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.
Predicting effective drug com- binations using gradient tree boosting based on features extracted from drug-protein heterogeneous network.BMC bioinformatics, 20(1):645
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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.