A Geometric Method for Model Reduction of Biochemical Networks with Polynomial Rate Functions
A Geometric Method for Model Reduction of Biochemical Networks with Polynomial Rate Functions
复制标题
具有多项式速率函数的生化网络模型约简的几何方法
DOI：
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发表时间：
2015
影响因子：
3.5
通讯作者：
O. Radulescu
中科院分区：
文献类型：
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作者：
S. Samal;D. Grigoriev;H. Fröhlich;A. Weber;O. Radulescu
生物化学网络的模型简化依赖于慢变量和快变量的知识。我们提出了一种基于牛顿多面体的几何方法，用多项式速率函数来识别生化网络的慢变量。该方法的要点是热带平衡的概念，它提供了慢不变流形的近似描述。与现有的数值算法（如固有的低维流形方法）相比，我们的方法是象征性的，并且利用数量级而不是模型参数的精确值。将这种方法应用到大量生化网络模型中，支持了这样一种观点，即尽管存在大量的分子调节因子，但细胞生理学最小模型中的动态变量数量可能很小。
Model reduction of biochemical networks relies on the knowledge of slow and fast variables. We provide a geometric method, based on the Newton polytope, to identify slow variables of a biochemical network with polynomial rate functions. The gist of the method is the notion of tropical equilibration that provides approximate descriptions of slow invariant manifolds. Compared to extant numerical algorithms such as the intrinsic low-dimensional manifold method, our approach is symbolic and utilizes orders of magnitude instead of precise values of the model parameters. Application of this method to a large collection of biochemical network models supports the idea that the number of dynamical variables in minimal models of cell physiology can be small, in spite of the large number of molecular regulatory actors.
DOI：
10.1073/pnas.88.16.7328
发表时间：
1991-08-01
影响因子：
11.1
作者：
TYSON, JJ
通讯作者：
TYSON, JJ