title: Hierarchical modularity of nested bow-ties in metabolic networks.
abstract: BACKGROUND
  The exploration of the structural topology and the organizing principles of genome-based large-scale metabolic networks is essential for studying possible relations between structure and functionality of metabolic networks. Topological analysis of graph models has often been applied to study the structural characteristics of complex metabolic networks.
  
  
  RESULTS
  In this work, metabolic networks of 75 organisms were investigated from a topological point of view. Network decomposition of three microbes (Escherichia coli, Aeropyrum pernix and Saccharomyces cerevisiae) shows that almost all of the sub-networks exhibit a highly modularized bow-tie topological pattern similar to that of the global metabolic networks. Moreover, these small bow-ties are hierarchically nested into larger ones and collectively integrated into a large metabolic network, and important features of this modularity are not observed in the random shuffled network. In addition, such a bow-tie pattern appears to be present in certain chemically isolated functional modules and spatially separated modules including carbohydrate metabolism, cytosol and mitochondrion respectively.
  
  
  CONCLUSIONS
  The highly modularized bow-tie pattern is present at different levels and scales, and in different chemical and spatial modules of metabolic networks, which is likely the result of the evolutionary process rather than a random accident. Identification and analysis of such a pattern is helpful for understanding the design principles and facilitate the modelling of metabolic networks.
authors.affiliation: School of Life Sciences & Technology, Shanghai Jiao Tong University, Shanghai 200240, China. zjane_cn@sjtu.edu.cn
authors.forename: Jing
authors.initials: J
authors.lastname: Zhao
authors.forename: Hong
authors.initials: H
authors.lastname: Yu
authors.forename: Jian-Hua
authors.initials: JH
authors.lastname: Luo
authors.forename: Zhi-Wei
authors.initials: ZW
authors.lastname: Cao
authors.forename: Yi-Xue
authors.initials: YX
authors.lastname: Li
mesh_terms: D000465:Algorithms; D002468:Cell Physiological Phenomena; D003196:Computer Graphics; D003198:Computer Simulation; D015870:Gene Expression / Q000502:physiology*; D008954:Models, Biological; D020543:Proteome / Q000378:metabolism*; D015398:Signal Transduction / Q000502:physiology*; D012984:Software; D014584:User-Computer Interface
chemical_list: D020543:Proteome