Network-based methods for gene function prediction

Qingfeng Chen; Yongjie Li; Kai Tan; Yvlu Qiao; Shirui Pan; Taijiao Jiang; Yi-Ping Phoebe Chen

doi:10.1093/bfgp/elab006

Network-based methods for gene function prediction

Brief Funct Genomics. 2021 Jul 17;20(4):249-257. doi: 10.1093/bfgp/elab006.

Authors

Qingfeng Chen¹, Yongjie Li², Kai Tan², Yvlu Qiao², Shirui Pan³, Taijiao Jiang⁴, Yi-Ping Phoebe Chen⁵

Affiliations

¹ University of Technology Sydney, China and Hundred-Talent Program.
² School of Computer and Electronic Information at Guangxi University.
³ Computer science from the University of Technology Sydney.
⁴ Suzhou Institute of System Medicine, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College.
⁵ Department of Computer Science and Computer Engineering, La Trobe University, Melbourne, Australia.

PMID: 33686431
DOI: 10.1093/bfgp/elab006

Abstract

The rapid development of high-throughput technology has generated a large number of biological networks. Network-based methods are able to provide rich information for inferring gene function. This is composed of analyzing the topological characteristics of genes in related networks, integrating biological information, and considering data from different data sources. To promote network biology and related biotechnology research, this article provides a survey for the state of the art of advanced methods of network-based gene function prediction and discusses the potential challenges.

Keywords: computational biology; function prediction; gene function; network integration; network representation; network-based methods.

Network-based methods for gene function prediction

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