Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/31907

TitleCBFA : phenotype prediction integrating metabolic models with constraints derived from experimental data
Author(s)Carreira, Rafael
Evangelista, Pedro
Maia, Paulo
Vilaça, Paulo
Pont, M.
Tomb, J. F.
Rocha, I.
Rocha, Miguel
KeywordsConstraint-based modeling
Metabolic Flux analysis
Metabolic engineering
Open-source software
Issue date2014
PublisherBioMed Central
JournalBMC Systems Biology
CitationCarreira, R.; Evangelista, Pedro; Maia, P.; Vilaça, P.; Pont, Marcellinus; Tomb, Jean-François; Rocha, I.; Rocha, Miguel, CBFA: phenotype prediction integrating metabolic models with constraints derived from experimental data. BMC Systems Biology, 8(123), 2014
Abstract(s)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.
TypeArticle
URIhttp://hdl.handle.net/1822/31907
DOI10.1186/s12918-014-0123-1
ISSN1752-0509
e-ISSN1752-0509
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CEB - Publicações em Revistas/Séries Internacionais / Publications in International Journals/Series

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