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“School of Biological”

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Paper   IPM / Biological / 13694
School of Biological Sciences
  Title:   FCDECOMP: Decomposition of metabolic networks based on flux coupling relations
  Author(s): 
1 . A. Rezvan.
2 . S. A. Marashi.
3 . C. Eslahchi.
  Status:   Published
  Journal: Bioinformatics and Computational Biology
  No.:  5
  Vol.:  12
  Year:  2014
  Pages:   21
  Supported by:  IPM
  Abstract:
A metabolic network model provides a computational framework to study the metabolism of a cell at the system level. Due to their large sizes and complexity, rational decomposition of these networks into subsystems is a strategy to obtain better insight into the metabolic functions. Additionally, decomposing metabolic networks paves the way to use computational methods that will be otherwise very slow when run on the original genome-scale network. In the present study, we propose FCDECOMP decomposition method based on flux coupling relations (FCRs) between pairs of reaction fluxes. This approach utilizes a genetic algorithm (GA) to obtain subsystems that can be analyzed in isolation, i.e. without considering the reactions of the original network in the analysis. Therefore, we propose that our method is useful for discovering biologically meaningful modules in metabolic networks. As a case study, we show that when this method is applied to the metabolic networks of barley seeds and yeast, the modules are in good agreement with the biological compartments of these networks.

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