Uncovering New Drug Properties in Target-Based Drug-Drug Similarity Networks.

ABSTRACT: Despite recent advances in bioinformatics, systems biology, and machine learning, the accurate prediction of drug properties remains an open problem. Indeed, because the biological environment is a complex system, the traditional approach-based on knowledge about the chemical structures-can not fully explain the nature of interactions between drugs and biological targets. Consequently, in this paper, we propose an unsupervised machine learning approach that uses the information we know about drug-target interactions to infer drug properties. To this end, we define drug similarity based on drug-target interactions and build a weighted Drug-Drug Similarity Network according to the drug-drug similarity relationships. Using an energy-model network layout, we generate drug communities associate

SUBMITTER: Udrescu L 

PROVIDER: S-EPMC7557376 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature