Deterministic graph-theoretic algorithm for detecting modules in biological interaction networks.

TitleDeterministic graph-theoretic algorithm for detecting modules in biological interaction networks.
Publication TypeJournal Article
Year of Publication2010
AuthorsChang RL, Luo F, Johnson S, Scheuermann RH
JournalInt J Bioinform Res Appl
Volume6
Issue2
Pagination101-19
Date Published2010
ISSN1744-5485
KeywordsAlgorithms, Protein Interaction Mapping, Proteome, Proteomics
Abstract

An approach for module identification, Modules of Networks (MoNet), introduced an intuitive module definition and clear detection method using edges ranked by the Girvan-Newman algorithm. Modules from a yeast network showed significant association with biological processes, indicating the method's utility; however, systematic bias leads to varied results across trials. MoNet modules also exclude some network regions. To address these shortcomings, we developed a deterministic version of the Girvan-Newman algorithm and a new agglomerative algorithm, Deterministic Modularization of Networks (dMoNet). dMoNet simultaneously processes structurally equivalent edges while preserving intuitive foundations of the MoNet algorithm and generates modules with full network coverage.

DOI10.1504/IJBRA.2010.032115
PubMed URLhttp://www.ncbi.nlm.nih.gov/pubmed/20223734?dopt=Abstract
Alternate TitleInt J Bioinform Res Appl
PubMed ID20223734