Multi-view fusion based on graph convolutional network with attention mechanism for predicting miRNA related to drugs.

ABSTRACT: MicroRNAs (miRNAs) play crucial roles in cancer progression, invasion, and response to treatment, particularly in regulating anticancer drug resistance and sensitivity. Identifying potential human miRNA-drug associations (MDAs) that manifest as resistance or sensitivity relationships offers valuable insights for cancer treatment and drug development. With the growing availability of biological data, computational methods have emerged as powerful tools to complement experimental approaches. However, limited attention has been paid to computational prediction of MDAs. Furthermore, existing approaches typically rely on known MDA information, overlooking the valuable insights available from multi-source data related to miRNAs and drugs. In this study, we present a multi-view fusion-based graph

SUBMITTER: Sheng N 

PROVIDER: S-EPMC12617909 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature