ResGIN-Att predicts drug synergy by extracting multi-scale molecular features with residual GIN, fusing them via LSTM, and modeling interactions with cross-attention, achieving competitive results on five benchmark datasets.
Systems pharma- cology: bridging systems biology and pharmacokinetics- pharmacodynamics (pkpd) in drug discovery and develop- ment.Pharmaceutical research, 28(7):1460–1464, 2011
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Drug Synergy Prediction via Residual Graph Isomorphism Networks and Attention Mechanisms
ResGIN-Att predicts drug synergy by extracting multi-scale molecular features with residual GIN, fusing them via LSTM, and modeling interactions with cross-attention, achieving competitive results on five benchmark datasets.