This is a protocol preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Method Article
Daniel Hyduke
Center for Systems Biology for Enteropathogens
Corresponding Author
License:
This work is licensed under a CC BY-NC 3.0 License. Read Full License
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 significant 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: (1) network gap filling, (2) 13C analysis, (3) metabolic engineering, (4) omics-guided analysis, and (5) 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.
Keywords
constraint based modeling, network reconstruction, metabolism, systems biology, metabolic engineering
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Bernhard Ø. Palsson serves on the scientific advisory board of Genomatica, Inc.
This is a list of supplementary files associated with this preprint. Click to download.
- supplement0.pdf
Supplementary Material All Supplementary Material (S1-S5)
- supplement0.pdf
Table 2. Troubleshooting Table
- supplement0.pdf
Table 1. Features of the COBRA Toolbox 1.0 and 2.0
- supplement0.pdf
Table 3. growthExpMatch gap filling solutions
- supplement0.pdf
Table 4. Expected results from OptKnock and GDLS optimizations for lactate, succinate and pyruvate production growing on glucose
Loading...
Version History
CURRENT STATUS: Posted
Version 1
Posted 11 May, 2011
Community comments: 4
Metrics
Comments: 0
HTML Views: ...
Associated Publications
Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox
by Scott A Becker, Adam M Feist, Monica L Mo, +3
Nature Protocols (11 May, 2011)
Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0
by Jan Schellenberger, Richard Que, Ronan M T Fleming, +10
Nature Protocols (15 September, 2011)
Method Article
Daniel Hyduke
Center for Systems Biology for Enteropathogens
Corresponding Author
Version History
CURRENT STATUS: Posted
Version 1
Posted 11 May, 2011
Community comments: 4
Metrics
Comments: 0
HTML Views: ...
License:
This work is licensed under a CC BY-NC 3.0 License. Read Full License
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 significant 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: (1) network gap filling, (2) 13C analysis, (3) metabolic engineering, (4) omics-guided analysis, and (5) 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.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Loading...
Associated Publications
Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox
by Scott A Becker, Adam M Feist, Monica L Mo, +3
Nature Protocols (11 May, 2011)
Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0
by Jan Schellenberger, Richard Que, Ronan M T Fleming, +10
Nature Protocols (15 September, 2011)