title: Construction and completion of flux balance models from pathway databases.
abstract: BACKGROUND
  Flux balance analysis (FBA) is a well-known technique for genome-scale modeling of metabolic flux. Typically, an FBA formulation requires the accurate specification of four sets: biochemical reactions, biomass metabolites, nutrients and secreted metabolites. The development of FBA models can be time consuming and tedious because of the difficulty in assembling completely accurate descriptions of these sets, and in identifying errors in the composition of these sets. For example, the presence of a single non-producible metabolite in the biomass will make the entire model infeasible. Other difficulties in FBA modeling are that model distributions, and predicted fluxes, can be cryptic and difficult to understand.
  
  
  RESULTS
  We present a multiple gap-filling method to accelerate the development of FBA models using a new tool, called MetaFlux, based on mixed integer linear programming (MILP). The method suggests corrections to the sets of reactions, biomass metabolites, nutrients and secretions. The method generates FBA models directly from Pathway/Genome Databases. Thus, FBA models developed in this framework are easily queried and visualized using the Pathway Tools software. Predicted fluxes are more easily comprehended by visualizing them on diagrams of individual metabolic pathways or of metabolic maps. MetaFlux can also remove redundant high-flux loops, solve FBA models once they are generated and model the effects of gene knockouts. MetaFlux has been validated through construction of FBA models for Escherichia coli and Homo sapiens.
  
  
  BACKGROUND
  Pathway Tools with MetaFlux is freely available to academic users, and for a fee to commercial users. Download from: biocyc.org/download.shtml.
  
  
  BACKGROUND
  mario.latendresse@sri.com
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Bioinformatics Research Group/Artificial Intelligence Center, SRI International, Menlo Park, CA 94025, USA. mario.latendresse@sri.com
authors.forename: Mario
authors.initials: M
authors.lastname: Latendresse
authors.forename: Markus
authors.initials: M
authors.lastname: Krummenacker
authors.forename: Miles
authors.initials: M
authors.lastname: Trupp
authors.forename: Peter D
authors.initials: PD
authors.lastname: Karp
mesh_terms: D030562:Databases, Protein; D004926:Escherichia coli / Q000378:metabolism; D006801:Humans; D053858:Metabolic Networks and Pathways; D008954:Models, Biological; D020543:Proteome / Q000032:analysis; D012984:Software
chemical_list: D020543:Proteome