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MGDTA: EXPLORING MULTIGRANULAR REPRESENTATIONS FOR DRUG-TARGET BINDING AFFINITY PREDICTION
Code and data for reproducing the results of machine-learning vs classical scoring functions on a similarity-based benchmark
MulinforCPI: enhancing precision of compound-protein interaction prediction through novel perspectives on multi-level information integration
Method for drug repurposing from knowledge graphs and literature
NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions
NHGNN-DTA: A Node-adaptive Hybrid Graph Neural Network for Interpretable Drug-target Binding Affinity Prediction
Applications of Ollivier Ricci Curvature in Biomolecular Data Analysis
A multiple-layer inter-molecular contact features based deep neural network for protein-ligand binding affinity prediction
Improving protein–ligand docking and screening accuracies by incorporating a scoring function correction term
Comparison of active site and full kinase sequences for drug-target affinity prediction and molecular generation. Full paper: https://pubs.acs.org/doi/10.1021/acs.jcim.1c00889
Bioinformatics'2022 PerceiverCPI: A nested cross-attention network for compound-protein interaction prediction
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