Skip to content

Shihang-Wang-58/papers_for_molecular_representation

Folders and files

NameName
Last commit message
Last commit date

Latest commit

Β 

History

21 Commits
Β 
Β 

Repository files navigation

contributing

papers_for_molecular_representation

AI_MR

Updating...

Molecular representation (MR) refers to the process of converting molecules into mathematical or computational formats that can be processed by algorithms to model, analyze and predict molecular behavior. Effective molecular representation is critical for many tasks in drug discovery, such as virtual screening, activity prediction, and scaffold hopping, which aim to navigate the chemical space effectively and efficiently.

Contents πŸ“˜

Considering the increasing number of papers in this field, we roughly summarize some articles and put them into the following categories:

Survey πŸ“ƒ

  • [2024] Molecular representations in bio-cheminformatics (Memetic Computing) [paper]
  • [2024] From intuition to AI: evolution of small molecule representations in drug discovery (Briefings in Bioinformatics) [paper]
  • [2024] Image-based molecular representation learning for drug development: a survey (Briefings in Bioinformatics) [paper] [中文解读]
  • [2022] Deep learning methods for molecular representation and property prediction (Drug Discovery Today) [paper]
  • [2021] A review of molecular representation in the age of machine learning (WIREs Computational Molecular Science) [paper]
  • [2021] Geometric deep learning on molecular representations (Nature Machine Intelligence) [paper]
  • [2020] Molecular representations in AI-driven drug discovery: a review and practical guide (Journal of Cheminformatics) [paper]

Datasets πŸ“‚

To be continued...

Tools βš™οΈ

To be continued...

Papers πŸ“ƒ

Molecular_Fingerprints_Descriptors-based_MR

  • [CrossFuse-XGBoost] CrossFuse-XGBoost: accurate prediction of the maximum recommended daily dose through multi-feature fusion, cross-validation screening and extreme gradient boosting (2024) (Briefings in Bioinformatics) [paper] [code] GitHub stars

  • [MapLight] ADMET property prediction through combinations of molecular fingerprints (2023) (arXiv) [paper] [code] GitHub stars

  • [BoostSweet] BoostSweet: Learning molecular perceptual representations of sweeteners (2022) (Food Chemistry) [paper]

  • [FP-BERT] A fingerprints based molecular property prediction method using the BERT model (2022) (Journal of Cheminformatics) [paper] [code] GitHub stars

  • [MolMapNet] Out-of-the-box deep learning prediction of pharmaceutical properties by broadly learned knowledge-based molecular representations (2021) (Nature Machine Intelligence) [paper] [code] GitHub stars

  • [FP-ADMET] FP-ADMET a compendium of fingerprint-based ADMET prediction models (2021) (Journal of Cheminformatics) [paper] [code]

Language_Model-based_MR

  • [t-SMILES] t-SMILES: a fragment-based molecular representation framework for de novo ligand design (2024) (Nature Communications) [paper] [code] GitHub stars

  • [INTransformer] INTransformer: Data augmentation-based contrastive learning by injecting noise into transformer for molecular property prediction (2024) (Journal of Molecular Graphics and Modelling) [paper] [code] GitHub stars

  • [DeepSA] DeepSA: a deep-learning driven predictor of compound synthesis accessibility (2023) (Journal of Cheminformatics) [paper] [code] GitHub stars

  • [MolRoPE-BERT] MolRoPE-BERT: An enhanced molecular representation with Rotary Position Embedding for molecular property prediction (2023) (Journal of Molecular Graphics and Modelling) [paper]

  • [MOLFORMER] Molecular set representation learning (2022) (Nature Machine Intelligence) [paper] [code] GitHub stars

  • [MTL-BERT] Pushing the Boundaries of Molecular Property Prediction for Drug Discovery with Multitask Learning BERT Enhanced by SMILES Enumeration (2022) (Research) [paper] [code] GitHub stars

  • [Mol-BERT] Mol-BERT: An Effective Molecular Representation with BERT for Molecular Property Prediction (2021) (Wireless Communications and Mobile Computing) [paper] [code] GitHub stars

  • [Mol2vec] Mol2vec: Unsupervised Machine Learning Approach with Chemical Intuition (2018) (Journal of Chemical Information and Modeling) [paper] [code] GitHub stars

Graph-based_MR

  • [MMGX] Enhancing property and activity prediction and interpretation using multiple molecular graph representations with MMGX (2024) (Communications Chemistry) [paper] [code] GitHub stars

