DTAP: a unified graph transformer framework for joint prediction of drug-target affinity and docking pose. [PDF]
Liu J, Ding Y, Yan Y, Zheng L, Pan Y.
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Correction to: Breaking the barriers of data scarcity in drug-target affinity prediction. [PDF]
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MixingDTA: improved drug-target affinity prediction by extending mixup with guilt-by-association. [PDF]
Kim Y +6 more
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UAMRL: multi-granularity uncertainty-aware multimodal representation learning for drug-target affinity prediction. [PDF]
Xu W +5 more
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DualPG-DTA: A Large Language Model-Powered Graph Neural Network Framework for Enhanced Drug-Target Affinity Prediction and Discovery of Novel CDK9 Inhibitors Exhibiting In Vivo Anti-Leukemia Activity. [PDF]
Chen Y +7 more
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MEGDTA: multi-modal drug-target affinity prediction based on protein three-dimensional structure and ensemble graph neural network. [PDF]
Hou Z +5 more
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Dual modality feature fused neural network integrating binding site information for drug target affinity prediction. [PDF]
He H, Chen G, Tang Z, Chen CY.
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Drug target affinity prediction based on multi-scale gated power graph and multi-head linear attention mechanism. [PDF]
Hu S, Hu J, Zhang X, Jin S, Xu X.
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PocketDTA: an advanced multimodal architecture for enhanced prediction of drug-target affinity from 3D structural data of target binding pockets. [PDF]
Zhao L, Wang H, Shi S.
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Machine Learning approach for Drug-Target affinity prediction in Computer Aided Drug Design
Dani NJ +3 more
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