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

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

416 Scopus Citations
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Author(s)

  • 55 authors, including
  • Laurent Heirendt
  • Ding Ma
  • Ronan M. T. Fleming

Detail(s)

Original languageEnglish
Pages (from-to)639-702
Journal / PublicationNature Protocols
Volume14
Issue number3
Online published20 Feb 2019
Publication statusPublished - Mar 2019
Externally publishedYes

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.

Citation Format(s)

Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v3. 0. / 55 authors, including; Heirendt, Laurent; Ma, Ding et al.

In: Nature Protocols, Vol. 14, No. 3, 03.2019, p. 639-702.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review