Non-linear reduction for kinetic models of metabolic reaction networks
Non-linear reduction for kinetic models of metabolic reaction networks
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DOI：
10.1016/j.ymben.2003.11.003
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发表时间：
2004-04-01
影响因子：
8.4
通讯作者：
Hu, WS
中科院分区：
文献类型：
--
作者：
Gerdtzen, ZP;Daoutidis, P;Hu, WS
代谢网络的动力学模型对于预测和优化培养中细胞的瞬态行为是必不可少的。然而，这样的模型是固有的高维和僵硬的，由于大量的物种和反应所涉及的和广泛不同的数量级的动力学速率常数。在本文中，我们解决的问题，推导出非刚性，降阶非线性模型的代谢网络与快速和缓慢的反应占主导地位的动态。我们提出了一种方法，奇异摄动分析的基础上，它允许系统识别的准稳态条件的快速反应，并推导出明确的非线性模型的慢动力学独立的快速反应速率表达式。该方法已成功地应用于人体红细胞和酿酒酵母代谢的详细模型。(C)2004年爱思唯尔公司All rights reserved.
Kinetic models of metabolic networks are essential for predicting and optimizing the transient behavior of cells in culture. However, such models are inherently high dimensional and stiff due to the large number of species and reactions involved and to kinetic rate constants of widely different orders of magnitude. In this paper we address the problem of deriving non-stiff, reduced-order non-linear models of the dominant dynamics of metabolic networks with fast and slow reactions. We present a method, based on singular perturbation analysis, which allows the systematic identification of quasi-steady-state conditions for the fast reactions, and the derivation of explicit non-linear models of the slow dynamics independent of the fast reaction rate expressions. The method is successfully applied to detailed models of metabolism in human erythrocytes and Saccharomyces cerevisiae. (C) 2004 Elsevier Inc. All rights reserved.