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Analysis of the impact degree distribution in metabolic networks using branching process approximation

Author

Listed:
  • Takemoto, Kazuhiro
  • Tamura, Takeyuki
  • Cong, Yang
  • Ching, Wai-Ki
  • Vert, Jean-Philippe
  • Akutsu, Tatsuya

Abstract

Theoretical frameworks to estimate the tolerance of metabolic networks to various failures are important to evaluate the robustness of biological complex systems in systems biology. In this paper, we focus on a measure for robustness in metabolic networks, namely, the impact degree, and propose an approximation method to predict the probability distribution of impact degrees from metabolic network structures using the theory of branching process. We demonstrate the relevance of this method by testing it on real-world metabolic networks. Although the approximation method possesses a few limitations, it may be a powerful tool for evaluating metabolic robustness.

Suggested Citation

  • Takemoto, Kazuhiro & Tamura, Takeyuki & Cong, Yang & Ching, Wai-Ki & Vert, Jean-Philippe & Akutsu, Tatsuya, 2012. "Analysis of the impact degree distribution in metabolic networks using branching process approximation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(1), pages 379-387.
    • Handle: RePEc:eee:phsmap:v:391:y:2012:i:1:p:379-387
    DOI: 10.1016/j.physa.2011.08.011
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    References listed on IDEAS

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    1. H. Jeong & B. Tombor & R. Albert & Z. N. Oltvai & A.-L. Barabási, 2000. "The large-scale organization of metabolic networks," Nature, Nature, vol. 407(6804), pages 651-654, October.
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    1. Takemoto, Kazuhiro & Tamura, Takeyuki & Akutsu, Tatsuya, 2013. "Theoretical estimation of metabolic network robustness against multiple reaction knockouts using branching process approximation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(21), pages 5525-5535.

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