LM-DTI: a tool of predicting drug-target interactions using the node2vec and network path score methods.

ABSTRACT: Introduction: Drug-target interaction (DTI) prediction is a key step in drug function discovery and repositioning. The emergence of large-scale heterogeneous biological networks provides an opportunity to identify drug-related target genes, which led to the development of several computational methods for DTI prediction. Methods: Considering the limitations of conventional computational methods, a novel tool named LM-DTI based on integrated information related to lncRNAs and miRNAs was proposed, which adopted the graph embedding (node2vec) and the network path score methods. First, LM-DTI innovatively constructed a heterogeneous information network containing eight networks composed of four types of nodes (drug, target, lncRNA, and miRNA). Next, the node2vec method was used t

SUBMITTER: Li J 

PROVIDER: S-EPMC10203599 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature