Grand canonical Markov model: A stochastic theory for open nonequilibrium biochemical networks
Grand canonical Markov model: A stochastic theory for open nonequilibrium biochemical networks
复制标题
DOI：
10.1063/1.2165193
复制
发表时间：
2006-01-28
影响因子：
4.4
通讯作者：
Qian, H
中科院分区：
文献类型：
--
作者：
Heuett, WJ;Qian, H
在本文中，我们提出了一个随机模型的可逆生化反应网络，被驱动通过一个开放的边界，使系统与周围环境的显式物质交换的结果。随机模型基于主方程方法，与统计力学的巨正则系综密切相关。我们表明，它是可能的分析计算的随机变量的联合概率函数描述的分子在系统的每个状态的一般线性网络。反应化学势和电导的定义遵循该模型的固有特性，提供了系统中能量耗散的描述。我们还能够提出新的方法，实验确定反应通量和生化亲和力在非平衡稳态以及整体网络连接。(c)2006年，美国物理学会。
In this paper we present the results of a stochastic model of reversible biochemical reaction networks that are being driven through an open boundary, such that the system is interacting with its surrounding environment with explicit material exchange. The stochastic model is based on the master equation approach and is intimately related to the grand canonical ensemble of statistical mechanics. We show that it is possible to analytically calculate the joint probability function of the random variables describing the number of molecules in each state of the system for general linear networks. Definitions of reaction chemical potentials and conductances follow from inherent properties of this model, providing a description of energy dissipation in the system. We are also able to suggest novel methods for experimentally determining reaction fluxes and biochemical affinities at nonequilibrium steady state as well as the overall network connectivity. (c) 2006 American Institute of Physics.