Module detection for bacteria based on spectral clustering of protein-protein functional association networks

Hongwei Wu, Yaming Lin, Fun Choi Chan, Rocio Alba-Flores

Research output: Contribution to book or proceedingConference articlepeer-review

Abstract

Network analysis-based module detection has significant implications in many fields. In cellular/ molecular biology, module detection based on analyses of metabolic/regulatory networks will not only help us understand more about the function and evolution of cellular machinery of an organism, but will also provide tractable contextual information for potential drug targets and facilitate improvements in drug designs. We here present our preliminary study on the module detection for bacteria based on the spectral clustering of the protein-protein functional association networks. We first examined how the parameter of the spectral clustering algorithm (i.e., the number of clusters) affects our module detection results, and demonstrated that when the number of clusters was set too small or too large the resulting module collection deteriorate in terms of gene coverage and intra-module association. We then compared our predicted modules against the randomly generated modules, and demonstrated that our modules (i) have a higher ratio of the intra-module to inter-module gene-gene functional association scores and (ii) can better capture the modularization information inherent in the experimentally verified modules. Finally we compared the module collections of seven bacterial organisms, and observed that modules related to membrane transport and cell motility are among those that are conserved among multiple organisms. Because it is desirable from both scientific and technical points of view to study functional modules at various resolution levels, we believe that the spectral clustering algorithm, with the flexibility rendered by different parameter settings, provides an appropriate solution in terms of capturing the modularization properties of networks and computational affordability.

Original languageEnglish
Title of host publication2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2011
Pages465-472
Number of pages8
DOIs
StatePublished - 2011
Event2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2011 - Atlanta, GA, United States
Duration: Nov 12 2011Nov 15 2011

Publication series

Name2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2011

Conference

Conference2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2011
Country/TerritoryUnited States
CityAtlanta, GA
Period11/12/1111/15/11

Scopus Subject Areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

Keywords

  • Functional Association Network
  • Module
  • Spectral clustering

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