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Exploiting stoichiometric redundancies for computational efficiency and network reduction

机译:利用化学计量冗余来提高计算效率和减少网络

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摘要

Analysis of metabolic networks typically begins with construction of the stoichiometry matrix, which characterizes the network topology. This matrix provides, via the balance equation, a description of the potential steady-state flow distribution. This paper begins with the observation that the balance equation depends only on the structure of linear redundancies in the network, and so can be stated in a succinct manner, leading to computational efficiencies in steady-state analysis. This alternative description of steady-state behaviour is then used to provide a novel method for network reduction, which complements existing algorithms for describing intracellular networks in terms of input-output macro-reactions (to facilitate bioprocess optimization and control). Finally, it is demonstrated that this novel reduction method can be used to address elementary mode analysis of large networks: the modes supported by a reduced network can capture the input-output modes of a metabolic module with significantly reduced computational effort.
机译:代谢网络的分析通常从化学计量矩阵的构建开始,该矩阵表征了网络拓扑。该矩阵通过平衡方程提供对潜在稳态流量分布的描述。本文首先观察到平衡方程仅取决于网络中线性冗余的结构,因此可以用简洁的方式表述,从而提高了稳态分析的计算效率。然后使用这种稳态行为的替代描述来提供一种用于网络还原的新颖方法,该方法可以补充现有的用于根据输入输出宏反应来描述细胞内网络的算法(以促进生物过程的优化和控制)。最后,证明了这种新颖的还原方法可用于解决大型网络的基本模式分析:简化网络支持的模式可以以显着减少的计算量捕获代谢模块的输入-输出模式。

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