Multimodal contrastive learning for integrating molecular representations and cellular phenotypes in drug-target interaction prediction.

Abstract excerpt

MOTIVATION: Accurate prediction of drug-target interactions (DTIs) is fundamental to drug discovery and mechanistic understanding. While deep learning has advanced computational DTI prediction, most existing methods rely primarily on molecular structural representations, including drug structures and protein sequences, while overlooking cellular phenotypes that reflect downstream biological effects. Cell Painting...

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