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CBFA: phenotype prediction integrating metabolic models with constraints derived from experimental data.

Carreira R, Evangelista P, Maia P, Vilaça P, Pont M, Tomb JF, Rocha I, Rocha M - BMC Syst Biol (2014)

Bottom Line: 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.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.The aim is to provide a simple to use software tool focused on the application of several flux prediction methods.

View Article: PubMed Central - PubMed

Affiliation: Centre of Biological Engineering, University of Minho, Campus de Gualtar, Braga, Portugal. rafaelcc@di.uminho.pt.

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.

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Overview of the application: on the left side, the inputs are represented; the centre box contains the different functional blocks of the application: the types of constraints, the determination of the system type and the supported methods; the right boxes represent the outputs of the methods.
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Fig1: Overview of the application: on the left side, the inputs are represented; the centre box contains the different functional blocks of the application: the types of constraints, the determination of the system type and the supported methods; the right boxes represent the outputs of the methods.

Mentions: An overview of the overall workflow implemented in CBFA is provided in Figure 1, where the different inputs, the generated constraints, the system types, the supported methods and their outputs are shown. In this section, the main steps and alternatives offered by the pipeline to execute the flux analysis methods are briefly explained. The detailed description of the implemented methods and complete mathematical formulations are provided as supplementary material (Additional file 2), also available on the project’s website. Additionally, a Beginner’s tutorial with illustrations for all the steps needed to perform the software tasks is available to help first-time users (Additional file 3 and online documentation on the site).Figure 1


CBFA: phenotype prediction integrating metabolic models with constraints derived from experimental data.

Carreira R, Evangelista P, Maia P, Vilaça P, Pont M, Tomb JF, Rocha I, Rocha M - BMC Syst Biol (2014)

Overview of the application: on the left side, the inputs are represented; the centre box contains the different functional blocks of the application: the types of constraints, the determination of the system type and the supported methods; the right boxes represent the outputs of the methods.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4263207&req=5

Fig1: Overview of the application: on the left side, the inputs are represented; the centre box contains the different functional blocks of the application: the types of constraints, the determination of the system type and the supported methods; the right boxes represent the outputs of the methods.
Mentions: An overview of the overall workflow implemented in CBFA is provided in Figure 1, where the different inputs, the generated constraints, the system types, the supported methods and their outputs are shown. In this section, the main steps and alternatives offered by the pipeline to execute the flux analysis methods are briefly explained. The detailed description of the implemented methods and complete mathematical formulations are provided as supplementary material (Additional file 2), also available on the project’s website. Additionally, a Beginner’s tutorial with illustrations for all the steps needed to perform the software tasks is available to help first-time users (Additional file 3 and online documentation on the site).Figure 1

Bottom Line: 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.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.The aim is to provide a simple to use software tool focused on the application of several flux prediction methods.

View Article: PubMed Central - PubMed

Affiliation: Centre of Biological Engineering, University of Minho, Campus de Gualtar, Braga, Portugal. rafaelcc@di.uminho.pt.

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.

Show MeSH