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Creation and analysis of biochemical constraint-based models: the COBRA Toolbox v3.0

Creation and analysis of biochemical constraint-based models: the COBRA Toolbox v3.0
Creation and analysis of biochemical constraint-based models: the COBRA Toolbox v3.0
Constraint-based reconstruction and analysis (COBRA) provides a molecular mechanistic framework for integrative analysis of experimental molecular systems biology data and quantitative prediction of physicochemically and biochemically feasible phenotypic states. The COBRA Toolbox is a comprehensive desktop software suite of interoperable COBRA methods. It has found widespread application in biology, biomedicine, and biotechnology because its functions can be flexibly combined to implement tailored COBRA protocols for any biochemical network. This protocol is an update to the COBRA Toolbox v.1.0 and v.2.0. Version 3.0 includes new methods for quality-controlled reconstruction, modeling, topological analysis, strain and experimental design, and network visualization, as well as network integration of chemoinformatic, metabolomic, transcriptomic, proteomic, and thermochemical data. New multi-lingual code integration also enables an expansion in COBRA application scope via high-precision, high-performance, and nonlinear numerical optimization solvers for multi-scale, multi-cellular, and reaction kinetic modeling, respectively. This protocol provides an overview of all these new features and can be adapted to generate and analyze constraint-based models in a wide variety of scenarios. The COBRA Toolbox v.3.0 provides an unparalleled depth of COBRA methods.
1754-2189
639-702
Phan, Vuong Tu
52577e5d-ebe9-4a43-b5e7-68aa06cfdcaf
Heirendt, Laurent
451ec43c-b74c-4d15-9cdd-ca05689f0341
Arreckx, Sylvain
e08ca23e-3c23-45c4-8053-e5d3a06a0dec
et al.
Phan, Vuong Tu
52577e5d-ebe9-4a43-b5e7-68aa06cfdcaf
Heirendt, Laurent
451ec43c-b74c-4d15-9cdd-ca05689f0341
Arreckx, Sylvain
e08ca23e-3c23-45c4-8053-e5d3a06a0dec

Heirendt, Laurent and Arreckx, Sylvain , et al. (2019) Creation and analysis of biochemical constraint-based models: the COBRA Toolbox v3.0. Nature Protocols, 14, 639-702. (doi:10.1038/s41596-018-0098-2).

Record type: Article

Abstract

Constraint-based reconstruction and analysis (COBRA) provides a molecular mechanistic framework for integrative analysis of experimental molecular systems biology data and quantitative prediction of physicochemically and biochemically feasible phenotypic states. The COBRA Toolbox is a comprehensive desktop software suite of interoperable COBRA methods. It has found widespread application in biology, biomedicine, and biotechnology because its functions can be flexibly combined to implement tailored COBRA protocols for any biochemical network. This protocol is an update to the COBRA Toolbox v.1.0 and v.2.0. Version 3.0 includes new methods for quality-controlled reconstruction, modeling, topological analysis, strain and experimental design, and network visualization, as well as network integration of chemoinformatic, metabolomic, transcriptomic, proteomic, and thermochemical data. New multi-lingual code integration also enables an expansion in COBRA application scope via high-precision, high-performance, and nonlinear numerical optimization solvers for multi-scale, multi-cellular, and reaction kinetic modeling, respectively. This protocol provides an overview of all these new features and can be adapted to generate and analyze constraint-based models in a wide variety of scenarios. The COBRA Toolbox v.3.0 provides an unparalleled depth of COBRA methods.

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Accepted/In Press date: 1 April 2016
e-pub ahead of print date: 20 February 2019
Published date: 14 March 2019

Identifiers

Local EPrints ID: 434648
URI: http://eprints.soton.ac.uk/id/eprint/434648
ISSN: 1754-2189
PURE UUID: 7b4c9dc2-8386-4836-b67a-2db12ce4d4a0
ORCID for Vuong Tu Phan: ORCID iD orcid.org/0000-0002-1474-994X

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Date deposited: 04 Oct 2019 16:30
Last modified: 16 Mar 2024 04:42

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Contributors

Author: Vuong Tu Phan ORCID iD
Author: Laurent Heirendt
Author: Sylvain Arreckx
Corporate Author: et al.

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