Fig. 1From: MFSynDCP: multi-source feature collaborative interactive learning for drug combination synergy predictionThe workflows of the MFSynDCP model framework process. Drug molecular graphs are generated based on the SMILES sequences of drugs, and their feature embeddings are obtained using a GAT. Additionally, feature embeddings of cancer cell line gene expression profiles are acquired using a MLP. The embedding vectors of the drugs and cell lines are then concatenated and input into a multi-source feature interactive learning controller for the fusion of multi-source features. Finally, the fused features are fed into the prediction module for predicting the synergistic effects of drug combinationsBack to article page