Comparative analysis of network algorithms to address modularity with gene expression temporal data

Authors:
Suhaib Mohammed
Affiliations:
School of Bioscience, University of Exeter, Exeter, United Kingdom, EX4 4QD
Venue:
Proceedings of the International Conference on Bioinformatics, Computational Biology and Biomedical Informatics
Year:
2013

Citing 2
Cited 0

A systematic comparison and evaluation of biclustering methods for gene expression data

Bioinformatics
SIMoNe

Bioinformatics

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Abstract

In recent years, hierarchical networks have received comparatively less attention to explore microarray gene expression data although hierarchical modularity of biological networks has been demonstrated. We compare three networking algorithms for the study of complex biological network modularity: RedeR, weighted correlation network analysis (WGCNA) and statistical inference of modular networks (SIMoNe). Our main contributions in this work include a filtering process, which filters out non-differentially expressed genes and a novel score for performance measurement. We show in this paper how the performance of algorithms can be improved using this filtering process.