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Adiabatic coarse-graining and simulations of stochastic biochemical networks

机译:绝热粗粒度和随机生化网络模拟

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摘要

We propose a universal approach for analysis and fast simulations of stiff stochastic biochemical networks, which rests on elimination of fast chemical species without a loss of information about mesoscopic, non-Poissonian fluctuations of the slow ones. Our approach is similar to the Born-Oppenheimer approximation in quantum mechanics and follows from the stochastic path integral representation of the cumulant generating function of reaction events. In applications with a small number of chemical reactions, it produces analytical expressions for cumulants of chemical fluxes between the slow variables. This allows for a low-dimensional, interpretable representation and can be used for high-accuracy, low-complexity coarse-grained numerical simulations. As an example, we derive the coarse-grained description for a chain of biochemical reactions and show that the coarse-grained and the microscopic simulations agree, but the former is 3 orders of magnitude faster.
机译:我们提出了一种用于分析和快速模拟刚性随机生化网络的通用方法,该方法基于消除快速化学物种而不会丢失有关慢速化学物种的介观,非泊松波动的信息。我们的方法类似于量子力学中的Born-Oppenheimer逼近,并且遵循反应事件累积量生成函数的随机路径积分表示。在具有少量化学反应的应用中,它会生成慢变量之间化学通量累积量的解析表达式。这样可以实现低维,可解释的表示,并且可以用于高精度,低复杂度的粗粒度数值模拟。例如,我们导出了一系列生化反应的粗粒度描述,并表明粗粒度和微观模拟相吻合,但前者的速度要快3个数量级。

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    Center for Nonlinear Studies, and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, NM 87545 Computer, Computational, and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, NM 87545;

    Computer, Computational, and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, NM 87545;

    Center for Nonlinear Studies, and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, NM 87545 Computer, Computational, and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, NM 87545;

  • 收录信息 美国《科学引文索引》(SCI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
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  • 正文语种 eng
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