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 synergistic drug combinations via hierarchical molecular representation and cell line latent space fusion.Computer Methods and Programs in Biomedicine, page 108933, 2025
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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.