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Publication : Integrating genetic and network analysis to characterize genes related to mouse weight.

First Author  Ghazalpour A Year  2006
Journal  PLoS Genet Volume  2
Issue  8 Pages  e130
PubMed ID  16934000 Mgi Jnum  J:115983
Mgi Id  MGI:3692672 Doi  10.1371/journal.pgen.0020130
Citation  Ghazalpour A, et al. (2006) Integrating genetic and network analysis to characterize genes related to mouse weight. PLoS Genet 2(8):e130
abstractText  Systems biology approaches that are based on the genetics of gene expression have been fruitful in identifying genetic regulatory loci related to complex traits. We use microarray and genetic marker data from an F2 mouse intercross to examine the large-scale organization of the gene co-expression network in liver, and annotate several gene modules in terms of 22 physiological traits. We identify chromosomal loci (referred to as module quantitative trait loci, mQTL) that perturb the modules and describe a novel approach that integrates network properties with genetic marker information to model gene/trait relationships. Specifically, using the mQTL and the intramodular connectivity of a body weight-related module, we describe which factors determine the relationship between gene expression profiles and weight. Our approach results in the identification of genetic targets that influence gene modules (pathways) that are related to the clinical phenotypes of interest.
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