title: Flux balance impact degree: a new definition of impact degree to properly treat reversible reactions in metabolic networks.
abstract: BACKGROUND
  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.
  
  
  BACKGROUND
  https://sunflower.kuicr.kyoto-u.ac.jp/∼tyoyo/fbid/index.html
authors.affiliation: Bioinformatics Center, Kyoto University, Kyoto, Japan, Centre for Computational Biology, Mines ParisTech, 35 rue Saint-Honoré, Fontainebleau, France.
authors.forename: Yang
authors.initials: Y
authors.lastname: Zhao
authors.forename: Takeyuki
authors.initials: T
authors.lastname: Tamura
authors.forename: Tatsuya
authors.initials: T
authors.lastname: Akutsu
authors.forename: Jean-Philippe
authors.initials: JP
authors.lastname: Vert
mesh_terms: D000465:Algorithms; D004926:Escherichia coli / Q000235:genetics / Q000378:metabolism; D017353:Gene Deletion; D053858:Metabolic Networks and Pathways / Q000235:genetics*; D008954:Models, Biological; D010641:Phenotype