A Machine Learning-Based Biological Drug-Target Interaction Prediction Method for a Tripartite Heterogeneous Network.

ABSTRACT: Drug repositioning is the identification of interactions between drugs and target proteins in pharmaceutical sciences. Traditional large-scale validation through chemical experiments is time-consuming and expensive, while drug repositioning can drastically decrease the cost and duration taken by traditional drug development. With the rapid advancement of high-throughput technologies and the explosion of various biological and medical data, computational drug repositioning methods have been used to systematically identify potential drug-target interactions. Some of them are based on a particular class of machine learning algorithms called kernel methods. In this paper, we propose a new machine learning prediction method combining multiple kernels into a tripartite heterogeneous drug-target-

SUBMITTER: Zheng Y 

PROVIDER: S-EPMC7860102 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature