharmaceutical and academic research in the area of ophthalmology. We are a professional team equipped to respond to the requirements of both international multi-center and single-site investigator studies. Our group includes dedicated clinical retinal experts, high-end software development with year-long ophthalmic image analysis background, administrative and quality management personnel and certified readers. The VRC has established a solid network of collaborations with over 600 academic sites distributed across 5 continents, which have served successfully in numerous prospective randomized clinical trials. In addition to our imaging services, we offer a broad range of complementary services to effectively accomplish new therapeutic strategies for ocular diseases. Our services are supported by state-of-the-art technology offering conventional as well as the most specialized methods available...","1","2023-11-10 17:20:56","2023-11-21 00:14:11","VRC" +"388","Laboratoire de Traitement de l’information Médicale","latim","logo/latim.jpg","https://latim.univ-brest.fr/","Born from the complementarity between the field of health and the communication sciences, the LaTIM (""laboratoire de traitement de l’information médicale"" for laboratory of medical information processing) develops a multidisciplinary research driven by members from University of Western Brittany, IMT Atlantique, INSERM and Brest CHRU (university hospitals). Information is at the heart of the research project of the unit; being by nature multimodal, complex, heterogeneous, shared and distributed, it is integrated by researchers into methodological solutions for the sole purpose of improving the actual medical benefit. The field of expression of this research focuses on the therapeutic action in oncology (ACTION team) and in the field of interventional therapies (IMAGINE team). Benefiting from a unit within the CHRU, the UMR (joint research unit) has (in addition to access to its own platforms) a privileged access to hospital technical platforms, as well as to all clinical data and ...","1","2023-11-10 17:33:16","2023-11-21 00:14:26","LaTIM" +"389","European Progression Of Neurological Disease initiative","europond","logo/europond.jpg","http://europond.eu/#:~:text=The%20EuroPOND%20initiative%20is%20a,a%20range%20of%20neurological%20disorders.","The EuroPOND initiative is a unique team of scientists spanning computational neuroscience and clinical neurology. Together we are developing computational models and using state-of-the-art data-science techniques to understand a range of neurological disorders. We are learning characteristic patterns of progression directly from large medical data sets including Alzheimer’s disease, Multiple Sclerosis, normal ageing, and abnormal brain development in preterm infants. These disease signatures will enable improved diagnosis and management of neurological disorders.","1","2023-11-10 17:33:16","2023-11-21 00:14:36","" +"390","Alzheimer's Association","alz","logo/alz.jpg","https://www.alz.org/","The Alzheimer's Association leads the way to end Alzheimer's and all other dementia — by accelerating global research, driving risk reduction and early detection, and maximizing quality care and support.","1","2023-11-10 17:45:22","2023-11-21 00:14:49","ALZ" +"391","Alzheimer's Society","alzheimers-society","logo/alzheimers-society.jpg","https://www.alzheimers.org.uk/","At Alzheimer’s Society we’re working towards a world where dementia no longer devastates lives. We do this by giving help to those living with dementia today, and providing hope for the future. As a Society, we are made up of people with dementia, carers, trusted experts, campaigners, researchers and clinicians. We are the UK’s largest collective force of people with unparalleled knowledge and over 40 years of experience addressing the biggest challenges facing people living with dementia.","1","2023-11-10 17:46:24","2023-11-21 00:14:59","" +"392","Institute for Systems and Computer Engineering, Technology and Science","inesc-tec","logo/inesc-tec.jpg","https://www.inesctec.pt/en","INESC TEC is a private non-profit research association, with Public Interest status, dedicated to scientific research and technological development, technology transfer, advanced consulting and training, and pre-incubation of new technology-based companies. As an institution operating at the interface of the academic and business worlds, bringing closer together academia, companies, public administration, and society, INESC TEC typically applies the knowledge and results generated as part of its research in technology transfer projects, seeking value creation and immediate social relevance.","1","2023-11-10 17:49:29","2023-11-21 00:15:05","INESC TEC" +"393","i3S Association","i3s","logo/i3s.png","https://www.i3s.up.pt/","The i3S Association merges three institutes and researchers from several schools of the UPorto, thus consolidating an extensive collaboration between all institutions spanning many years. The long-term collaboration between IBMC, INEB and IPATIMUP - the three founding institutes of i3S - encompasses joint projects, co-supervision of PhD students, sharing of large equipment and employment of research staff under coordinated policies. Six schools of the UPorto (FMUP, ICBAS, FMDUP, FCUP, FEUP and FFUP) and three hospitals (CH S João, CH Porto and IPO) also contribute to the activities of i3S. This wide participation of schools, research institutions and hospitals in a research institute is unique in Portugal and it is a valuable asset for science and technology development, while creating an environment that feeds real breakthrough research and translation of discoveries into the clinic. The building where i3S is headquartered, still fairly fresh as it was completed in 2015, is also...","1","2023-11-10 17:53:33","2023-11-21 00:15:13","" +"394","Institute of Molecular Pathology and Immunology of the University of Porto","ipatimup","logo/ipatimup.jpeg","https://www.ipatimup.pt/Site/","At a time when budgetary constraints and the pandemic are still being felt in terms of oncological diseases, with an impact on both the increase in mortality and the number of cases diagnosed late, Ipatimup begins a new cycle of fortnightly sessions on cancer literacy with same objectives as the first edition: inform about the most recent therapies in the fight against cancer, simplify concepts, raise awareness of early diagnosis and place patients at the center of the discussion. The initiative, which takes place from January 19 to March 23, 2023, in six district capitals, will once again bring together some of the best national experts, with emphasis on the presence of Prof. Manuel Sobrinho Simões. In this edition, we also have the participation of the renowned actor Jorge Serafim who, through popular tales and some humor, will humanize the theme. The initiative is carried out in partnership with Antena1, RTP and Roche Foundation Medicine and also has the support of Merck.","1","2023-11-10 17:57:21","2023-11-21 00:15:32","IPATIMUP" +"395","Isfahan University of Medical Sciences","mui","","http://www.mui.ac.ir/","As one of the oldest scientific institutions in Iran, Isfahan University of Medical sciences and Health Services abbreviated as MUI has been a pioneer in medical education and research, as well as delivery of health and treatment services in the country. MUI established in 1946, is a first degree governmental university. Faculties are medical sciences oriented with a new trend toward medical engineering and biomedical sciences. It is located in metropolitan city of Isfahan the center of Isfahan province, at central area of Iran. Currently it has more than 1500 academic members working in nine faculties and more then 40 research centers. MUI is responsible for delivery of health services across the vast expanse of the health network which was created in 1985 with the integration of medical education and health services provision in the country. Currently more than 20 health networks and 18 teaching hospitals are covering the health management system of the province.","1","2023-11-10 18:22:25","2023-11-10 18:24:34","MUI" +"396","Shri Guru Gobind Singhji Institute of Engineering and Technology","sggs","logo/sggs.jpg","https://www.sggs.ac.in/","Established in 1981, Shri Guru Gobind Singhji Institute of Engineering and Technology (SGGSIET), Nanded, is one of the