Comparative analysis of network algorithms to address modularity with gene expression temporal data
Pages 876 - 882
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.
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- Comparative analysis of network algorithms to address modularity with gene expression temporal data
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September 2013
987 pages
ISBN:9781450324342
DOI:10.1145/2506583
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Published: 22 September 2013
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