Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Minireview cung cấp cho các bạn kiến thức về ngành y đề tài: Systematic bioinformatic analysis of expression levels of 17,330 human genes across 9,783 samples from 175 types of healthy and pathological tissues. | Open Access Systematic bioinformatic analysis of expression levels of 17 330 human genes across 9 783 samples from 175 types of healthy and pathological tissues Sami KilpinenH Reija AutioH Kalle Ojala Kristiina Iljin Elmar Bucher Henri Sara Tommi Pisto Matti Saarela Rolf I Skotheim Mari Bjorkman John-Patrick Mpindi Saija Haapa-Paananen Paula Vainio Henrik Edgren Maija Wolf Jaakko Astola Matthias Nees Sampsa Hautaniemi and Olli Kallioniemi Addresses Medical Biotechnology VTT Technical Research Centre and University of Turku Itainen pitkakatu 4C Turku Finland. Institute for Molecular Medicine Finland FIMM University of Helsinki Tukholmankatu 8 Helsinki Finland. Department of Signal Processing Tampere University of Technology Korkeakoulunkatu 1 Tampere Finland. Department of Cancer Prevention Institute for Cancer Research Rikshospitalet-Radiumhospitalet Medical Centre Oslo NO-0310 Norway. Computational Systems Biology Laboratory Institute of Biomedicine and Genome-Scale Biology Research Program University of Helsinki Haartmaninkatu 8 Finland. H These authors contributed equally to this work. Correspondence Olli Kallioniemi. Email Published 19 September 2008 Genome Biology 2008 9 R139 doi gb-2008-9-9-rl 39 The electronic version of this article is the complete one and can be found online at http 2008 9 9 R139 Received 15 May 2008 Revised 7 August 2008 Accepted l9 September 2008 2008 Kilpinen et al licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License http licenses by which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract Our knowledge on tissue- and disease-specific functions of human genes is rather limited and highly context-specific. Here we have developed a method for the comparison of mRNA expression levels of most human genes across 9 783 .
