Ehrentreich F, Schomburg D
Institut für Biochemie, Universität zu Köln, Zülpicher Strasse 47, 50674, Cologne, Germany.
Funct Integr Genomics. 2003 Dec;3(4):189-96. doi: 10.1007/s10142-003-0091-9. Epub 2003 Oct 16.
The dynamic generation and qualitative analysis of metabolic networks relying on continuously growing qualified metabolic data by a joint database/graph theoretical approach is described. The procedure is applied to analyze the connectivity of a metabolic network after enzyme removal and to subsequently perform shortest path analyses. The focus lies on the analysis of the connectivity of the metabolic network depending on model assumptions. Here we analyze the influence of the number of strongly connected components on the assignment of reversibility or irreversibility of the biochemical reactions.
描述了一种通过联合数据库/图论方法,依靠持续增长的合格代谢数据动态生成和定性分析代谢网络的方法。该程序用于分析去除酶后代谢网络的连通性,并随后进行最短路径分析。重点在于根据模型假设分析代谢网络的连通性。在此,我们分析强连通分量的数量对生化反应可逆性或不可逆性分配的影响。