Drug-target interactions prediction using marginalized denoising model on heterogeneous networks.

ABSTRACT:

Background

Drugs achieve pharmacological functions by acting on target proteins. Identifying interactions between drugs and target proteins is an essential task in old drug repositioning and new drug discovery. To recommend new drug candidates and reposition existing drugs, computational approaches are commonly adopted. Compared with the wet-lab experiments, the computational approaches have lower cost for drug discovery and provides effective guidance in the subsequent experimental verification. How to integrate different types of biological data and handle the sparsity of drug-target interaction data are still great challenges.

Results

In this paper, we propose a novel drug-target interactions (DTIs) prediction method incorporating marginalized denoising model on heterogen

SUBMITTER: Tang C 

PROVIDER: S-EPMC7653902 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature