NTD-DR: Nonnegative tensor decomposition for drug repositioning.

ABSTRACT: Computational drug repositioning aims to identify potential applications of existing drugs for the treatment of diseases for which they were not designed. This approach can considerably accelerate the traditional drug discovery process by decreasing the required time and costs of drug development. Tensor decomposition enables us to integrate multiple drug- and disease-related data to boost the performance of prediction. In this study, a nonnegative tensor decomposition for drug repositioning, NTD-DR, is proposed. In order to capture the hidden information in drug-target, drug-disease, and target-disease networks, NTD-DR uses these pairwise associations to construct a three-dimensional tensor representing drug-target-disease triplet associations and integrates them with similarity informati

SUBMITTER: Jamali AA 

PROVIDER: S-EPMC9302855 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature