Heterogeneous graph inference based on similarity network fusion for predicting lncRNA-miRNA interaction.

ABSTRACT: LncRNA and miRNA are two non-coding RNA types that are popular in current research. LncRNA interacts with miRNA to regulate gene transcription, further affecting human health and disease. Accurate identification of lncRNA-miRNA interactions contributes to the in-depth study of the biological functions and mechanisms of non-coding RNA. However, relying on biological experiments to obtain interaction information is time-consuming and expensive. Considering the rapid accumulation of gene information and the few computational methods, it is urgent to supplement the effective computational models to predict lncRNA-miRNA interactions. In this work, we propose a heterogeneous graph inference method based on similarity network fusion (SNFHGILMI) to predict potential lncRNA-miRNA interactions. Firs

SUBMITTER: Fan Y 

PROVIDER: S-EPMC9050493 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature