Model-order reduction of biochemical reaction networks
Model-order reduction of biochemical reaction networks
复制标题
生化反应网络的模型降阶
DOI：
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发表时间：
2012
期刊：
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通讯作者：
B. Jayawardhana
中科院分区：
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作者：
Shodhan Rao;A. Schaft;K. V. Eunen;Barbara M. Bakker;B. Jayawardhana
本文提出了一种模型降阶方法，用于求解由一般酶动力学（包括质量作用和Michaelis-Menten动力学）控制的化学反应网络。模型降阶方法是基于描述化学反应网络中络合物图形结构的加权拉普拉斯矩阵的Kron降阶。我们将我们的方法应用于酵母糖酵解模型，其中的模拟结果表明，一些关键代谢产物的降阶模型的瞬态行为是在良好的协议与全阶模型。
In this paper we propose a model-order reduction method for chemical reaction networks governed by general enzyme kinetics, including the mass-action and Michaelis-Menten kinetics. The model-order reduction method is based on the Kron reduction of the weighted Laplacian matrix which describes the graph structure of complexes in the chemical reaction network. We apply our method to a yeast glycolysis model, where the simulation result shows that the transient behaviour of a number of key metabolites of the reduced-order model is in good agreement with those of the full-order model.