promising leader institutions in technical education, research and technology transfer. Since its inception, the institute is dedicated to students’ centric learning and believes in pursuing academic excellence. It is having neat, clean and green campus spread over land of 46 acres. It receives 100% grant-in aid from Government of Maharashtra. In less than 25 years of its inception, the Institute has made a mark in technical education and quality research which got endorsed by a third party survey constituted by Government of Maharashtra and headed by Dr. F. C. Kohli, Chairman, TCS. Through that survey conducted in 2004, SGGSIE&T, Nanded is identified as an Institute which can be raised to the level of Center of Excellence along with three other well established organizations such as College of Engineering, Pune; VJTI, Mumbai and ICT, Mumbai. The institute offers...","1","2023-11-10 18:31:41","2023-11-21 00:15:58","SGGS" +"397","Universiti Teknologi PETRONAS","utp","logo/utp.jpg","https://www.utp.edu.my/Pages/Home.aspx","Universiti Teknologi PETRONAS (UTP) was established on 10 January 1997 and is the best private university in Malaysia. The campus is built on a 400 hectare (1,000 acres) site strategically located at Bandar Seri Iskandar, Perak Darul Ridzuan, Malaysia. The university is a wholly-owned subsidiary of PETRONAS, the national oil and gas company of Malaysia. UTP offers a wide range of industry-relevant engineering, science and technology programmes at undergraduate and postgraduate levels. It aims to produce well-rounded graduates with excellent leadership qualities and communication abilities. The university conducts extensive research activities in collaboration with PETRONAS and other institutions and industries, locally and abroad, on six research focus and niche areas. They are self-sustainable building, transport infrastructure, health analytics, hydrocarbon recovery, contaminant management and autonomous system.","1","2023-11-10 18:34:58","2023-11-21 00:16:11","UTP" +"398","Inserm","inserm","logo/inserm.jpg","https://www.inserm.fr/en/home/","Founded in 1964, Inserm is a public scientific and technological institute which operates under the joint authority of the French Ministries of Health and Research. The institute is dedicated to biomedical research and human health, and is involved in the entire range of activities from the laboratory to the patient’s bedside. It also partners with the most prestigious research institutions in the world that are committed to scientific challenges and progress in these fields.","1","2023-11-10 18:36:35","2023-11-21 00:16:21","" +"399","University of Edinburgh","university-of-edinburgh","logo/university-of-edinburgh.jpeg","https://www.ed.ac.uk/","Imagine what you could do at a world-leading university that is globally recognised for its teaching, research and innovation. The University of Edinburgh has been providing students with world-class teaching for more than 425 years, unlocking the potential of some of the world's leading thinkers since 1583.","1","2023-11-10 18:37:36","2023-11-21 00:16:27","" +"400","University of Texas Health Science Center at Houston","uth","logo/uthealth-houston.jpg","https://www.uth.edu/","UTHealth Houston is Texas’ resource for health care education, innovation, scientific discovery, and excellence in patient care. With half a century of experience, UTHealth Houston is one of the nation’s most comprehensive academic health centers.","1","2023-11-10 18:40:53","2023-11-21 00:16:36","UTH" +"401","Université de Bourgogne","ub","logo/u-bourgogne.jpg","https://en.u-bourgogne.fr/","uB fulfils a dual mission of education and research in all scientific fields. Located in Burgundy between Paris and Lyon, the city of Dijon is home to uB's main campus, with several others spread across the region. It offers 400 different degrees across all levels (Bachelor, Master, and PhD), employs 3,000 staff members, and enrols 34,000 students, among whom more than 2,900 are international. Most programmes are taught in French, but a growing number are taught in English.","1","2023-11-10 18:41:53","2023-11-21 00:16:45","uB" +"402","Shushrusha Hospital","shushrusha","logo/shushrusha.jpg","https://www.shushrushahospital.org/index.html","Around the period of 1965-70s the state of Maharashtra was undergoing sea change in its development under the able leadership of the then Chief Minister, Shri YB Chavan who initiated the cooperative movement in a big way. Taking advantage of this movement and to benefit the masses, the hospital was conceptualized and planned by Late Dr Vasant Shripad Ranadive under the auspices of Shushrusha Citizen’s Cooperative Hospital Society, Dadar (W). The hospital was founded in 1966, having been registered in 1964, under The Maharashtra Cooperative Societies Act, 1960, and under Maharashtra Nursing Homes Registration Act, 1949. The completed building was inaugurated by the then prime minister of India, Mrs Indira Gandhi, in 1969. Originally it started with 2 floors. Dr Ranadive passed away in 1971. Shortly thereafter it entered a phase of slackening of patient flow when Dr Nandu S Laud, MS (Ortho), took the responsibility of rejuvenating it and developed it to the present level in a gradu...","1","2023-11-10 18:44:45","2023-11-21 00:16:53","" +"403","Dr. Shankarrao Chavan Government Medical College","drscgmc","logo/drscgmc.jpeg","https://www.drscgmcnanded.in/index.php","Dr.Shankarrao Chavan Government Medical College (Dr.SCGMC) & Hospital - Vishnupuri, situated in Nanded city of Maharashtra. It was established in 1988. The College shifted to the Vishnupuri, Nanded area in March 2015 located on the Nanded-Latur State Highway. Initially, started in 1988, in the Vazirabad area of Nanded attached to Shri Guru Gobind Singhji Memorial Civil hospital.The hospital has grown into a much bigger hospital in an area of 115 acres campus after its shift to the Vishnupuri, Nanded area in the outskirts of the city offering a huge scope for expansion in future in all aspects of medical education research & further development in all technical specialities.","1","2023-11-10 20:07:33","2023-11-21 00:17:00","Dr.SCGMC" +"404","Computational Structural Biology Group","computational-structural-biology-group-","logo/biozentrum.jpg","http://www.biozentrum.unibas.ch/schwede/","","3","2023-11-11 01:27:47","2023-11-21 00:19:37","" +"405","Swiss Institute of Bioinformatics (SIB)","sib","logo/sib.jpg","http://sib.swiss/","SIB is a leading organization in biological and biomedical data science. It maximizes the impact of, and investments in scientific projects by making data FAIR (Findable, Accessible, Interoperable and Reusable), provides long-term access to leading Swiss biodata resources, and is a high-quality partner enabling innovation in academia, hospitals and industry. It does this through its complementary pillars on coordination, open databases and software tools, and centre of excellence.","3","2023-11-13 22:23:58","2023-11-21 00:17:21","SIB" +"406","Biozentrum of the University of Basel","biozentrum","logo/biozentrum.jpg","http://www.biozentrum.unibas.ch/","The Biozentrum of the University of Basel is one of the leading life sciences institutes in the world. The primary focus is basic molecular and biomedical research and teaching. It’s international and interdisciplinary research groups explore how molecules and cells create life, spanning the scale from atom to organism. Founded in 1971, the Biozentrum has been the birth place of many fundamental discoveries in biology and medicine, spawning several Nobel Laureates.","3","2023-11-13 22:24:00","2023-11-21 00:17:11","" +"407","National Institute of Aging","nia","logo/nih.png","https://www.nia.nih.gov/","NIA leads a broad scientific effort to understand the nature of aging and to extend the healthy, active years of life. NIA is the primary federal agency supporting and conducting Alzheimer's disease research.","3","2023-11-16 22:06:31","2023-11-21 00:13:03","NIA" +"408","National Aeronautics and Space Administration","nasa","logo/nasa.jpg","https://www.nasa.gov/","NASA explores the unknown in air and space, innovates for the benefit of humanity, and inspires the world through discovery.","1","2023-11-16 22:08:34","2023-11-21 00:17:31","NASA" +"414","CDC National Center for Injury Prevention and Control","ncipc","logo/cdc-ncipc.jpg","https://www.cdc.gov/injury/","For 30 years, CDC’s