4.7 Article

Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0

Journal

NATURE PROTOCOLS
Volume 6, Issue 9, Pages 1290-1307

Publisher

NATURE RESEARCH
DOI: 10.1038/nprot.2011.308

Keywords

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Funding

  1. National Institute of Allergy and Infectious Diseases NIH/DHHS [Y1-AI-8401-01]
  2. NIH [GM68837-05A1, DE-PS02-08ER08-01, GM057089-12, GM057089-11S1]
  3. CalIT2 Summer scholars program
  4. U.S. Department of Energy, Offices of Advanced Scientific Computing Research and the Biological and Environmental Research [DE-SC0002009]
  5. National Science Foundation Integrative Graduate Education and Research Traineeship (IGERT) [DGE-0504645]

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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) C-13 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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