Literature DB >> 23030980

Metabolic network modularity arising from simple growth processes.

Kazuhiro Takemoto1.   

Abstract

Metabolic networks consist of linked functional components, or modules. The mechanism underlying metabolic network modularity is of great interest not only to researchers of basic science but also to those in fields of engineering. Previous studies have suggested a theoretical model, which proposes that a change in the evolutionary goal (system-specific purpose) increases network modularity, and this hypothesis was supported by statistical data analysis. Nevertheless, further investigation has uncovered additional possibilities that might explain the origin of network modularity. In this work we propose an evolving network model without tuning parameters to describe metabolic networks. We demonstrate, quantitatively, that metabolic network modularity can arise from simple growth processes, independent of the change in the evolutionary goal. Our model is applicable to a wide range of organisms and appears to suggest that metabolic network modularity can be more simply determined than previously thought. Nonetheless, our proposition does not serve to contradict the previous model; it strives to provide an insight from a different angle in the ongoing efforts to understand metabolic evolution, with the hope of eventually achieving the synthetic engineering of metabolic networks.

Mesh:

Substances:

Year:  2012        PMID: 23030980     DOI: 10.1103/PhysRevE.86.036107

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  4 in total

1.  Human Impacts and Climate Change Influence Nestedness and Modularity in Food-Web and Mutualistic Networks.

Authors:  Kazuhiro Takemoto; Kosuke Kajihara
Journal:  PLoS One       Date:  2016-06-20       Impact factor: 3.240

2.  Does habitat variability really promote metabolic network modularity?

Authors:  Kazuhiro Takemoto
Journal:  PLoS One       Date:  2013-04-12       Impact factor: 3.240

3.  Mutation rules and the evolution of sparseness and modularity in biological systems.

Authors:  Tamar Friedlander; Avraham E Mayo; Tsvi Tlusty; Uri Alon
Journal:  PLoS One       Date:  2013-08-06       Impact factor: 3.240

Review 4.  Topology of molecular interaction networks.

Authors:  Wynand Winterbach; Piet Van Mieghem; Marcel Reinders; Huijuan Wang; Dick de Ridder
Journal:  BMC Syst Biol       Date:  2013-09-16
  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.