Fig. 1

The framework of CNN-DDI algorithm.The algorithm mainly contain two parts, combinational features selection module and CNN-based prediction module. (1)Firstly, features vectors are selected from feature selection module using the four types of features. We encode features and generate binary vectors, each value of the vector represents whether the component exists. Then we calculate Jaccard similarity to measure the correlation between drugs. In this way, we get features vectors as the input of the prediction module.Secondly, features vectors are inputted into prediction module. The prediction module based on CNN consists of convolutional layers, full-connecteed layers and a softmax layer.Convolutional layers can enhance the ability of learning deep characteristics. Through the DDIs’ predictor, we get the probabilities of all DDIs-associated events’ types and select the event with the highest probability