National Center for Injury Prevention and Control (Injury Center) has been a leader in protecting Americans from injury and violence so that individuals, families, and communities can be safe, healthy, and thriving. We work proactively with our partners to track trends, conduct research, raise awareness, and implement prevention programs.","1","2023-12-06 07:22:56","2023-12-06 08:50:23","NCIPC" +"415","Centers for Disease Control and Prevention","cdc","logo/cdc.jpg","https://www.cdc.gov/injury/","CDC is the nation’s leading science-based, data-driven, service organization that protects the public’s health. For more than 70 years, we’ve put science into action to help children stay healthy so they can grow and learn; to help families, businesses, and communities fight disease and stay strong; and to protect the public’s health.","2","2023-12-06 07:26:44","2023-12-06 08:15:44","CDC" +"416","United States Consumer Product Safety Commission","cpsc","logo/cpsc.jpg","https://www.cpsc.gov/","CPSC works to save lives and keep families safe by reducing the unreasonable risk of injuries and deaths associated with consumer products and fulfilling its vision to be the recognized global leader in consumer product safety. CPSC does this by: 1) Issuing and enforcing mandatory standards or banning consumer products if no feasible standard would adequately protect the public; 2) Obtaining the recall of products and arranging for a repair, replacement or refund for recalled products; 3) Researching potential product hazards; 4) Developing voluntary standards with standards organizations, manufacturers and businesses; 5) Informing and educating consumers directly and through traditional, online, and social media and by working with foreign, state and local governments and private organizations; and 6) Educating manufacturers worldwide about our regulations, supply chain integrity and development of safe products.","1","2023-12-06 07:29:21","2023-12-06 07:33:21","CPSC" +"417","VisioMel","visiomel","","https://www.sfpathol.org/actions-data-challenge-2022-23-francais.html","VisioMel began in 2021 when the French Society of Pathology, the French Society of Dermatology, the French Cutaneous Cancers Group, and the National Professional Council of Pathologists decided to build a challenge using clinical variables from a national database on melanoma (RIC-Mel).","1","2023-12-06 07:39:45","2023-12-06 07:41:13","" +"418","Health Data Hub","hdh","logo/hdh.png","https://www.health-data-hub.fr/","Health data can be useful to improve the health system, making it more efficient, more personalized and more humanistic. Every citizen deserves it! It is through the processing and cross-referencing of a large volume of quality data that the most impactful research can be carried out: improving the screening and diagnosis of a disease, analyzing the side effects of treatments, developing trials. clinics... We offer a set of services to support the players who contribute to finding tomorrow's solutions to improve the health of citizens: supporting project leaders, building and operating a technological platform to offer them the best tools, bringing together and formatting the data with the greatest potential for research.","2","2023-12-06 07:39:52","2023-12-06 07:43:28","HDH" +"419","Délégation ministérielle au Numérique en Santé","dns","logo/dns.jpg","https://gnius.esante.gouv.fr/en/players/player-profiles/delegation-ministerielle-au-numerique-en-sante-dns","The Ministerial Delegation for eHealth (DNS) is responsible for steering all eHealth transformation projects. The DNS reports directly to the Minister of Health. It closely oversees the Agence du Numérique en Santé (""ANS""). To bring all the stakeholders on board, the major pillars of eHealth policy are debated by the eHealth Council. The delegation also seeks advice from an ethics unit to ensure that its actions are consistent with humanist values and to interface with European and international initiatives relating to eHealth. The technical doctrine of the eHealth roadmap and the associated architecture diagram are updated regularly.","1","2023-12-06 07:51:13","2023-12-06 07:51:13","DNS" +"420","French Society of Pathology","sfp","logo/sfp.png","https://www.sfpathol.org/actions-data-challenge-2022-23-francais.html","The SFP brings together pathologists from all modes of practice. It is governed as an association under the law of 1901, recognized as being of public utility. Our goal is to promote pathological anatomy and cytology in all its aspects. The SFP is a partner of the ICCR (International Collaboration on Cancer Reporting)","1","2023-12-06 07:53:48","2023-12-06 08:01:20","SFP" +"421","Grand Défi","grand-defi","logo/dns.jpg","https://www.gouvernement.fr/decouvrir-les-grands-defis","The Grand Challenges, chosen by the Innovation Council and financed to the tune of €120M per year by the Fund for Innovation and Industry (FII), aim to respond to societal challenges in strategic areas requiring the lifting technological barriers.","1","2023-12-06 08:01:20","2023-12-06 08:03:51","" +"422","CDC National Center for Health Statistics","nchs","logo/cdc-nchs.jpg","https://www.cdc.gov/nchs/index.htm","NCHS provides timely and accurate health statistics for the United States.","1","2023-12-06 08:15:35","2023-12-06 08:50:27","NCHS" +"423","UCI Machine Learning Repository","uci-machine-learning-repository","logo/uci-ml-repo.png","https://archive.ics.uci.edu/","The UCI Machine Learning Repository is a collection of databases, domain theories, and data generators that are used by the machine learning community for the empirical analysis of machine learning algorithms. The archive was created as an ftp archive in 1987 by UCI PhD student David Aha. Since that time, it has been widely used by students, educators, and researchers all over the world as a primary source of machine learning datasets.","2","2023-12-06 08:24:19","2023-12-06 08:27:58","" +"424","National Oceanic and Atmospheric Administration","noaa","logo/noaa.jpg","https://www.noaa.gov/","National Oceanic and Atmospheric Administration (NOAA) is an agency that enriches life through science. Our reach goes from the surface of the sun to the depths of the ocean floor as we work to keep the public informed of the changing environment around them.","1","2023-12-06 08:31:23","2023-12-06 08:32:49","NOAA" +"425","U.S. Department of Commerce","us-department-of-commerce","logo/us-dept-commerce.jpg","https://www.commerce.gov/","The Department of Commerce’s mission is to create the conditions for economic growth and opportunity for all communities.","1","2023-12-06 08:33:26","2023-12-06 08:34:14","" +"426","AARP Foundation","aarp-foundation","logo/aarp.png","https://www.aarp.org/aarp-foundation/","AARP Foundation creates and advances effective solutions to reduce poverty for and with older adults. In 2022, the people AARP Foundation served received more than $726 million in income, benefits, refunds, and credits. We fought systemic injustice, and we helped older adults with low income seize opportunities to re-enter the workforce, bolster their budgets, give back to their communities, and recover from disasters. But we didn’t do it alone. Our donors, partners, volunteers, board, and staff were united in a single purpose: to ensure that vulnerable older adults could secure the essentials. Together, we made a difference.","1","2023-12-06 08:38:27","2023-12-06 08:40:04","" +"427","Planned Parenthood Federation of America","ppfa","logo/ppfa.jpg","https://www.plannedparenthood.org/","Planned Parenthood is a trusted health care provider, an informed educator, a passionate advocate, and a global partner helping similar organizations around the world. Planned Parenthood delivers vital reproductive health care, sex education, and information to millions of people worldwide.","1","2023-12-06 08:47:14","2023-12-06 08:48:09","PPFA" +"428","CDC National Survey of Family Growth","nsfg","logo/cdc-nchs.jpg","https://www.cdc.gov/nchs/nsfg/index.htm?CDC_AA_refVal=https%3A%2F%2Fwww.cdc.gov%2Fnchs%2Fnsfg.htm","The National Survey of Family Growth (NSFG) gathers information on pregnancy and births, marriage and cohabitation, infertility, use of contraception, family life, and general and reproductive health. The survey results are used by the U.S. Department of Health and Human Services and others to plan health services and health education programs, and to do statistical studies of families, fertility, and health.","1","2023-12-06 08:49:39","2023-12-06 08:51:01","NSFG" +"429","altLabs","altlabs","logo/altlabs.jpg","https://altlabs.tech/","altLabs is a research non-profit institution focused on the development and advancement of safety-promoting technologies. We collaborate with world-class researchers across diverse scientific fields to prioritize thoughtful solutions with long-term positive impact on a global scale. In a nutshell, we’re working to make the world a safer place.","1","2023-12-06 08:56:57","2023-12-06 08:59:34","" +"430","iGEM","igem","logo/igem.jpg","https://igem.org/","iGEM educates the workforce and the leaders of the Synthetic Biology industry. The iGEM Foundation is an independent, non-profit organization dedicated to the advancement of synthetic biology, education and competition, and the development of an open, collaborative, and cooperative community.","1","2023-12-06 08:58:34","2023-12-06 08:59:36","" diff --git a/apps/openchallenges/organization-service/src/main/resources/openapi.yaml b/apps/openchallenges/organization-service/src/main/resources/openapi.yaml index 4d81b466c7..93fb244921 100644 --- a/apps/openchallenges/organization-service/src/main/resources/openapi.yaml +++ b/apps/openchallenges/organization-service/src/main/resources/openapi.yaml @@ -257,31 +257,42 @@ components: example: 1 format: int64 type: integer - Email: - description: An email address. - example: john.smith@example.com - format: email - type: string OrganizationLogin: - description: The login of an organization + description: The unique login of an organization. example: example-org maxLength: 64 minLength: 2 pattern: "^[a-z0-9]+(?:-[a-z0-9]+)*$" type: string + Url: + description: A URL to the website or image. + example: https://openchallenges.io + format: url + maxLength: 500 + nullable: true + type: string + CreatedDatetime: + description: Datetime when metadata was added to the OC database. + example: 2022-07-04T22:19:11Z + format: date-time + type: string + ModifiedDatetime: + description: Datetime when metadata was last modified in the OC database. + example: 2022-07-04T22:19:11Z + format: date-time + type: string Organization: description: An organization example: createdAt: 2022-07-04T22:19:11Z avatarKey: logo/dream.png - websiteUrl: https://example.com + websiteUrl: https://openchallenges.io acronym: OC name: Example organization description: A description of the organization. id: 1 challengeCount: 10 login: example-org - email: john.smith@example.com updatedAt: 2022-07-04T22:19:11Z properties: id: @@ -290,55 +301,58 @@ components: format: int64 type: integer name: + description: The name of the organization. example: Example organization type: string - email: - description: An email address. - example: john.smith@example.com - format: email - type: string login: - description: The login of an organization + description: The unique login of an organization. example: example-org maxLength: 64 minLength: 2 pattern: "^[a-z0-9]+(?:-[a-z0-9]+)*$" type: string description: + description: A description of the organization. example: A description of the organization. + nullable: true type: string avatarKey: example: logo/dream.png type: string websiteUrl: - example: https://example.com + description: A URL to the website or image. + example: https://openchallenges.io format: url + maxLength: 500 + nullable: true type: string challengeCount: + default: 0 + description: The number of challenges involving this organization. example: 10 - format: int32 minimum: 0 type: integer createdAt: + description: Datetime when metadata was added to the OC database. example: 2022-07-04T22:19:11Z format: date-time type: string updatedAt: + description: Datetime when metadata was last modified in the OC database. example: 2022-07-04T22:19:11Z format: date-time type: string acronym: + description: An acronym of the organization. example: OC + maxLength: 10 type: string required: - createdAt - - description - - email - id - login - name - updatedAt - - websiteUrl type: object OrganizationsPage: allOf: diff --git a/apps/openchallenges/organization-service/src/test/java/org/sagebionetworks/openchallenges/organization/service/model/mapper/OrganizationMapperTest.java b/apps/openchallenges/organization-service/src/test/java/org/sagebionetworks/openchallenges/organization/service/model/mapper/OrganizationMapperTest.java index 66dc66825a..ebd340f04a 100644 --- a/apps/openchallenges/organization-service/src/test/java/org/sagebionetworks/openchallenges/organization/service/model/mapper/OrganizationMapperTest.java +++ b/apps/openchallenges/organization-service/src/test/java/org/sagebionetworks/openchallenges/organization/service/model/mapper/OrganizationMapperTest.java @@ -14,7 +14,6 @@ public void ConvertToEntity_ShouldReturnDtoProperties_WhenDtoPropertiesPassed() dto.setName("Test Organization"); dto.setDescription("This is a test organization"); dto.setId(4599L); - dto.setEmail("testemail@test.edu"); dto.setLogin("login"); dto.setAvatarKey("avatar Key"); dto.setWebsiteUrl("url"); @@ -28,7 +27,6 @@ public void ConvertToEntity_ShouldReturnDtoProperties_WhenDtoPropertiesPassed() // verify the entity properties were copied Assertions.assertEquals(entity.getId(), dto.getId()); Assertions.assertEquals(entity.getName(), dto.getName()); - Assertions.assertEquals(entity.getEmail(), dto.getEmail()); Assertions.assertEquals(entity.getLogin(), dto.getLogin()); Assertions.assertEquals(entity.getAvatarKey(), dto.getAvatarKey()); Assertions.assertEquals(entity.getWebsiteUrl(), dto.getWebsiteUrl()); @@ -46,7 +44,6 @@ public void ConvertToEntity_ShouldReturnDtoProperties_WhenDtoPropertiesPassed() entity.setName("Test Organization"); entity.setDescription("This is a test organization"); entity.setId(4599L); - entity.setEmail("testemail@test.edu"); entity.setLogin("login"); entity.setAvatarKey("avatar Key"); entity.setWebsiteUrl("url"); @@ -60,7 +57,6 @@ public void ConvertToEntity_ShouldReturnDtoProperties_WhenDtoPropertiesPassed() // verify the entity properties were copied Assertions.assertEquals(entity.getId(), dto.getId()); Assertions.assertEquals(entity.getName(), dto.getName()); - Assertions.assertEquals(entity.getEmail(), dto.getEmail()); Assertions.assertEquals(entity.getLogin(), dto.getLogin()); Assertions.assertEquals(entity.getAvatarKey(), dto.getAvatarKey()); Assertions.assertEquals(entity.getWebsiteUrl(), dto.getWebsiteUrl()); diff --git a/libs/openchallenges/api-client-angular/src/lib/.openapi-generator/FILES b/libs/openchallenges/api-client-angular/src/lib/.openapi-generator/FILES index 2b6d90ff20..2265932581 100644 --- a/libs/openchallenges/api-client-angular/src/lib/.openapi-generator/FILES +++ b/libs/openchallenges/api-client-angular/src/lib/.openapi-generator/FILES @@ -21,7 +21,6 @@ model/challengeContribution.ts model/challengeContributionRole.ts model/challengeContributionsPage.ts model/challengeContributionsPageAllOf.ts -model/challengeDifficulty.ts model/challengeDirection.ts model/challengeIncentive.ts model/challengeInputDataType.ts diff --git a/libs/openchallenges/api-client-angular/src/lib/model/challenge.ts b/libs/openchallenges/api-client-angular/src/lib/model/challenge.ts index 1f98944ffa..31a0980c80 100644 --- a/libs/openchallenges/api-client-angular/src/lib/model/challenge.ts +++ b/libs/openchallenges/api-client-angular/src/lib/model/challenge.ts @@ -11,7 +11,6 @@ */ import { SimpleChallengePlatform } from './simpleChallengePlatform'; import { SimpleChallengeInputDataType } from './simpleChallengeInputDataType'; -import { ChallengeDifficulty } from './challengeDifficulty'; import { ChallengeStatus } from './challengeStatus'; import { ChallengeIncentive } from './challengeIncentive'; import { ChallengeSubmissionType } from './challengeSubmissionType'; @@ -26,7 +25,7 @@ export interface Challenge { */ id: number; /** - * The slug of the challenge. + * The unique slug of the challenge. */ slug: string; /** @@ -36,17 +35,25 @@ export interface Challenge { /** * The headline of the challenge. */ - headline?: string; + headline?: string | null; /** * The description of the challenge. */ description: string; - doi?: string; + /** + * The DOI of the challenge. + */ + doi?: string | null; status: ChallengeStatus; - difficulty: ChallengeDifficulty; platform?: SimpleChallengePlatform | null; - websiteUrl?: string; - avatarUrl?: string; + /** + * A URL to the