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Báo cáo y học: "inferring steady state single-cell gene expression distributions from analysis of mesoscopic samples"

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: inferring steady state single-cell gene expression distributions from analysis of mesoscopic samples. | Research Open Access Inferring steady state single-cell gene expression distributions from analysis of mesoscopic samples Jessica C Mar Renee Rubio and John Quackenbush Addresses Department of Biostatistics Harvard School of Public Health Huntington Avenue Boston Massachusetts 02115 USA. Department of Biostatistics and Computational Biology Dana-Farber Cancer Institute Binney St Boston Massachusetts 02115 USA. Department of Cancer Biology Dana-Farber Cancer Institute Binney St Boston Massachusetts 02115 USA. Correspondence John Quackenbush. Email johnq@jimmy.harvard.edu Published 14 December 2006 Genome Biology 2006 7 R119 doi l0.ll86 gb-2006-7- 12-r119 The electronic version of this article is the complete one and can be found online at http genomebiology.com 2006 7 12 R1 19 Received 4 August 2006 Revised 8 November 2006 Accepted 14 December 2006 2006 Mar 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 A great deal of interest has been generated by systems biology approaches that attempt to develop quantitative predictive models of cellular processes. However the starting point for all cellular gene expression the transcription of RNA has not been described and measured in a population of living cells. Results Here we present a simple model for transcript levels based on Poisson statistics and provide supporting experimental evidence for genes known to be expressed at high moderate and low levels. Conclusion Although the model describes a microscopic process occurring at the level of an individual cell the supporting data we provide uses a small number of cells where the echoes of the underlying stochastic processes can be seen. Not only do these data confirm our model but this general strategy .