Inferring the functions of longevity genes with modular subnetwork biomarkers of Caenorhabditis elegans aging

被引：29
作者：
Fortney, Kristen [1 ]
Kotlyar, Max [1 ]
Jurisica, Igor [1 ,2 ,3 ,4 ]
机构：
[1] Univ Toronto, Dept Med Biophys, Toronto, ON M5G 2M9, Canada
[2] Univ Toronto, Dept Comp Sci, Toronto, ON M5S 3G4, Canada
[3] Campbell Family Inst Canc Res, Toronto, ON M5G 1L7, Canada
[4] Ontario Canc Inst, Toronto, ON M5G 1L7, Canada
来源：
GENOME BIOLOGY | 2010年 / 11卷 / 02期
基金：
加拿大创新基金会;
关键词：
COMMUNITY STRUCTURE; NETWORK ANALYSIS; MICROARRAY DATA; EXPRESSION DATA; PATHWAYS; IDENTIFICATION; CLASSIFICATION; PREDICTION; SIGNATURES; PROFILES;
D O I：
10.1186/gb-2010-11-2-r13
中图分类号：
Q81 [生物工程学（生物技术）]; Q93 [微生物学];
学科分类号：
071005 ; 0836 ; 090102 ; 100705 ;
摘要：
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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页数：14
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