A graph auto-encoder model for miRNA-disease associations prediction

• Published in: Briefings in bioinformatics Vol. 22; no. 4
• Main Authors: Li, Zhengwei, Li, Jiashu, Nie, Ru, You, Zhu-Hong, Bao, Wenzheng
• Format: Journal Article
• Language: English
• Published: Oxford Oxford University Press 01.07.2021; Oxford Publishing Limited (England)
• Subjects: Biomarkers; Case studies; Clinical medicine; Coders; Colon; Colorectal cancer; Computer applications; Deregulation; Disease; Esophageal cancer; Esophagus; Graph neural networks; Kidney cancer; MicroRNAs; miRNA; Multilayers; Neoplasms; Network analysis; Neural networks; Nodes; Predictions; Ribonucleic acid; RNA; Tumors; miRNA-disease associations prediction; miRNA; complex disease; graph neural networks; graph auto-encoder; heterogeneous graph

Abstract Emerging evidence indicates that the abnormal expression of miRNAs involves in the evolution and progression of various human complex diseases. Identifying disease-related miRNAs as new biomarkers can promote the development of disease pathology and clinical medicine. However, designing bio...