Refer to .
Leveraging big data to transform target selection and drug discovery.
Harnessing big ‘omics’ data and AI for drug discovery in hepatocellular carcinoma.
Data Types include Genomics (G), Epigenomics (E), Transcriptomics (T), Proteomics (P), Metabolomics (M), Phenomics (P), Imaging (I) .
Mainly list the big data repositories
(***) A Library of Phosphoproteomic and Chromatin Signatures for Characterizing Cellular Responses to Drug Perturbations.
profiled 90 drugs (in triplicate) in six cell lines using two different proteomic assays
(*) Orthotopic patient-derived xenografts of paediatric solid tumours.
sensitivity data of 150 drugs across >20 pediatric cell lines
(*) NCI ALMANAC 5,000 pairs of FDA-approved drugs that were tested against the NCI-60
(***) Liver cancer single cells (Landscape of Infiltrating T Cells in Liver Cancer Revealed by Single-Cell Sequencing).
5,063 single T cells isolated from peripheral blood, tumor, and adjacent normal tissues from six hepatocellular carcinoma patients.