Fig. 2

Overall framework of DPDDI. The main steps are as follows. First, the feature extractor of DPDDI constructs a two-layer graph convolutional network (GCN) to obtain drug latent features, which capture the complex relations between the drug nodes in the DDI network. Then, each pair of drugs is represented as a feature vector by concatenating the corresponding latent features of the drugs. Last, the feature vectors of representing the drug pairs are fed into a deep neural network to train the predictor to deduce potential DDIs