CEIT and Tecnun, University of Navarra, San Sebastián 20018, Spain.
Bioinformatics. 2016 Jul 1;32(13):2001-7. doi: 10.1093/bioinformatics/btw072. Epub 2016 Feb 28.
The concept of Minimal Cut Sets (MCSs) is used in metabolic network modeling to describe minimal groups of reactions or genes whose simultaneous deletion eliminates the capability of the network to perform a specific task. Previous work showed that MCSs where closely related to Elementary Flux Modes (EFMs) in a particular dual problem, opening up the possibility to use the tools developed for computing EFMs to compute MCSs. Until recently, however, there existed no method to compute an EFM with some specific characteristic, meaning that, in the case of MCSs, the only strategy to obtain them was to enumerate them using, for example, the standard K-shortest EFMs algorithm.
In this work, we adapt the recently developed theory to compute EFMs satisfying several constraints to the calculation of MCSs involving a specific reaction knock-out. Importantly, we emphasize that not all the EFMs in the dual problem correspond to real MCSs, and propose a new formulation capable of correctly identifying the MCS wanted. Furthermore, this formulation brings interesting insights about the relationship between the primal and the dual problem of the MCS computation.
A Matlab-Cplex implementation of the proposed algorithm is available as a supplementary material
Supplementary data are available at Bioinformatics online.
最小割集 (MCS) 的概念被用于代谢网络建模,以描述同时删除这些反应或基因会导致网络无法执行特定任务的最小反应或基因组。以前的工作表明,MCS 与特定对偶问题中的基本通量模式 (EFM) 密切相关,这为使用计算 EFM 的工具来计算 MCS 开辟了可能性。然而,直到最近,还没有一种方法可以计算具有特定特征的 EFM,这意味着,在 MCS 的情况下,获得它们的唯一策略是使用例如标准 K-最短 EFM 算法对其进行枚举。
在这项工作中,我们适应了最近发展的理论,以计算满足涉及特定反应敲除的 MCS 计算的几个约束的 EFM。重要的是,我们强调并非对偶问题中的所有 EFM 都对应于真正的 MCS,并提出了一种新的公式,可以正确识别所需的 MCS。此外,该公式为 MCS 计算的原始和对偶问题之间的关系提供了有趣的见解。
所提出算法的 Matlab-Cplex 实现可作为补充材料获得。
补充数据可在 Bioinformatics 在线获得。