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Breaking the barriers of data scarcity in drug–target affinity prediction

Briefings in Bioinformatics, 2023
Abstract Accurate prediction of drug–target affinity (DTA) is of vital importance in early-stage drug discovery, facilitating the identification of drugs that can effectively interact with specific targets and regulate their activities. While wet experiments remain the most reliable method, they are time-consuming and resource-intensive,
Qizhi Pei, Lijun Wu, Jinhua Zhu
exaly   +4 more sources

Modality-DTA: Multimodality Fusion Strategy for Drug–Target Affinity Prediction

IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2023
Prediction of the drug-target affinity (DTA) plays an important role in drug discovery. Existing deep learning methods for DTA prediction typically leverage a single modality, namely simplified molecular input line entry specification (SMILES) or amino acid sequence to learn representations.
Xixi Yang   +2 more
exaly   +4 more sources

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