website or image. + */ + websiteUrl?: string | null; + /** + * A URL to the website or image. + */ + avatarUrl?: string | null; incentives: Array; submissionTypes: Array; inputDataTypes?: Array; @@ -62,7 +69,13 @@ export interface Challenge { * The number of times the challenge has been starred by users. */ starredCount: number; + /** + * Datetime when metadata was added to the OC database. + */ createdAt: string; + /** + * Datetime when metadata was last modified in the OC database. + */ updatedAt: string; } diff --git a/libs/openchallenges/api-client-angular/src/lib/model/challengeDifficulty.ts b/libs/openchallenges/api-client-angular/src/lib/model/challengeDifficulty.ts deleted file mode 100644 index c2e961e731..0000000000 --- a/libs/openchallenges/api-client-angular/src/lib/model/challengeDifficulty.ts +++ /dev/null @@ -1,24 +0,0 @@ -/** - * OpenChallenges REST API - * No description provided (generated by Openapi Generator https://github.com/openapitools/openapi-generator) - * - * The version of the OpenAPI document: 1.0.0 - * - * - * NOTE: This class is auto generated by OpenAPI Generator (https://openapi-generator.tech). - * https://openapi-generator.tech - * Do not edit the class manually. - */ - - -/** - * The difficulty level of a challenge. - */ -export type ChallengeDifficulty = 'good_for_beginners' | 'intermediate' | 'advanced'; - -export const ChallengeDifficulty = { - GoodForBeginners: 'good_for_beginners' as ChallengeDifficulty, - Intermediate: 'intermediate' as ChallengeDifficulty, - Advanced: 'advanced' as ChallengeDifficulty -}; - diff --git a/libs/openchallenges/api-client-angular/src/lib/model/challengeSearchQuery.ts b/libs/openchallenges/api-client-angular/src/lib/model/challengeSearchQuery.ts index 090c36fd27..2fe1043474 100644 --- a/libs/openchallenges/api-client-angular/src/lib/model/challengeSearchQuery.ts +++ b/libs/openchallenges/api-client-angular/src/lib/model/challengeSearchQuery.ts @@ -12,7 +12,6 @@ import { ChallengeDirection } from './challengeDirection'; import { ChallengeCategory } from './challengeCategory'; import { ChallengeSort } from './challengeSort'; -import { ChallengeDifficulty } from './challengeDifficulty'; import { ChallengeStatus } from './challengeStatus'; import { ChallengeIncentive } from './challengeIncentive'; import { ChallengeSubmissionType } from './challengeSubmissionType'; @@ -36,10 +35,6 @@ export interface ChallengeSearchQuery { */ sortSeed?: number | null; direction?: ChallengeDirection | null; - /** - * An array of challenge difficulty levels used to filter the results. - */ - difficulties?: Array; /** * An array of challenge incentive types used to filter the results. */ diff --git a/libs/openchallenges/api-client-angular/src/lib/model/models.ts b/libs/openchallenges/api-client-angular/src/lib/model/models.ts index ad2cf89d5a..ae37a08e44 100644 --- a/libs/openchallenges/api-client-angular/src/lib/model/models.ts +++ b/libs/openchallenges/api-client-angular/src/lib/model/models.ts @@ -5,7 +5,6 @@ export * from './challengeContribution'; export * from './challengeContributionRole'; export * from './challengeContributionsPage'; export * from './challengeContributionsPageAllOf'; -export * from './challengeDifficulty'; export * from './challengeDirection'; export * from './challengeIncentive'; export * from './challengeInputDataType'; diff --git a/libs/openchallenges/api-client-angular/src/lib/model/organization.ts b/libs/openchallenges/api-client-angular/src/lib/model/organization.ts index 9f082ab97b..97e3e51578 100644 --- a/libs/openchallenges/api-client-angular/src/lib/model/organization.ts +++ b/libs/openchallenges/api-client-angular/src/lib/model/organization.ts @@ -19,21 +19,38 @@ export interface Organization { * The unique identifier of an organization */ id: number; - name: string; /** - * An email address. + * The name of the organization. */ - email: string; + name: string; /** - * The login of an organization + * The unique login of an organization. */ login: string; - description: string; + /** + * A description of the organization. + */ + description?: string | null; avatarKey?: string; - websiteUrl: string; + /** + * A URL to the website or image. + */ + websiteUrl?: string | null; + /** + * The number of challenges involving this organization. + */ challengeCount?: number; + /** + * Datetime when metadata was added to the OC database. + */ createdAt: string; + /** + * Datetime when metadata was last modified in the OC database. + */ updatedAt: string; + /** + * An acronym of the organization. + */ acronym?: string; } diff --git a/libs/openchallenges/api-description/build/challenge.openapi.yaml b/libs/openchallenges/api-description/build/challenge.openapi.yaml index e1a898db01..253f2b28d3 100644 --- a/libs/openchallenges/api-description/build/challenge.openapi.yaml +++ b/libs/openchallenges/api-description/build/challenge.openapi.yaml @@ -178,14 +178,6 @@ components: enum: - asc - desc - ChallengeDifficulty: - description: The difficulty level of a challenge. - type: string - enum: - - good_for_beginners - - intermediate - - advanced - example: intermediate ChallengeIncentive: description: The incentive type of the challenge. type: string @@ -268,11 +260,6 @@ components: nullable: true direction: $ref: '#/components/schemas/ChallengeDirection' - difficulties: - description: An array of challenge difficulty levels used to filter the results. - type: array - items: - $ref: '#/components/schemas/ChallengeDifficulty' incentives: description: An array of challenge incentive types used to filter the results. type: array @@ -369,7 +356,7 @@ components: format: int64 example: 1 ChallengeSlug: - description: The slug of the challenge. + description: The unique slug of the challenge. type: string minLength: 3 maxLength: 255 @@ -385,6 +372,7 @@ components: type: string minLength: 0 maxLength: 80 + nullable: true example: Example challenge headline ChallengeDescription: description: The description of the challenge. @@ -392,6 +380,13 @@ components: minLength: 0 maxLength: 1000 example: This is an example description of the challenge. + ChallengeDoi: + description: The DOI of the challenge. + type: string + format: url + maxLength: 120 + nullable: true + example: https://doi.org/123/abc ChallengePlatformId: description: The unique identifier of a challenge platform. type: integer @@ -412,11 +407,18 @@ components: $ref: '#/components/schemas/ChallengePlatformSlug' name: $ref: '#/components/schemas/ChallengePlatformName' + nullable: true required: - id - slug - name + Url: + description: A URL to the website or image. + type: string + format: url + maxLength: 500 nullable: true + example: https://openchallenges.io ChallengeInputDataTypeId: description: The unique identifier of a challenge input data type. type: integer @@ -458,6 +460,16 @@ components: format: date nullable: true example: '2017-07-21' + CreatedDatetime: + description: Datetime when metadata was added to the OC database. + type: string + format: date-time + example: '2022-07-04T22:19:11Z' + ModifiedDatetime: + description: Datetime when metadata was last modified in the OC database. + type: string + format: date-time + example: '2022-07-04T22:19:11Z' Challenge: type: object description: A challenge @@ -473,19 +485,15 @@ components: description: $ref: '#/components/schemas/ChallengeDescription' doi: - type: string + $ref: '#/components/schemas/ChallengeDoi' status: $ref: '#/components/schemas/ChallengeStatus' - difficulty: - $ref: '#/components/schemas/ChallengeDifficulty' platform: $ref: '#/components/schemas/SimpleChallengePlatform' websiteUrl: - type: string - format: url + $ref: '#/components/schemas/Url' avatarUrl: - type: string - format: url + $ref: '#/components/schemas/Url' incentives: type: array items: @@ -506,21 +514,18 @@ components: description: The number of times the challenge has been starred by users. type: integer default: 0 + minimum: 0 + example: 100 createdAt: - type: string - format: date-time - example: '2022-07-04T22:19:11Z' + $ref: '#/components/schemas/CreatedDatetime' updatedAt: - type: string - format: date-time - example: '2022-07-04T22:19:11Z' + $ref: '#/components/schemas/ModifiedDatetime' required: - id - slug - name - description - status - - difficulty - incentives - submissionTypes - starredCount diff --git a/libs/openchallenges/api-description/build/openapi.yaml b/libs/openchallenges/api-description/build/openapi.yaml index 