title: CBFA: phenotype prediction integrating metabolic models with constraints derived from experimental data.
abstract: BACKGROUND
  Flux analysis methods lie at the core of Metabolic Engineering (ME), providing methods for phenotype simulation that allow the determination of flux distributions under different conditions. Although many constraint-based modeling software tools have been developed and published, none provides a free user-friendly application that makes available the full portfolio of flux analysis methods.
  
  
  RESULTS
  This work presents Constraint-based Flux Analysis (CBFA), an open-source software application for flux analysis in metabolic models that implements several methods for phenotype prediction, allowing users to define constraints associated with measured fluxes and/or flux ratios, together with environmental conditions (e.g. media) and reaction/gene knockouts. CBFA identifies the set of applicable methods based on the constraints defined from user inputs, encompassing algebraic and constraint-based simulation methods. The integration of CBFA within the OptFlux framework for ME enables the utilization of different model formats and standards and the integration with complementary methods for phenotype simulation and visualization of results.
  
  
  CONCLUSIONS
  A general-purpose and flexible application is proposed that is independent of the origin of the constraints defined for a given simulation. The aim is to provide a simple to use software tool focused on the application of several flux prediction methods.
authors.affiliation: Centre of Biological Engineering, University of Minho, Campus de Gualtar, Braga, Portugal. rafaelcc@di.uminho.pt.|CCTC, University of Minho, Campus de Gualtar, Braga, Portugal. rafaelcc@di.uminho.pt.|SilicoLife, Lda, Rua do Canastreiro 15, Braga, Portugal. rafaelcc@di.uminho.pt.
authors.forename: Rafael
authors.initials: R
authors.lastname: Carreira
authors.affiliation: Centre of Biological Engineering, University of Minho, Campus de Gualtar, Braga, Portugal. pevangelista@silicolife.com.|SilicoLife, Lda, Rua do Canastreiro 15, Braga, Portugal. pevangelista@silicolife.com.
authors.forename: Pedro
authors.initials: P
authors.lastname: Evangelista
authors.affiliation: Centre of Biological Engineering, University of Minho, Campus de Gualtar, Braga, Portugal. pmaia@silicolife.com.|SilicoLife, Lda, Rua do Canastreiro 15, Braga, Portugal. pmaia@silicolife.com.
authors.forename: Paulo
authors.initials: P
authors.lastname: Maia
authors.affiliation: CCTC, University of Minho, Campus de Gualtar, Braga, Portugal. pvilaca@silicolife.com.|SilicoLife, Lda, Rua do Canastreiro 15, Braga, Portugal. pvilaca@silicolife.com.
authors.forename: Paulo
authors.initials: P
authors.lastname: Vilaça
authors.affiliation: E.I. DuPont De Nemours & Co., Inc, Wilmington, DE, USA. marcellinus.pont@usa.dupont.com.
authors.forename: Marcellinus
authors.initials: M
authors.lastname: Pont
authors.affiliation: E.I. DuPont De Nemours & Co., Inc, Wilmington, DE, USA. jean-francois.tomb@usa.dupont.com.
authors.forename: Jean-François
authors.initials: JF
authors.lastname: Tomb
authors.affiliation: Centre of Biological Engineering, University of Minho, Campus de Gualtar, Braga, Portugal. irocha@deb.uminho.pt.
authors.forename: Isabel
authors.initials: I
authors.lastname: Rocha
authors.affiliation: Centre of Biological Engineering, University of Minho, Campus de Gualtar, Braga, Portugal. mrocha@di.uminho.pt.
authors.forename: Miguel
authors.initials: M
authors.lastname: Rocha
mesh_terms: D003198:Computer Simulation; D060847:Metabolic Engineering / Q000379:methods*; D064688:Metabolic Flux Analysis / Q000379:methods*; D053858:Metabolic Networks and Pathways; D008954:Models, Biological; D010641:Phenotype; D012984:Software