Báo cáo y học: " Binary gene induction and protein expression in individual cells"

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: Binary gene induction and protein expression in individual cells | Theoretical Biology and Medical Modelling BioMed Central Research Open Access Binary gene induction and protein expression in individual cells Qiang Zhang 1 Melvin E Andersen1 and Rory B Conolly2 Address Division of Computational Biology CIIT Centers for Health Research Research Triangle Park NC 27709 USA and 2National Center for Computational Toxicology . Environmental Protection Agency Research Triangle Park North Carolina 27711 USA Email Qiang Zhang - qzhang@ Melvin E Andersen - mandersen@ Rory B Conolly- Corresponding author Published 05 April 2006 Received 08 February 2006 Theoretical Biology and Medical Modelling2006 3 18 doi 1742-4682-3-18 Accepted 05 April 2006 This article is available from http content 3 1 18 2006Zhang 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 Background Eukaryotic gene transcription is believed to occur in either a binary or a graded fashion. With binary induction a transcription activator TA regulates the probability with which a gene template is switched from the inactive to the active state without affecting the rate at which RNA molecules are produced from the template. With graded also called rheostat-like induction the gene template has continuously varying levels of transcriptional activity and the TA regulates the rate of RNA production. Support for each of these two mechanisms arises primarily from experimental studies measuring reporter proteins in individual cells rather than from direct measurement of induction events at the gene template. Methods and results In this paper using a computational model of stochastic gene expression we have studied the biological and experimental conditions under

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