Method
Inferring the functions of longevity genes with modular subnetwork biomarkers of Caenorhabditis elegans aging
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* Corresponding author: Igor Jurisica juris@ai.utoronto.ca
1 Department of Medical Biophysics, University of Toronto, 610 University Avenue, Toronto, M5G 2M9, Canada
2 The Campbell Family Institute for Cancer Research and Ontario Cancer Institute, 101 College Street, TMDT 9-305, Toronto, M5G 1L7, Canada
3 Department of Computer Science, University of Toronto, 10 King's College Road, Toronto, M5S 3G4, Canada
Genome Biology 2010, 11:R13 doi:10.1186/gb-2010-11-2-r13
Published: 3 February 2010Abstract
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.