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Title:Decomposition of metabolic network based on the global connectivity structure of reaction graph
Authors: Hongwu Ma ; Xueming Zhao ; Yingjin Yuan ; An-Ping Zeng
Date: 2004
Publication Title:Bioinformatics
Publisher:Oxford University Press
Publication Type:Journal Article Publication Status:Published
Volume No:20(12) Page Nos:1870-1876
DOI:10.1093/bioinformatics/bth167 ISBN/ISSN:1460-2059
In this work, we use a reaction graph representation of a metabolic network for the identification of its global connectivity structure and for decomposition. A bow-tie connectivity structure similar to that previously discovered for metabolite graph is found also to exist in the reaction graph. Based on this bow-tie structure, a new decomposition method is proposed, which uses a distance definition derived from the path length between two reactions. An hierarchical classification tree is first constructed from the distance matrix among the reactions in the giant strong component of the bow-tie structure. These reactions are then grouped into different subsets based on the hierarchical tree. Reactions in the IN and OUT subsets of the bow-tie structure are subsequently placed in the corresponding subsets according to a majority rule . Compared with the decomposition methods proposed in literature, ours is based on combined properties of the global network structure and local reaction connectivity rather than, primarily, on the connection degree of metabolites. The method is applied to decompose the metabolic network of Escherichia coli. Eleven subsets are obtained. More detailed investigations of the subsets show that reactions in the same subset are really functionally related. The rational decomposition of metabolic networks, and subsequent studies of the subsets, make it more amenable to understand the inherent organization and functionality of metabolic networks at the modular level.
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Bibtex format
author = { Hongwu Ma and Xueming Zhao and Yingjin Yuan and An-Ping Zeng },
title = {Decomposition of metabolic network based on the global connectivity structure of reaction graph},
journal = {Bioinformatics},
publisher = {Oxford University Press},
year = 2004,
volume = {20(12)},
pages = {1870-1876},
doi = {10.1093/bioinformatics/bth167},
url = {},

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