Departamento de Matemáticas, Centro de Investigación y de Estudios Avanzados del IPN, Av Instituto Politécnico Nacional 2508, 07360 México DF, Mexico.
J Theor Biol. 2010 May 21;264(2):377-85. doi: 10.1016/j.jtbi.2010.02.004. Epub 2010 Feb 6.
In this work we introduce a novel approach to study biochemical noise. It comprises a simplification of the master equation of complex reaction schemes (via an adiabatic approximation) and the numerical solution of the reduced master equation. The accuracy of this procedure is tested by comparing its results with analytic solutions (when available) and with Gillespie stochastic simulations. We further employ our approach to study the stochastic expression of a simple gene network, which is subject to negative feedback regulation at the transcriptional level. Special attention is paid to the influence of negative feedback on the amplitude of intrinsic noise, as well as on the relaxation rate of the system probability distribution function to the steady solution. Our results suggest the existence of an optimal feedback strength that maximizes this relaxation rate.
在这项工作中，我们引入了一种研究生化噪声的新方法。它包括简化复杂反应方案的主方程（通过绝热近似）和简化主方程的数值解。通过将结果与解析解（如果可用）和 Gillespie 随机模拟进行比较，测试了该方法的准确性。我们进一步将我们的方法应用于研究简单基因网络的随机表达，该网络受到转录水平的负反馈调节。特别关注负反馈对固有噪声幅度以及系统概率分布函数到稳态解的弛豫速率的影响。我们的结果表明，存在一个最佳的反馈强度，可以最大化这种弛豫速率。
