A hub-attachment based method to detect functional modules from confidence-scored protein interactions and expression profiles

Chia Hao Chin, Shu Hwa Chen, Chin Wen Ho, Ming Tat Ko, Chung Yen Lin

Research output: Contribution to journalArticle

32 Citations (Scopus)

Abstract

Background: Many research results show that the biological systems are composed of functional modules. Members in the same module usually have common functions. This is useful information to understand how biological systems work. Therefore, detecting functional modules is an important research topic in the post-genome era. One of functional module detecting methods is to find dense regions in Protein-Protein Interaction (PPI) networks. Most of current methods neglect confidence-scores of interactions, and pay little attention on using gene expression data to improve their results.Results: In this paper, we propose a novel hub-attachment based method to detect functional modules from confidence-scored protein interactions and expression profiles, and we name it HUNTER. Our method not only can extract functional modules from a weighted PPI network, but also use gene expression data as optional input to increase the quality of outcomes. Using HUNTER on yeast data, we found it can discover more novel components related with RNA polymerase complex than those existed methods from yeast interactome. And these new components show the close relationship with polymerase after functional analysis on Gene Ontology.Conclusion: A C++ implementation of our prediction method, dataset and supplementary material are available at http://hub.iis.sinica.edu.tw/Hunter/. Our proposed HUNTER method has been applied on yeast data, and the empirical results show that our method can accurately identify functional modules. Such useful application derived from our algorithm can reconstruct the biological machinery, identify undiscovered components and decipher common sub-modules inside these complexes like RNA polymerases I, II, III.

Original languageEnglish
Article numberS25
JournalBMC Bioinformatics
Volume11
Issue numberSUPPLL.1
DOIs
Publication statusPublished - Jan 18 2010
Externally publishedYes

Fingerprint

Confidence
Proteins
Protein
Module
Yeast
Interaction
Biological systems
RNA
Gene expression
Protein Interaction Maps
Genes
Protein Interaction Networks
Yeasts
RNA Polymerase I
Protein-protein Interaction
Gene Expression Data
Functional analysis
Biological Systems
DNA-Directed RNA Polymerases
Machinery

ASJC Scopus subject areas

  • Structural Biology
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Applied Mathematics

Cite this

A hub-attachment based method to detect functional modules from confidence-scored protein interactions and expression profiles. / Chin, Chia Hao; Chen, Shu Hwa; Ho, Chin Wen; Ko, Ming Tat; Lin, Chung Yen.

In: BMC Bioinformatics, Vol. 11, No. SUPPLL.1, S25, 18.01.2010.

Research output: Contribution to journalArticle

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