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Báo cáo y học: "Harnessing naturally randomized transcription to infer regulatory relationships among genes"

Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Critical Care giúp cho các bạn có thêm kiến thức về ngành y học đề tài: Harnessing naturally randomized transcription to infer regulatory relationships among genes. | Open Access Method Harnessing naturally randomized transcription to infer regulatory relationships among genes Lin S Chen Frank Emmert-Streib and John D Storey Addresses Department of Biostatistics University of Washington 1705 NE Pacific St Seattle WA 98195 USA. Department of Genome Sciences University of Washington 1705 NE Pacific St Seattle WA 98195 USA. Correspondence John D Storey. Email jstorey@u.washington.edu Published II October 2007 Genome Biology 2007 8 R2I9 doi I0.II86 gb-2007-8- I0-r2I9 The electronic version of this article is the complete one and can be found online at http genomebiology.com 2007 8 I0 R2I9 Received 2I May 2007 Revised 24 July 2007 Accepted I I October 2007 2007 Chen 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 We develop an approach utilizing randomized genotypes to rigorously infer causal regulatory relationships among genes at the transcriptional level based on experiments in which genotyping and expression profiling are performed. This approach can be used to build transcriptional regulatory networks and to identify putative regulators of genes. We apply the method to an experiment in yeast in which genes known to be in the same processes and functions are recovered in the resulting transcriptional regulatory network. Background It is now possible to measure DNA variation RNA expression levels and protein expression levels from thousands of genes in a given biologic sample 1-3 . Of great interest is inferring the wiring diagram or the way in which many genes regulate one another and interact from these sources of high-throughput data 4 5 . However this goal is complicated by the fact that RNA levels protein levels phenotypes and environmental conditions may all affect .