A Novel Approach for Drug-Target Interactions Prediction Based on Multimodal Deep Autoencoder.

ABSTRACT: Drug targets are biomacromolecules or biomolecular structures that bind to specific drugs and produce therapeutic effects. Therefore, the prediction of drug-target interactions (DTIs) is important for disease therapy. Incorporating multiple similarity measures for drugs and targets is of essence for improving the accuracy of prediction of DTIs. However, existing studies with multiple similarity measures ignored the global structure information of similarity measures, and required manual extraction features of drug-target pairs, ignoring the non-linear relationship among features. In this paper, we proposed a novel approach MDADTI for DTIs prediction based on MDA. MDADTI applied random walk with restart method and positive pointwise mutual information to calculate the topological similarity

SUBMITTER: Wang H 

PROVIDER: S-EPMC6997437 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature