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This article is part of the supplement: Selected articles from The 8th Annual Biotechnology and Bioinformatics Symposium (BIOT-2011)

Open Access Research

An effective method for network module extraction from microarray data

Priyakshi Mahanta1, Hasin A Ahmed1, Dhruba K Bhattacharyya1* and Jugal K Kalita2

Author Affiliations

1 Dept. of Comp. Sc. and Engg, Tezpur University, Napaam, Tezpur, India

2 Dept. of Computer Science, University of Colorado, Colorado Springs, USA

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BMC Bioinformatics 2012, 13(Suppl 13):S4  doi:10.1186/1471-2105-13-S13-S4

Published: 24 August 2012

Abstract

Background

The development of high-throughput Microarray technologies has provided various opportunities to systematically characterize diverse types of computational biological networks. Co-expression network have become popular in the analysis of microarray data, such as for detecting functional gene modules.

Results

This paper presents a method to build a co-expression network (CEN) and to detect network modules from the built network. We use an effective gene expression similarity measure called NMRS (Normalized mean residue similarity) to construct the CEN. We have tested our method on five publicly available benchmark microarray datasets. The network modules extracted by our algorithm have been biologically validated in terms of Q value and p value.

Conclusions

Our results show that the technique is capable of detecting biologically significant network modules from the co-expression network. Biologist can use this technique to find groups of genes with similar functionality based on their expression information.