  • [R-MAT] Relative Molecule Self-Attention Transformer (2024) (Journal of Cheminformatics) [paper] [code] GitHub stars

  • [SMPT] Pre-training molecular representation model with spatial geometry for property prediction (2024) (Computational Biology and Chemistry) [paper] [code] GitHub stars

  • [TOML-BERT] Enhancing Molecular Property Prediction through Task-Oriented Transfer Learning (2024) (Journal of Medicinal Chemistry) [paper] [code] GitHub stars

  • [Gram matrix] Gram matrix: an efficient representation of molecular conformation and learning objective for molecular pretraining (2024) (Briefings in Bioinformatics) [paper] [code] GitHub stars

  • [GSL-MPP] Molecular property prediction based on graph structure learning (2024) (Bioinformatics) [paper] [code] GitHub stars

  • [MolFormer] Large-scale chemical language representations capture molecular structure and properties (2024) (Nature Machine Intelligence) [paper] [code] GitHub stars

  • [FunQG] FunQG: Molecular Representation Learning via Quotient Graphs (2023) (Journal of Chemical Information and Modeling) [paper] [code] GitHub stars

  • [MolCAP] MolCAP: Molecular Chemical reActivity Pretraining and prompted-finetuning enhanced molecular representation learning (2023) (Computers in Biology and Medicine) [paper] [code] GitHub stars

  • [SME] Chemistry-intuitive explanation of graph neural networks for molecular property prediction with substructure masking (2023) (Nature Communications) [paper] [code]

  • [HiMol] Hierarchical Molecular Graph Self-Supervised Learning for Property Prediction (2023) (Communications Chemistry) [paper] [code] GitHub stars

  • [PharmHGT] Pharmacophoric-constrained heterogeneous graph transformer model for molecular property prediction (2023) (Journal of Chemical Information and Modeling) [paper] [code] GitHub stars

  • [IFGN] Predicting molecular properties based on the interpretable graph neural network with multistep focus mechanism (2023) (Briefings in Bioinformatics) [paper]

  • [KANO] Knowledge graph-enhanced molecular contrastive learning with functional prompt. (2023) (Nature Machine Intelligence) [paper] [code] GitHub stars

  • [KPGT] A knowledge-guided pre-training framework for improving molecular representation learning (2023) (Nature Communications) [paper] [code] GitHub stars

  • [ReLMole] ReLMole: Molecular Representation Learning Based on Two-Level Graph Similarities (2022) (Journal of Chemical Information and Modeling) [paper] [code] GitHub stars

  • [GEM] Geometry-enhanced molecular representation learning for property prediction (2022) (Nature Machine Intelligence) [paper] [code] GitHub stars

  • [GraphMVP] Pre-Training Molecular Graph Representation with 3D Geometry (2022) (ICLR 2022) [paper] [code] GitHub stars

  • [MPG] An effective self-supervised framework for learning expressive molecular global representations to drug discovery (2021) (Briefings in Bioinformatics) [paper] [code] GitHub stars

  • [GROVER] Self-Supervised Graph Transformer on Large-Scale Molecular Data (2020) (NIPS2020) [paper] [code] GitHub stars

  • [Attentive FP] Pushing the Boundaries of Molecular Representation for Drug Discovery with the Graph Attention Mechanism (2020) (Journal of Medicinal Chemistry) [paper] [code] GitHub stars

Multimodal-based_MR

  • [MoleSG] Complementary multi-modality molecular self-supervised learning via non-overlapping masking for property prediction (2024) (Briefings in Bioinformatics) [paper] [code] GitHub stars

  • [MMFDL] Multimodal fused deep learning for drug property prediction: Integrating chemical language and molecular graph (2024) (Computational and Structural Biotechnology Journal) [paper] [code] GitHub stars

  • [COATI] COATI:Multimodal Contrastive Pretraining for Representing and Traversing ChemicalSpace (2024) (Journal of Chemical Information and Modeling) [paper] [code] GitHub stars

  • [DLF-MFF] A deep learning framework for predicting molecular property based on multi-type features fusion (2024) (Computers in Biology and Medicine) [paper] [code] GitHub stars

  • [VideoMol] A Molecular Video-derived Foundation Model for Scientific Drug Discovery (2024) (Nature Communications) [paper] [code] GitHub stars

  • [MvMRL] MvMRL: a multi-view molecular representation learning method for molecular property prediction (2024) (Briefings in Bioinformatics) [paper] [code] GitHub stars

