Prediction of biomarker–disease associations based on graph attention network and text representation

• Published in: Briefings in bioinformatics Vol. 23; no. 5
• Main Authors: Yang, Minghao, Huang, Zhi-An, Gu, Wenhao, Han, Kun, Pan, Wenying, Yang, Xiao, Zhu, Zexuan
• Format: Journal Article
• Language: English
• Published: Oxford Oxford University Press 20.09.2022; Oxford Publishing Limited (England)
• Subjects: Availability; Biomarkers; Computer applications; Disease; Information resources; Predictions; Representations; Source code; graph attention network; text-based relation representation; lncRNA–disease associations; miRNA–disease associations; bimodal fusion network; microbe–disease associations

Abstract Motivation The associations between biomarkers and human diseases play a key role in understanding complex pathology and developing targeted therapies. Wet lab experiments for biomarker discovery are costly, laborious and time-consuming. Computational prediction methods can be used to great...