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Inferring the Functions of Longevity Genes with Modular Subnetwork Biomarkers of Caenorhabditis Elegans Aging

Overview
Journal Genome Biol
Specialties Biology
Genetics
Date 2010 Feb 5
PMID 20128910
Citations 16
Authors
Affiliations
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Abstract

A central goal of biogerontology is to identify robust gene-expression biomarkers of aging. Here we develop a method where the biomarkers are networks of genes selected based on age-dependent activity and a graph-theoretic property called modularity. Tested on Caenorhabditis elegans, our algorithm yields better biomarkers than previous methods - they are more conserved across studies and better predictors of age. We apply these modular biomarkers to assign novel aging-related functions to poorly characterized longevity genes.

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References
1.
Hwang T, Park T . Identification of differentially expressed subnetworks based on multivariate ANOVA. BMC Bioinformatics. 2009; 10:128. PMC: 2696448. DOI: 10.1186/1471-2105-10-128. View

2.
Edgar R, Domrachev M, Lash A . Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res. 2001; 30(1):207-10. PMC: 99122. DOI: 10.1093/nar/30.1.207. View

3.
Budovsky A, Abramovich A, Cohen R, Chalifa-Caspi V, Fraifeld V . Longevity network: construction and implications. Mech Ageing Dev. 2006; 128(1):117-24. DOI: 10.1016/j.mad.2006.11.018. View

4.
Palla G, Derenyi I, Farkas I, Vicsek T . Uncovering the overlapping community structure of complex networks in nature and society. Nature. 2005; 435(7043):814-8. DOI: 10.1038/nature03607. View

5.
Alexa A, Rahnenfuhrer J, Lengauer T . Improved scoring of functional groups from gene expression data by decorrelating GO graph structure. Bioinformatics. 2006; 22(13):1600-7. DOI: 10.1093/bioinformatics/btl140. View