828f0fe919..df6b59252f 100644 --- a/libs/openchallenges/api-description/build/openapi.yaml +++ b/libs/openchallenges/api-description/build/openapi.yaml @@ -328,14 +328,6 @@ components: enum: - asc - desc - ChallengeDifficulty: - description: The difficulty level of a challenge. - type: string - enum: - - good_for_beginners - - intermediate - - advanced - example: intermediate ChallengeIncentive: description: The incentive type of the challenge. type: string @@ -418,11 +410,6 @@ components: nullable: true direction: $ref: '#/components/schemas/ChallengeDirection' - difficulties: - description: An array of challenge difficulty levels used to filter the results. - type: array - items: - $ref: '#/components/schemas/ChallengeDifficulty' incentives: description: An array of challenge incentive types used to filter the results. type: array @@ -521,7 +508,7 @@ components: format: int64 example: 1 ChallengeSlug: - description: The slug of the challenge. + description: The unique slug of the challenge. type: string minLength: 3 maxLength: 255 @@ -537,6 +524,7 @@ components: type: string minLength: 0 maxLength: 80 + nullable: true example: Example challenge headline ChallengeDescription: description: The description of the challenge. @@ -544,6 +532,13 @@ components: minLength: 0 maxLength: 1000 example: This is an example description of the challenge. + ChallengeDoi: + description: The DOI of the challenge. + type: string + format: url + maxLength: 120 + nullable: true + example: 'https://doi.org/123/abc' ChallengePlatformId: description: The unique identifier of a challenge platform. type: integer @@ -564,11 +559,18 @@ components: $ref: '#/components/schemas/ChallengePlatformSlug' name: $ref: '#/components/schemas/ChallengePlatformName' + nullable: true required: - id - slug - name + Url: + description: A URL to the website or image. + type: string + format: url + maxLength: 500 nullable: true + example: 'https://openchallenges.io' ChallengeInputDataTypeId: description: The unique identifier of a challenge input data type. type: integer @@ -610,6 +612,16 @@ components: format: date nullable: true example: '2017-07-21' + CreatedDatetime: + description: Datetime when metadata was added to the OC database. + type: string + format: date-time + example: '2022-07-04T22:19:11Z' + ModifiedDatetime: + description: Datetime when metadata was last modified in the OC database. + type: string + format: date-time + example: '2022-07-04T22:19:11Z' Challenge: type: object description: A challenge @@ -625,19 +637,15 @@ components: description: $ref: '#/components/schemas/ChallengeDescription' doi: - type: string + $ref: '#/components/schemas/ChallengeDoi' status: $ref: '#/components/schemas/ChallengeStatus' - difficulty: - $ref: '#/components/schemas/ChallengeDifficulty' platform: $ref: '#/components/schemas/SimpleChallengePlatform' websiteUrl: - type: string - format: url + $ref: '#/components/schemas/Url' avatarUrl: - type: string - format: url + $ref: '#/components/schemas/Url' incentives: type: array items: @@ -658,21 +666,18 @@ components: description: The number of times the challenge has been starred by users. type: integer default: 0 + minimum: 0 + example: 100 createdAt: - type: string - format: date-time - example: '2022-07-04T22:19:11Z' + $ref: '#/components/schemas/CreatedDatetime' updatedAt: - type: string - format: date-time - example: '2022-07-04T22:19:11Z' + $ref: '#/components/schemas/ModifiedDatetime' required: - id - slug - name - description - status - - difficulty - incentives - submissionTypes - starredCount @@ -1052,13 +1057,8 @@ components: description: A string of search terms used to filter the results. type: string example: data provider - Email: - description: An email address. - type: string - format: email - example: john.smith@example.com OrganizationLogin: - description: The login of an organization + description: The unique login of an organization. type: string minLength: 2 maxLength: 64 @@ -1071,45 +1071,40 @@ components: id: $ref: '#/components/schemas/OrganizationId' name: + description: The name of the organization. type: string example: Example organization - email: - $ref: '#/components/schemas/Email' login: $ref: '#/components/schemas/OrganizationLogin' description: + description: A description of the organization. type: string + nullable: true example: A description of the organization. avatarKey: type: string example: logo/dream.png websiteUrl: - type: string - format: url - example: 'https://example.com' + $ref: '#/components/schemas/Url' challengeCount: + description: The number of challenges involving this organization. type: integer - format: int32 minimum: 0 + default: 0 example: 10 createdAt: - type: string - format: date-time - example: '2022-07-04T22:19:11Z' + $ref: '#/components/schemas/CreatedDatetime' updatedAt: - type: string - format: date-time - example: '2022-07-04T22:19:11Z' + $ref: '#/components/schemas/ModifiedDatetime' acronym: + description: An acronym of the organization. type: string + maxLength: 10 example: OC required: - id - name - - email - login - - description - - websiteUrl - createdAt - updatedAt OrganizationsPage: @@ -1128,6 +1123,11 @@ components: - organizations x-java-class-annotations: - '@lombok.Builder' + Email: + description: An email address. + type: string + format: email + example: john.smith@example.com UserCreateRequest: type: object description: The information required to create a user account diff --git a/libs/openchallenges/api-description/build/organization.openapi.yaml b/libs/openchallenges/api-description/build/organization.openapi.yaml index d0211f4f48..c4199afc42 100644 --- a/libs/openchallenges/api-description/build/organization.openapi.yaml +++ b/libs/openchallenges/api-description/build/organization.openapi.yaml @@ -166,18 +166,30 @@ components: type: integer format: int64 example: 1 - Email: - description: An email address. - type: string - format: email - example: john.smith@example.com OrganizationLogin: - description: The login of an organization + description: The unique login of an organization. type: string minLength: 2 maxLength: 64 pattern: ^[a-z0-9]+(?:-[a-z0-9]+)*$ example: example-org + Url: + description: A URL to the website or image. + type: string + format: url + maxLength: 500 + nullable: true + example: https://openchallenges.io + CreatedDatetime: + description: Datetime when metadata was added to the OC database. + type: string + format: date-time + example: '2022-07-04T22:19:11Z' + ModifiedDatetime: + description: Datetime when metadata was last modified in the OC database. + type: string + format: date-time + example: '2022-07-04T22:19:11Z' Organization: type: object description: An organization @@ -185,45 +197,40 @@ components: id: $ref: '#/components/schemas/OrganizationId' name: + description: The name of the organization. type: string example: Example organization - email: - $ref: '#/components/schemas/Email' login: $ref: '#/components/schemas/OrganizationLogin' description: + description: A description of the organization. type: string + nullable: true example: A description of the organization. avatarKey: type: string example: logo/dream.png websiteUrl: - type: string - format: url - example: https://example.com + $ref: '#/components/schemas/Url' challengeCount: + description: The number of challenges involving this organization. type: integer - format: int32 minimum: 0 + default: 0 example: 10 createdAt: - type: string - format: date-time - example: '2022-07-04T22:19:11Z' + $ref: '#/components/schemas/CreatedDatetime' updatedAt: - type: string - format: date-time - example: '2022-07-04T22:19:11Z' + $ref: '#/components/schemas/ModifiedDatetime' acronym: + description: An acronym of the organization. type: string + maxLength: 10 example: OC required: - id - name - - email - login - - description - - websiteUrl - createdAt - updatedAt OrganizationsPage: diff --git a/libs/openchallenges/api-description/src/components/schemas/Challenge.yaml b/libs/openchallenges/api-description/src/components/schemas/Challenge.yaml index e8fcc92f9c..604c1db5b5 100644 --- a/libs/openchallenges/api-description/src/components/schemas/Challenge.yaml +++ b/libs/openchallenges/api-description/src/components/schemas/Challenge.yaml @@ -12,19 +12,17 @@ properties: description: $ref: ChallengeDescription.yaml doi: - type: string + # type: array + # items: + $ref: ChallengeDoi.yaml status: $ref: ChallengeStatus.yaml - difficulty: - $ref: ChallengeDifficulty.yaml platform: $ref: SimpleChallengePlatform.yaml websiteUrl: - type: string - format: url + $ref: Url.yaml avatarUrl: - type: string - format: url + $ref: Url.yaml incentives: type: array items: @@ -37,12 +35,8 @@ properties: type: array items: $ref: SimpleChallengeInputDataType.yaml - # fullName: - # type: string # ownerId: # $ref: AccountId.yaml - # readmeId: - # $ref: ChallengeReadmeId.yaml # featured: # description: Whether the challenge is featured # type: boolean @@ -63,21 +57,18 @@ properties: description: The number of times the challenge has been starred by users. type: integer default: 0 + minimum: 0 + example: 100 createdAt: - type: string - format: date-time - example: '2022-07-04T22:19:11Z' + $ref: CreatedDatetime.yaml updatedAt: - type: string - format: date-time - example: '2022-07-04T22:19:11Z' + $ref: ModifiedDatetime.yaml required: - id - slug - name - description - status - - difficulty - incentives - submissionTypes - starredCount diff --git a/libs/openchallenges/api-description/src/components/schemas/ChallengeCreateRequest.yaml b/libs/openchallenges/api-description/src/components/schemas/ChallengeCreateRequest.yaml index 3b2758884c..d87c838137 100644 --- a/libs/openchallenges/api-description/src/components/schemas/ChallengeCreateRequest.yaml +++ b/libs/openchallenges/api-description/src/components/schemas/ChallengeCreateRequest.yaml @@ -27,8 +27,6 @@ properties: # platformId: # $ref: ChallengePlatformId.yaml # nullable: true - difficulty: - $ref: ChallengeDifficulty.yaml # submissionTypes: # type: array # items: @@ -58,7 +56,6 @@ required: - name - description - status -# - description # example: # name: awesome-challenge # displayName: Awesome Challenge diff --git a/libs/openchallenges/api-description/src/components/schemas/ChallengeDifficulty.yaml b/libs/openchallenges/api-description/src/components/schemas/ChallengeDifficulty.yaml deleted file mode 100644 index 44dc702d11..0000000000 --- a/libs/openchallenges/api-description/src/components/schemas/ChallengeDifficulty.yaml +++ /dev/null @@ -1,7 +0,0 @@ -description: The difficulty level of a challenge. -type: string -enum: - - good_for_beginners - - intermediate - - advanced -example: intermediate diff --git a/libs/openchallenges/api-description/src/components/schemas/ChallengeDoi.yaml b/libs/openchallenges/api-description/src/components/schemas/ChallengeDoi.yaml new file mode 100644 index 0000000000..6811e05ae2 --- /dev/null +++ b/libs/openchallenges/api-description/src/components/schemas/ChallengeDoi.yaml @@ -0,0 +1,6 @@ +description: The DOI of the challenge. +type: string +format: url +maxLength: 120 +nullable: true +example: https://doi.org/123/abc diff --git a/libs/openchallenges/api-description/src/components/schemas/ChallengeHeadline.yaml b/libs/openchallenges/api-description/src/components/schemas/ChallengeHeadline.yaml index b7c9acf6cb..40c017e517 100644 --- a/libs/openchallenges/api-description/src/components/schemas/ChallengeHeadline.yaml +++ b/libs/openchallenges/api-description/src/components/schemas/ChallengeHeadline.yaml @@ -2,4 +2,5 @@ description: The headline of the challenge. type: string minLength: 0 maxLength: 80 +nullable: true example: Example challenge headline diff --git a/libs/openchallenges/api-description/src/components/schemas/ChallengeReadme.yaml b/libs/openchallenges/api-description/src/components/schemas/ChallengeReadme.yaml deleted file mode 100644 index 1908f0470a..0000000000 --- a/libs/openchallenges/api-description/src/components/schemas/ChallengeReadme.yaml +++ /dev/null @@ -1,19 +0,0 @@ -type: object -description: A challenge README -allOf: - - $ref: ChallengeReadmeCreateResponse.yaml - - $ref: ChallengeReadmeCreateRequest.yaml - - type: object - properties: - createdAt: - type: string - format: date-time - updatedAt: - type: string - format: date-time - required: - - createdAt - - updatedAt - example: - createdAt: '2017-07-08T16:18:44-04:00' - updatedAt: '2017-07-08T16:18:44-04:00' diff --git a/libs/openchallenges/api-description/src/components/schemas/ChallengeReadmeCreateRequest.yaml b/libs/openchallenges/api-description/src/components/schemas/ChallengeReadmeCreateRequest.yaml deleted file mode 100644 index abc3faaefd..0000000000 --- a/libs/openchallenges/api-description/src/components/schemas/ChallengeReadmeCreateRequest.yaml +++ /dev/null @@ -1,9 +0,0 @@ -type: object -description: The information used to the README of a challenge -properties: - text: - type: string -required: - - text -example: - text: A great README text diff --git a/libs/openchallenges/api-description/src/components/schemas/ChallengeReadmeCreateResponse.yaml b/libs/openchallenges/api-description/src/components/schemas/ChallengeReadmeCreateResponse.yaml deleted file mode 100644 index 5e0fda8d9e..0000000000 --- a/libs/openchallenges/api-description/src/components/schemas/ChallengeReadmeCreateResponse.yaml +++ /dev/null @@ -1,9 +0,0 @@ -type: object -description: The unique identifier of the challenge README created -properties: - id: - $ref: ChallengeReadmeId.yaml -required: - - id -example: - id: 507f1f77bcf86cd799439011 diff --git a/libs/openchallenges/api-description/src/components/schemas/ChallengeReadmeId.yaml b/libs/openchallenges/api-description/src/components/schemas/ChallengeReadmeId.yaml deleted file mode 100644 index efca0572f4..0000000000 --- a/libs/openchallenges/api-description/src/components/schemas/ChallengeReadmeId.yaml +++ /dev/null @@ -1,3 +0,0 @@ -description: The unique identifier of a challenge README -type: string -example: 507f1f77bcf86cd799439011 diff --git a/libs/openchallenges/api-description/src/components/schemas/ChallengeReadmeUpdateRequest.yaml b/libs/openchallenges/api-description/src/components/schemas/ChallengeReadmeUpdateRequest.yaml deleted file mode 100644 index 1c0e376f5f..0000000000 --- a/libs/openchallenges/api-description/src/components/schemas/ChallengeReadmeUpdateRequest.yaml +++ /dev/null @@ -1,9 +0,0 @@ -type: object -description: The new README content of a challenge -properties: - text: - type: string -required: - - text -example: - text: A great README text diff --git a/libs/openchallenges/api-description/src/components/schemas/ChallengeSearchQuery.yaml b/libs/openchallenges/api-description/src/components/schemas/ChallengeSearchQuery.yaml index 5b2d5a5324..a46d4c3f06 100644 --- a/libs/openchallenges/api-description/src/components/schemas/ChallengeSearchQuery.yaml +++ b/libs/openchallenges/api-description/src/components/schemas/ChallengeSearchQuery.yaml @@ -24,11 +24,6 @@ properties: nullable: true direction: $ref: ChallengeDirection.yaml - difficulties: - description: An array of challenge difficulty levels used to filter the results. - type: array - items: - $ref: ChallengeDifficulty.yaml incentives: description: An array of challenge incentive types used to filter the results. type: array diff --git a/libs/openchallenges/api-description/src/components/schemas/ChallengeSlug.yaml b/libs/openchallenges/api-description/src/components/schemas/ChallengeSlug.yaml index 284b516d69..38c47396e5 100644 --- a/libs/openchallenges/api-description/src/components/schemas/ChallengeSlug.yaml +++ b/libs/openchallenges/api-description/src/components/schemas/ChallengeSlug.yaml @@ -1,4 +1,4 @@ -description: The slug of the challenge. +description: The unique slug of the challenge. type: string minLength: 3 maxLength: 255 diff --git a/libs/openchallenges/api-description/src/components/schemas/CreatedDatetime.yaml b/libs/openchallenges/api-description/src/components/schemas/CreatedDatetime.yaml new file mode 100644 index 0000000000..bf8f871cd7 --- /dev/null +++ b/libs/openchallenges/api-description/src/components/schemas/CreatedDatetime.yaml @@ -0,0 +1,4 @@ +description: Datetime when metadata was added to the OC database. +type: string +format: date-time +example: '2022-07-04T22:19:11Z' diff --git a/libs/openchallenges/api-description/src/components/schemas/ModifiedDatetime.yaml b/libs/openchallenges/api-description/src/components/schemas/ModifiedDatetime.yaml new file mode 100644 index 0000000000..698d40703a --- /dev/null +++ b/libs/openchallenges/api-description/src/components/schemas/ModifiedDatetime.yaml @@ -0,0 +1,4 @@ +description: Datetime when metadata was last modified in the OC database. +type: string +format: date-time +example: '2022-07-04T22:19:11Z' diff --git a/libs/openchallenges/api-description/src/components/schemas/Organization.yaml