Constructing the energy landscape for genetic switching system driven by intrinsic noise.

Constructing the energy landscape for genetic switching system driven by intrinsic noise.
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构建本征噪声驱动的基因转换系统的能量格局

DOI:
10.1371/journal.pone.0088167
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发表时间:
2014
期刊:
影响因子:
3.7
通讯作者:
Li T
Li T
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Lv C;Li X;Li F;Li T

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噪声驱动的基因开关是基因调控网络中的一个基本细胞过程。描述这种开关及其波动特性的量化是计算生物学中的一个关键问题。以自调控二聚体模型为例,设计了一种定量研究基因调控系统受内在噪声干扰时亚稳态的一般方法。基于大偏差理论,我们开发了新的分析技术来描述和计算开和关状态之间的最佳过渡路径。我们还构建了二聚体模型的全局准势能景观。从所获得的准势,我们可以提取定量的结果,如mRNA,蛋白质和二聚体的平稳分布,表达状态的噪声强度,以及从任一稳定状态开始的平均切换时间。在最后阶段,我们将此程序应用于转录级联模型。我们的研究结果表明,准势能景观和所提出的方法是一般的理解在其他生物系统的亚稳态与固有噪声。
Genetic switching driven by noise is a fundamental cellular process in genetic regulatory networks. Quantitatively characterizing this switching and its fluctuation properties is a key problem in computational biology. With an autoregulatory dimer model as a specific example, we design a general methodology to quantitatively understand the metastability of gene regulatory system perturbed by intrinsic noise. Based on the large deviation theory, we develop new analytical techniques to describe and calculate the optimal transition paths between the on and off states. We also construct the global quasi-potential energy landscape for the dimer model. From the obtained quasi-potential, we can extract quantitative results such as the stationary distributions of mRNA, protein and dimer, the noise strength of the expression state, and the mean switching time starting from either stable state. In the final stage, we apply this procedure to a transcriptional cascades model. Our results suggest that the quasi-potential energy landscape and the proposed methodology are general to understand the metastability in other biological systems with intrinsic noise.
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