Literature DB >> 33686431

Network-based methods for gene function prediction.

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

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.
© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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

Year:  2021        PMID: 33686431     DOI: 10.1093/bfgp/elab006

Source DB:  PubMed          Journal:  Brief Funct Genomics        ISSN: 2041-2649            Impact factor:   4.241


  1 in total

1.  The Coronavirus Network Explorer: mining a large-scale knowledge graph for effects of SARS-CoV-2 on host cell function.

Authors:  Andreas Krämer; Jean-Noël Billaud; Stuart Tugendreich; Dan Shiffman; Martin Jones; Jeff Green
Journal:  BMC Bioinformatics       Date:  2021-05-03       Impact factor: 3.169

  1 in total

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