  • [PremuNet] A pre-trained multi-representation fusion network for molecular property prediction (2024) (Information Fusion) [paper] [code] GitHub stars

  • [ISMol] Dual-View Learning Based on Images and Sequences for Molecular Property Prediction. (2024) (IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS,) [paper] [code] GitHub stars

  • [CLAMP] Enhancing Activity Prediction Models in Drug Discovery with the Ability to Understand Human Language (2023) (arXiv) [paper] [code] GitHub stars

  • [CGIP] Chemical structure-aware molecular image representation learning (2023) (Briefings in Bioinformatics) [paper] [code] GitHub stars

  • [UniMAP] UniMAP: Universal SMILES-Graph Representation Learning (2023) (arXiv) [paper]

  • [FP-GNN] FP-GNN: a versatile deep learning architecture for enhanced molecular property prediction (2022) (Briefings in Bioinformatics) [paper] [code] GitHub stars

  • [ImageMol] Accurate prediction of molecular properties and drug targets using a self-supervised image representation learning framework (2022) (Nature Machine Intelligence) [paper] [code] GitHub stars

Contrastive_Learning-based_MR

  • [PhenoScreen] PhenoScreen: A Dual-Space Contrastive Learning Framework-based Phenotypic Screening Method by Linking Chemical Perturbations to Cellular Morphology (2024) (BioRxiv) [paper] [code]GitHub stars

  • [MOCO] Molecular Contrastive Pretraining with Collaborative Featurizations (2024) (Journal of Chemical Information and Modeling) [paper]

  • [MolFeSCue] MolFeSCue: enhancing molecular property prediction in data-limited and imbalanced contexts using few-shot and contrastive learning (2024) (Bioinformatics) [paper] [code] GitHub stars

  • [3D-MOL] 3D-Mol: A Novel Contrastive Learning Framework for Molecular Property Prediction with 3D Information (2024) (Pattern Analysis and Applications) [paper] [code] GitHub stars

  • [UniCorn] UniCorn: A Unified Contrastive Learning Approach for Multi-view Molecular Representation Learning (2024) (arXiv) [paper]

  • [3DGCL] 3D graph contrastive learning for molecular property prediction (2023) (Bioinformatics) [paper] [code] GitHub stars

  • [CasANGCL] CasANGCL: pre-training and fine-tuning model based on cascaded attention network and graph contrastive learning for molecular property prediction (2023) (Briefings in Bioinformatics) [paper] [code] GitHub stars

  • [FraSICL] Molecular property prediction by semantic-invariant contrastive learning (2023) (Bioinformatics) [paper] [code] GitHub stars

  • [iMolCLR] Improving Molecular Contrastive Learning via Faulty Negative Mitigation and Decomposed Fragment Contrast (2022) (Journal of Chemical Information and Modeling) [paper] [code] GitHub stars

  • [MolCLR] Molecular contrastive learning of representations via graph neural networks (2022) (Nature Machine Intelligence) [paper] [code] GitHub stars

  • [ATMOL] Attention-wise masked graph contrastive learning for predicting molecular property (2022) (Briefings in Bioinformatics) [paper] [code] GitHub stars

  • [SMICLR] Contrastive Learning on Multiple Molecular Representations for Semisupervised and Unsupervised Representation Learning (2022) (Journal of Chemical Information and Modeling) [paper] [code] GitHub stars

  • [MoCL] MoCL: Data-driven Molecular Fingerprint via Knowledge-aware Contrastive Learning from Molecular Graph (2021) (KDD2021) [paper] [code] GitHub stars

  • [GraphCL] Graph Contrastive Learning with Augmentations (2020) (arXiv) [paper] [code] GitHub stars

3D_Molecular_Structure-based_MR

  • [GeminiMol] Molecular Representation Model Enhanced by Conformational Space Profile (2023) (Advanced Science) [paper] [code]GitHub stars

  • [UniMol] Uni-Mol: A Universal 3D Molecular Representation Learning Framework (2023) (ICLR2023) [paper] [code] GitHub stars

Others

Acknowledgement 🀝

We would like to thank all the developers who have contributed to the field of molecular representation. Shihang Wang thanks Lin Wang , Jianmin Wang and Bo Li for their inspiration and help.

Get in Touch πŸ’Œ

If you have any questions, please feel free to contact Shihang Wang (Email: [email protected]).

Pull requests are highly welcomed!

Star History Chart

About

Collection of papers for Molecular Representation using AI

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published