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双向调控对基因网络噪声的影响。

Effects of bidirectional regulation on noises in gene networks.

机构信息

Center for Computational and Evolutionary Biology, Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.

出版信息

Phys Chem Chem Phys. 2010 Mar 14;12(10):2418-26. doi: 10.1039/b912111k. Epub 2010 Jan 20.

Abstract

To investigate the effects of bidirectional regulation on the noise in protein concentration, a theoretical and simple three-gene network model is considered. The basic idea behind this model is from Paulsson's proposition (J. Paulsson, Phys. Life Rev. 2005, 2, 157-175), where the synthesis and degradation of a mRNA species corresponding to a target protein are regulated directly and indirectly by a certain sigma-factor, and a random increase in the concentration of the sigma-factor should increase both the synthesis and degradation rates of the mRNA species (bidirectional regulation). Using the standard Omega-expansion technique (linear noise approximation) and Monte Carlo simulation, our main results show clearly that for the steady-state statistics the effects of the noise of the sigma-factor on the stochastic fluctuation of the target protein could partially cancel out.

摘要

为了研究双向调节对蛋白质浓度噪声的影响,考虑了一个理论上简单的三基因网络模型。该模型的基本思想来自于 Paulsson 的提议(J. Paulsson,Phys. Life Rev. 2005, 2, 157-175),其中对应于靶蛋白的 mRNA 种类的合成和降解直接和间接受到特定 sigma 因子的调节,而 sigma 因子浓度的随机增加应该会同时增加 mRNA 种类的合成和降解速率(双向调节)。使用标准的 Omega 展开技术(线性噪声逼近)和蒙特卡罗模拟,我们的主要结果清楚地表明,对于稳态统计,sigma 因子噪声对靶蛋白随机波动的影响部分可以相互抵消。

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