Reference : Quantitative prediction of cellular metabolism with constraint-based models: the COBR...
Scientific journals : Article
Life sciences : Multidisciplinary, general & others
Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0.
Schellenberger, Jan [> >]
Que, Richard [> >]
Fleming, Ronan MT mailto [> >]
Thiele, Ines mailto [> >]
Orth, Jeffrey D. [> >]
Feist, Adam M. [> >]
Zielinski, Daniel C. [> >]
Bordbar, Aarash [> >]
Lewis, Nathan E. [> >]
Rahmanian, Sorena [> >]
Kang, Joseph [> >]
Hyduke, Daniel R. [> >]
Palsson, Bernhard O. [> >]
Nature Protocols
[en] Algorithms ; Computational Biology/methods ; Metabolic Networks and Pathways ; Software
[en] Over the past decade, a growing community of researchers has emerged around the use of constraint-based reconstruction and analysis (COBRA) methods to simulate, analyze and predict a variety of metabolic phenotypes using genome-scale models. The COBRA Toolbox, a MATLAB package for implementing COBRA methods, was presented earlier. Here we present a substantial update of this in silico toolbox. Version 2.0 of the COBRA Toolbox expands the scope of computations by including in silico analysis methods developed since its original release. New functions include (i) network gap filling, (ii) (13)C analysis, (iii) metabolic engineering, (iv) omics-guided analysis and (v) visualization. As with the first version, the COBRA Toolbox reads and writes systems biology markup language-formatted models. In version 2.0, we improved performance, usability and the level of documentation. A suite of test scripts can now be used to learn the core functionality of the toolbox and validate results. This toolbox lowers the barrier of entry to use powerful COBRA methods.

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