Journal Article

Flux balance impact degree: a new definition of impact degree to properly treat reversible reactions in metabolic networks

Yang Zhao, Takeyuki Tamura, Tatsuya Akutsu and Jean-Philippe Vert

in Bioinformatics

Volume 29, issue 17, pages 2178-2185
Published in print September 2013 | ISSN: 1367-4803
Published online July 2013 | e-ISSN: 1460-2059 | DOI: https://dx.doi.org/10.1093/bioinformatics/btt364

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Motivation: Metabolic pathways are complex systems of chemical reactions taking place in every living cell to degrade substrates and synthesize molecules needed for life. Modeling the robustness of these networks with respect to the dysfunction of one or several reactions is important to understand the basic principles of biological network organization, and to identify new drug targets. While several approaches have been proposed for that purpose, they are computationally too intensive to analyze large networks, and do not properly handle reversible reactions.

Results: We propose a new modelthe flux balance impact degreeto model the robustness of large metabolic networks with respect to gene knock-out. We formulate the computation of the impact of one or several reaction blocking as linear programs, and propose efficient strategies to solve them. We show that the proposed method better predicts the phenotypic impact of single gene deletions on Escherichia coli than existing methods.

Availability: https://sunflower.kuicr.kyoto-u.ac.jp/∼tyoyo/fbid/index.html

Contact: takutsu@kuicr.kyoto-u.ac.jp or Jean-Philippe.Vert@mines.org

Supplementary information: Supplementary data are available at Bioinformatics online.

Journal Article.  5560 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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