MvGraphDTA: multi-view-based graph deep model for drug-target affinity prediction by introducing the graphs and line graphs

During the experiments, we performed data augmentation on all the training sets used. Experimental results showed that MvGraphDTA outperformed the competitive state-of-the-art methods on benchmark datasets for DTA prediction. Additionally, we evaluated the universality and generalization performance of MvGraphDTA on additional datasets. Experimental outcomes revealed that MvGraphDTA exhibited good universality and generalization capability, making it a reliable tool for drug-target interaction prediction.