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Báo cáo y học: " Ranking candidate genes in rat models of type 2 diabetes"
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Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học quốc tế cung cấp cho các bạn kiến thức về ngành y đề tài: "Ranking candidate genes in rat models of type 2 diabetes | Theoretical Biology and Medical Modelling BioMed Central Open Access Ranking candidate genes in rat models of type 2 diabetes Lars Andersson 1 Greta Petersen1 and Fredrik Stâhl2 Address Department of Cell and Molecular Biology-Genetics Gõteborg University Box 462 SE 40530 Gõteborg Sweden and 2School of Health Science University Collage of Borâs SE-501 90 Borâs Sweden Email Lars Andersson - lars.andersson@gen.gu.se Greta Petersen - greta.petersen@gen.gu.se Fredrik Stâhl - fredrik.stahl@hb.se Corresponding author Published 3 July 2009 Received 10 October 2008 Theoretical Biology and Medical Modelling 2009 6 12 doi 10.1186 1742-4682-6-12 Accepted 3 July 2009 This article is available from http www.tbiomed.cOm content 6 1 12 2009 Andersson et al licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License http creativecommons.org licenses by 2.0 which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract__ Background Rat models are frequently used to find genomic regions that contribute to complex diseases so called quantitative trait loci QTLs . In general the genomic regions found to be associated with a quantitative trait are rather large covering hundreds of genes. To help selecting appropriate candidate genes from QTLs associated with type 2 diabetes models in rat we have developed a web tool called Candidate Gene Capture CGC specifically adopted for this disorder. Methods CGC combines diabetes-related genomic regions in rat with rat human homology data textual descriptions of gene effects and an array of 789 keywords. Each keyword is assigned values that reflect its co-occurrence with 24 different reference terms describing sub-phenotypes of type 2 diabetes for example insulin resistance . The genes are then ranked based on the occurrences of .