Table of Contents
ISRN Biomathematics
Volume 2012 (2012), Article ID 726429, 11 pages
http://dx.doi.org/10.5402/2012/726429
Research Article

Partitioning a PPI Network into Overlapping Modules Constrained by High-Density and Periphery Tracking

Computational Systems Biology Lab, Nara Institute of Science and Technology, Ikoma, Nara 630-0101, Japan

Received 13 February 2012; Accepted 14 March 2012

Academic Editors: G. L. Borosky, J. Chow, and J. M. Peregrín-Alvarez

Copyright © 2012 Md. Altaf-Ul-Amin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This paper presents an algorithm called DPClusO for partitioning simple graphs into overlapping modules, that is, clusters constrained by density and periphery tracking. The major advantages of DPClusO over the related and previously published algorithm DPClus are shorter running time and ensuring coverage, that is, each node goes to at least one module. DPClusO is a general-purpose clustering algorithm and useful for finding overlapping cohesive groups in a simple graph for any type of application. This work shows that the modules generated by DPClusO from several PPI networks of yeast with high-density constraint match with more known complexes compared to some other recently published complex generating algorithms. Furthermore, the biological significance of the high density modules has been demonstrated by comparing their P values in the context of Gene Ontology (GO) terms with those of the randomly generated modules having the same size, distribution, and zero density. As a consequence, it was also learnt that a PPI network is a combination of mainly high-density and star-like modules.