Drug-target interaction prediction through fine-grained selection and bidirectional random walk methodology.

ABSTRACT: The study of drug-target interaction plays an important role in the process of drug development. The subject of DTI forecasting has advanced significantly in the last several years, yielding numerous significant research findings and methodologies. Heterogeneous data sources provide richer information and comprehensive perspectives for drug-target interaction prediction, so many existing methods rely on heterogeneous networks, and graph embedding technology becomes an important technology to extract information from heterogeneous networks. These approaches, however, are less concerned with potential noisy information in heterogeneous networks and more focused on the extent of information extraction in those networks. Based on this, a potential DTI predictive network model called FBRWPC is

SUBMITTER: Wang Y 

PROVIDER: S-EPMC11300600 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature