一种针对代谢网络多平衡态性质的强连通分解方法  

A STRONG CONNECTIVITY DECOMPOSITION METHOD FOR ANALYZING THE MULTI-EQUILIBRIUM PROPERTY OF GENERAL METABOLIC NETWORKS

作　　者：毕文健[1] 郭金[1] 赵延龙[1] 张纪峰[1] 

机构地区：[1]中国科学院数学与系统科学研究院系统科学研究所系统控制重点实验室,北京100190

出　　处：《系统科学与数学》2012年第6期653-665,共13页Journal of Systems Science and Mathematical Sciences

基　　金：国家自然科学基金(61134013;11171333);中国科学院青年促进会基金(4106960)资助课题

摘　　要：针对反应速率满足一定条件的代谢网络,提出了一种强连通分解方法对网络进行分解,通过研究分解后的子网络来分析整体网络的多平衡态性质.基于代谢网络的拓扑结构,构造了其对应的代谢反应图和相互作用图,引入了紧缩运算的定义,构造了强连通分解算法;给出了该算法的计算复杂度,证明了分解的唯一性以及分解后子网络的强连通性,阐明了子网络与整体网络在多平衡态性质意义下的关系,举例说明了强连通算法和所得主要结果的有效性.For general metabolic networks whose reaction rates satisfy some conditions, a strong connectivity decomposition （SCD） method is proposed, which can not only divide the whole network into a set of sub-networks but also keep the strong connectivity of the network. This makes it possible to understand the multi-equilibrium property of the whole network by analyzing the sub-networks. The SCD method is based on only the topological structure of the network. To get an SCD for a given metabolic network, the concepts of metabolic reaction graph, interaction graph and contraction operation are introduced. It is shown that for a given metabolic network, the SCD is unique, all the sub-networks are strongly connected, and the computational complexity of the decomposition is polynomial. The relationship between the whole network and sub-networks is given in the sense of multi-equilibrium properties. Examples are given to demonstrate the effectiveness of the algorithms and the main results.

关 键 词：代谢网络 强连通分解算法 相互作用图 多平衡态性质 紧缩运算. 

分 类 号：O157.5[理学—数学] Q591[理学—基础数学]