Analysis of the impact degree distribution in metabolic networks using branching process approximation |
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| Authors: | Kazuhiro Takemoto Takeyuki Tamura Yang Cong Wai-Ki Ching Jean-Philippe Vert Tatsuya Akutsu |
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| Affiliation: | 1. PRESTO, Japan Science and Technology Agency, Kawaguchi, Saitama 332-0012, Japan;2. Department of Biophysics and Biochemistry, University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113-0033, Japan;3. Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, 611-0011, Japan;4. Department of Mathematics, The University of Hong Kong, Pokfulam Road, Hong Kong;5. Centre for Computational Biology, Mines ParisTech, 35 rue Saint-Honoré, 77305 Fontainebleau cedex, France;6. Institut Curie, 75248 Paris, France;7. INSERM, U900, 75248 Paris, France |
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| 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. |
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