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MCS2: minimal coordinated supports for fast enumeration of minimal cut sets in metabolic networks

机译:MCS2:最小的协调支持可快速枚举代谢网络中的最小割集

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摘要

MotivationConstraint-based modeling of metabolic networks helps researchers gain insight into the metabolic processes of many organisms, both prokaryotic and eukaryotic. Minimal cut sets (MCSs) are minimal sets of reactions whose inhibition blocks a target reaction in a metabolic network. Most approaches for finding the MCSs in constrained-based models require, either as an intermediate step or as a byproduct of the calculation, the computation of the set of elementary flux modes (EFMs), a convex basis for the valid flux vectors in the network. Recently, Ballerstein et al. proposed a method for computing the MCSs of a network without first computing its EFMs, by creating a dual network whose EFMs are a superset of the MCSs of the original network. However, their dual network is always larger than the original network and depends on the target reaction. Here we propose the construction of a different dual network, which is typically smaller than the original network and is independent of the target reaction, for the same purpose. We prove the correctness of our approach, minimal coordinated support (MCS2), and describe how it can be modified to compute the few smallest MCSs for a given target reaction.
机译:基于动力的代谢网络建模有助于研究人员深入了解许多生物的代谢过程,包括原核和真核生物。最小割集(MCS)是反应的最小集,其抑制作用会阻止代谢网络中的目标反应。在基于约束的模型中找到MCS的大多数方法,作为中间步骤或作为计算的副产品,都需要计算基本通量模式(EFM)集,这是网络中有效通量矢量的凸基础。 。最近,Ballerstein等。通过创建双网络(其EFM是原始网络的MCS的超集),提出了一种无需先计算其EFM即可计算网络MCS的方法。但是,它们的双重网络始终大于原始网络,并取决于目标反应。在此,出于相同的目的,我们提出了一个不同的双重网络的构造,该双重网络通常小于原始网络并且独立于目标反应。我们证明了我们的方法的正确性,最小的协同支持(MCS 2 ),并描述了如何修改该方法以计算给定目标反应的最小最小MCS。

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