Graph representation learning in bioinformatics: trends, methods and applications

• Published in: Briefings in bioinformatics Vol. 23; no. 1
• Main Authors: Yi, Hai-Cheng, You, Zhu-Hong, Huang, De-Shuang, Kwoh, Chee Keong
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 17.01.2022; Oxford Publishing Limited (England)
• Subjects: Algorithms; Bioinformatics; Complex systems; Computational Biology - methods; Data structures; Deep learning; Embedding; Graph neural networks; Graph representations; Graphical representations; Graphs; Knowledge; Knowledge representation; Learning algorithms; Machine Learning; Neural networks; Neural Networks, Computer; Topology; deep learning; graph embedding; graph neural network; graph representation learning; knowledge graph; healthcare

Abstract Graph is a natural data structure for describing complex systems, which contains a set of objects and relationships. Ubiquitous real-life biomedical problems can be modeled as graph analytics tasks. Machine learning, especially deep learning, succeeds in vast bioinformatics scenarios with d...