b/libs/openchallenges/api-description/src/components/schemas/Organization.yaml index 43d77ff701..041bfcabbe 100644 --- a/libs/openchallenges/api-description/src/components/schemas/Organization.yaml +++ b/libs/openchallenges/api-description/src/components/schemas/Organization.yaml @@ -4,44 +4,39 @@ properties: id: $ref: OrganizationId.yaml name: + description: The name of the organization. type: string example: Example organization - email: - $ref: Email.yaml login: $ref: OrganizationLogin.yaml description: + description: A description of the organization. type: string + nullable: true example: A description of the organization. avatarKey: type: string example: logo/dream.png websiteUrl: - type: string - format: url - example: https://example.com + $ref: Url.yaml challengeCount: + description: The number of challenges involving this organization. type: integer - format: int32 minimum: 0 + default: 0 example: 10 createdAt: - type: string - format: date-time - example: '2022-07-04T22:19:11Z' + $ref: CreatedDatetime.yaml updatedAt: - type: string - format: date-time - example: '2022-07-04T22:19:11Z' + $ref: ModifiedDatetime.yaml acronym: + description: An acronym of the organization. type: string + maxLength: 10 example: 'OC' required: - id - name - - email - login - - description - - websiteUrl - createdAt - updatedAt diff --git a/libs/openchallenges/api-description/src/components/schemas/OrganizationCreateRequest.yaml b/libs/openchallenges/api-description/src/components/schemas/OrganizationCreateRequest.yaml index e0bd1e6b86..1309e4219e 100644 --- a/libs/openchallenges/api-description/src/components/schemas/OrganizationCreateRequest.yaml +++ b/libs/openchallenges/api-description/src/components/schemas/OrganizationCreateRequest.yaml @@ -1,8 +1,6 @@ type: object description: The information required to create an org account properties: - email: - $ref: Email.yaml login: $ref: OrganizationLogin.yaml name: diff --git a/libs/openchallenges/api-description/src/components/schemas/OrganizationLogin.yaml b/libs/openchallenges/api-description/src/components/schemas/OrganizationLogin.yaml index 3dc097243f..66b9866248 100644 --- a/libs/openchallenges/api-description/src/components/schemas/OrganizationLogin.yaml +++ b/libs/openchallenges/api-description/src/components/schemas/OrganizationLogin.yaml @@ -1,4 +1,4 @@ -description: The login of an organization +description: The unique login of an organization. type: string minLength: 2 maxLength: 64 diff --git a/libs/openchallenges/api-description/src/components/schemas/SimpleChallengePlatform.yaml b/libs/openchallenges/api-description/src/components/schemas/SimpleChallengePlatform.yaml index ad8f0bd52b..fc9816e4a0 100644 --- a/libs/openchallenges/api-description/src/components/schemas/SimpleChallengePlatform.yaml +++ b/libs/openchallenges/api-description/src/components/schemas/SimpleChallengePlatform.yaml @@ -7,8 +7,8 @@ properties: $ref: ChallengePlatformSlug.yaml name: $ref: ChallengePlatformName.yaml +nullable: true required: - id - slug - name -nullable: true diff --git a/libs/openchallenges/api-description/src/components/schemas/Url.yaml b/libs/openchallenges/api-description/src/components/schemas/Url.yaml new file mode 100644 index 0000000000..0c5537297d --- /dev/null +++ b/libs/openchallenges/api-description/src/components/schemas/Url.yaml @@ -0,0 +1,6 @@ +description: A URL to the website or image. +type: string +format: url +maxLength: 500 +nullable: true +example: https://openchallenges.io diff --git a/libs/openchallenges/challenge-search/src/lib/challenge-search-filters.ts b/libs/openchallenges/challenge-search/src/lib/challenge-search-filters.ts index 86b003c795..5a8d3e4fa5 100644 --- a/libs/openchallenges/challenge-search/src/lib/challenge-search-filters.ts +++ b/libs/openchallenges/challenge-search/src/lib/challenge-search-filters.ts @@ -1,6 +1,5 @@ import { ChallengeCategory, - ChallengeDifficulty, ChallengeIncentive, ChallengeSort, ChallengeStatus, @@ -71,21 +70,6 @@ export const challengeStatusFilter: Filter[] = [ }, ]; -export const challengeDifficultyFilter: Filter[] = [ - { - value: ChallengeDifficulty.GoodForBeginners, - label: 'Good For Beginners', - }, - { - value: ChallengeDifficulty.Intermediate, - label: 'Intermediate', - }, - { - value: ChallengeDifficulty.Advanced, - label: 'Advanced', - }, -]; - export const challengeSubmissionTypesFilter: Filter[] = [ { value: ChallengeSubmissionType.ContainerImage, diff --git a/libs/openchallenges/org-profile/src/lib/mock-org-profiles.ts b/libs/openchallenges/org-profile/src/lib/mock-org-profiles.ts index 8b5765b101..11c13ad524 100644 --- a/libs/openchallenges/org-profile/src/lib/mock-org-profiles.ts +++ b/libs/openchallenges/org-profile/src/lib/mock-org-profiles.ts @@ -2,10 +2,8 @@ import { OrgProfile } from './org-profile'; export const EMPTY_ORG_PROFILE: OrgProfile = { username: '', - email: '', }; export const AWESOME_ORG_PROFILE: OrgProfile = { username: 'awesome-org', - email: 'awesome-org@example.com', }; diff --git a/libs/openchallenges/org-profile/src/lib/org-profile-overview/org-profile-overview.component.html b/libs/openchallenges/org-profile/src/lib/org-profile-overview/org-profile-overview.component.html index b849e59811..ab34e13900 100644 --- a/libs/openchallenges/org-profile/src/lib/org-profile-overview/org-profile-overview.component.html +++ b/libs/openchallenges/org-profile/src/lib/org-profile-overview/org-profile-overview.component.html @@ -3,7 +3,7 @@

Overview

{{ useNaIfFalsey(org.description) }}

-
+ @@ -17,10 +17,6 @@

Organization Details

Acronym {{ useNaIfFalsey(org.acronym) }} - - Contact Email - {{ useNaIfFalsey(org.email) }} -
diff --git a/libs/openchallenges/org-profile/src/lib/org-profile-overview/org-profile-overview.component.ts b/libs/openchallenges/org-profile/src/lib/org-profile-overview/org-profile-overview.component.ts index aad5edc31f..837b98afe8 100644 --- a/libs/openchallenges/org-profile/src/lib/org-profile-overview/org-profile-overview.component.ts +++ b/libs/openchallenges/org-profile/src/lib/org-profile-overview/org-profile-overview.component.ts @@ -18,7 +18,7 @@ export class OrgProfileOverviewComponent { @Input({ required: true }) organization!: Organization; organizationCards: OrganizationCard[] = MOCK_ORGANIZATION_CARDS; - useNaIfFalsey(str: string | undefined) { + useNaIfFalsey(str: string | undefined | null) { return str || 'Not available'; } } diff --git a/libs/openchallenges/org-profile/src/lib/org-profile.ts b/libs/openchallenges/org-profile/src/lib/org-profile.ts index d8337a0e2c..7e310796b1 100644 --- a/libs/openchallenges/org-profile/src/lib/org-profile.ts +++ b/libs/openchallenges/org-profile/src/lib/org-profile.ts @@ -1,5 +1,4 @@ // TODO: To remove once this interface is available from the client library. export interface OrgProfile { username: string; - email: string; } diff --git a/libs/openchallenges/ui/src/lib/challenge-card/challenge-card.component.ts b/libs/openchallenges/ui/src/lib/challenge-card/challenge-card.component.ts index 4d9a674cb9..b5396eacd8 100644 --- a/libs/openchallenges/ui/src/lib/challenge-card/challenge-card.component.ts +++ b/libs/openchallenges/ui/src/lib/challenge-card/challenge-card.component.ts @@ -25,7 +25,6 @@ export class ChallengeCardComponent implements OnInit { incentives!: string; statusClass!: string; time_info!: string | number; - // difficulty!: string | undefined; constructor(private imageService: ImageService) {} @@ -33,9 +32,6 @@ export class ChallengeCardComponent implements OnInit { if (this.challenge) { this.status = this.challenge.status ? this.challenge.status : 'No Status'; this.statusClass = this.challenge.status || ''; - // this.difficulty = this.challenge.difficulty - // ? startCase(this.challenge.difficulty.replace('-', '')) - // : undefined; this.desc = this.challenge.headline ? this.challenge.headline : this.challenge.description; diff --git a/libs/openchallenges/ui/src/lib/challenge-card/mock-challenges.ts b/libs/openchallenges/ui/src/lib/challenge-card/mock-challenges.ts index 37601b49fe..9485e383e7 100644 --- a/libs/openchallenges/ui/src/lib/challenge-card/mock-challenges.ts +++ b/libs/openchallenges/ui/src/lib/challenge-card/mock-challenges.ts @@ -9,7 +9,6 @@ export const MOCK_CHALLENGES: Challenge[] = [ headline: 'Example headline', description: 'Example description', status: 'active', - difficulty: 'good_for_beginners', platform: MOCK_PLATFORMS[0], incentives: [], submissionTypes: [],