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Int J Bioinform Res Appl. 2010;6(2):101-19.

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

Author information

1
University of California San Diego, La Jolla, San Diego, CA 92093-0412, USA. rlchang@ucsd.edu

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.

PMID:
20223734
DOI:
10.1504/IJBRA.2010.032115
[Indexed for MEDLINE]
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