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.

引用

页数：14

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