Assessing the most effective depth for PPI analysis

Jaine K. Blayney, Huiru Zheng, Haiying Wang, Francisco Azuaje

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Protein-protein interaction (PPI) networks are being increasingly used to support functional genomic research. PPI networks can consist of several thousand nodes and sampling is often used to extract meaningful information representative of the global network. However there has been relatively little research carried out on the impact of sampling and significance of depth on such networks. In this study, six PPI networks, three relevant to heart failure, one to asthma, and two consisting of randomly-selected proteins, are analyzed and compared through different network levels. The effect of network depth is examined in terms of network metrics, i.e. degree and betweenness centrality, and on the classification methods for identifying potentially significant nodes, which may represent novel therapeutic targets.

Original languageEnglish
Title of host publicationProceedings - 2009 International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing, IJCBS 2009
Pages286-292
Number of pages7
DOIs
Publication statusPublished - 26 Nov 2009
Externally publishedYes
Event2009 International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing, IJCBS 2009 - Shanghai, China
Duration: 03 Aug 200905 Aug 2009

Publication series

NameProceedings - 2009 International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing, IJCBS 2009

Conference

Conference2009 International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing, IJCBS 2009
CountryChina
CityShanghai
Period03/08/200905/08/2009

Keywords

  • Network depth
  • Network-based drug target novel therapeutic identification
  • Protein interactions

ASJC Scopus subject areas

  • Software
  • Biomedical Engineering

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