Fig. 1From: A learning-based method for drug-target interaction prediction based on feature representation learning and deep neural networkThe flowchart of DTI-CNN pipeline. The DTI-CNN contains heterogeneous-network-based feature extractor, denoising-autoencoder-based feature selector and CNN-based interaction predictor. First, the features are extracted from seven networks of drug and protein by the Jaccard similarity coefficient and RWR algorithm, then we get the low-dimensional representation of drug and protein features by adopting the DAE model. Third, a deep CNN model is constructed to predict the interaction of each pair of drugs and proteinsBack to article page