Coexpression network based on natural variation in human gene expression reveals gene interactions and functions Export

@article{citeulike:5870912, abstract = {10.1101/gr.097600.109 Genes interact in networks to orchestrate cellular processes. Analysis of these networks provides insights into gene interactions and functions. Here, we took advantage of normal variation in human gene expression to infer gene networks, which we constructed using correlations in expression levels of more than 8.5 million gene pairs in immortalized B cells from three independent samples. The resulting networks allowed us to identify biological processes and gene functions. Among the biological pathways, we found processes such as translation and glycolysis that co-occur in the same subnetworks. We predicted the functions of poorly characterized genes, including and , and provided experimental evidence that is part of the endoplasmic reticulum-associated secretory pathway. We also found that , a susceptibility gene of type 1 diabetes, interacts with , which plays a role in glucose transport. Furthermore, genes that predispose to the same diseases are clustered nonrandomly in the coexpression network, suggesting that networks can provide candidate genes that influence disease susceptibility. Therefore, our analysis of gene coexpression networks offers information on the role of human genes in normal and disease processes.}, author = {Nayak, Renuka R. and Kearns, Michael and Spielman, Richard S. and Cheung, Vivian G.}, citeulike-article-id = {5870912}, citeulike-linkout-0 = {http://dx.doi.org/10.1101/gr.097600.109}, citeulike-linkout-1 = {http://genome.cshlp.org/content/early/2009/09/30/gr.097600.109.abstract}, citeulike-linkout-2 = {http://genome.cshlp.org/content/early/2009/09/30/gr.097600.109.full.pdf}, citeulike-linkout-3 = {http://view.ncbi.nlm.nih.gov/pubmed/19797678}, citeulike-linkout-4 = {http://www.hubmed.org/display.cgi?uids=19797678}, day = {1}, doi = {10.1101/gr.097600.109}, issn = {1549-5477}, journal = {Genome Research}, keywords = {aaa, learning, test1, test11, testing}, month = {November}, number = {11}, pages = {1953--1962}, posted-at = {2009-11-05 06:47:41}, priority = {2}, title = {Coexpression network based on natural variation in human gene expression reveals gene interactions and functions}, url = {http://dx.doi.org/10.1101/gr.097600.109}, volume = {19}, year = {2009} }

TY - JOUR ID - citeulike:5870912 L3 - citeulike-article-id:5870912 N2 - 10.1101/gr.097600.109 Genes interact in networks to orchestrate cellular processes. Analysis of these networks provides insights into gene interactions and functions. Here, we took advantage of normal variation in human gene expression to infer gene networks, which we constructed using correlations in expression levels of more than 8.5 million gene pairs in immortalized B cells from three independent samples. The resulting networks allowed us to identify biological processes and gene functions. Among the biological pathways, we found processes such as translation and glycolysis that co-occur in the same subnetworks. We predicted the functions of poorly characterized genes, including and , and provided experimental evidence that is part of the endoplasmic reticulum-associated secretory pathway. We also found that , a susceptibility gene of type 1 diabetes, interacts with , which plays a role in glucose transport. Furthermore, genes that predispose to the same diseases are clustered nonrandomly in the coexpression network, suggesting that networks can provide candidate genes that influence disease susceptibility. Therefore, our analysis of gene coexpression networks offers information on the role of human genes in normal and disease processes. IS - 11 JF - Genome Research SN - 1549-5477 EP - 1962 TI - Coexpression network based on natural variation in human gene expression reveals gene interactions and functions VL - 19 SP - 1953 KW - aaa KW - learning KW - test1 KW - test11 KW - testing AU - Nayak, Renuka AU - Kearns, Michael AU - Spielman, Richard AU - Cheung, Vivian PY - 2009/11/01/ UR - http://dx.doi.org/10.1101/gr.097600.109 ER -