CEIT and TECNUN, University of Navarra, Manuel de Lardizabal 15, 20018 San Sebastian, Spain.
Genome Biol. 2011;12(5):R49. doi: 10.1186/gb-2011-12-5-r49. Epub 2011 May 27.
Graph-based methods have been widely used for the analysis of biological networks. Their application to metabolic networks has been much discussed, in particular noting that an important weakness in such methods is that reaction stoichiometry is neglected. In this study, we show that reaction stoichiometry can be incorporated into path-finding approaches via mixed-integer linear programming. This major advance at the modeling level results in improved prediction of topological and functional properties in metabolic networks.
基于图的方法已被广泛应用于生物网络的分析。这些方法在代谢网络中的应用已被广泛讨论,特别是指出此类方法的一个重要弱点是忽略了反应计量关系。在本研究中,我们展示了可以通过混合整数线性规划将反应计量关系纳入路径查找方法中。这种在建模层面上的重大改进导致了对代谢网络中拓扑和功能特性的预测得到改善。