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Stochastic lumping analysis for linear kinetics and its application to the fluctuation relations between hierarchical kinetic networks

机译:线性动力学随机集总分析及其在层次动力学网络波动关系中的应用

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摘要

Conventional studies of biomolecular behaviors rely largely on the construction of kinetic schemes. Since the selection of these networks is not unique, a concern is raised whether and under which conditions hierarchical schemes can reveal the same experimentally measured fluctuating behaviors and unique fluctuation related physical properties. To clarify these questions, we introduce stochasticity into the traditional lumping analysis, generalize it from rate equations to chemical master equations and stochastic differential equations, and extract the fluctuation relations between kinetically and thermodynamically equivalent networks under intrinsic and extrinsic noises. The results provide a theoretical basis for the legitimate use of low-dimensional models in the studies of macromolecular fluctuations and, more generally, for exploring stochastic features in different levels of contracted networks in chemical and biological kinetic systems. (C) 2015 AIP Publishing LLC.
机译:生物分子行为的常规研究主要依靠动力学方案的构建。由于这些网络的选择不是唯一的,因此引起关注的是,分层方案是否以及在何种条件下可以揭示相同的实验测量波动行为以及与波动相关的独特物理特性。为了澄清这些问题,我们将随机性引入传统的集总分析中,将其从速率方程式扩展到化学主方程式和随机微分方程式,并提取出固有和非固有噪声下动力学和热力学等效网络之间的波动关系。该结果为在大分子波动研究中合理使用低维模型提供了理论基础,并且更广泛地为在化学和生物动力学系统中不同水平的收缩网络探索随机特征提供了理论基础。 (C)2015 AIP Publishing LLC。

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