1Bioinformatics Center, Kyoto University, Kyoto, Japan, 2Centre for Computational Biology, Mines ParisTech, 35 rue Saint-Honoré, 77305 Fontainebleau, France and 3Institut Curie and 4INSERM U900, Paris, France
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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 model—the flux balance impact degree—to 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.htmlContact:email@example.com or Jean-Philippe.Vert@mines.orgSupplementary information:Supplementary data are available at Bioinformatics online.