Packages


  • The COBRA Toolbox

    The COnstraint-Based Reconstruction and Analysis (COBRA) Toolbox written in MATLAB.



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  • COBRApy

    COBRApy is a package for constraint-based modeling of biological networks written in Python.



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  • COBRA.jl

    High-level, high-performance, constraint-based reconstruction and analysis in Julia.



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  • COBRA.binary

    Linux, Windows and Mac binaries maintained by the constraint-based reconstruction and analysis (COBRA) community.



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  • MASS Toolbox

    The Mass-Action Stoichiometric Simulation (MASS) toolbox enables the construction and analysis of kinetic and constraint-based models.



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  • MATLAB.devTools

    Make a contribution to any git repository from MATLAB. The devTools are cross-platform, for novice and advanced users. Contribute the smart way!



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What is COBRA?

The COnstraints Based Reconstruction and Analysis (COBRA) approach to systems biology accepts the fact that we do not possess sufficiently detailed parameter data to precisely model, in the biophysical sense, an organism at genome-scale.


Increasingly, omics data has been used to define the set of feasible states for a biological network in a given condition based on current knowledge. These constraints include compartmentalization, mass conservation, molecular crowding, and thermodynamic directionality. More recently, transcriptome data have been used to reduce the size of the set of computed feasible states.


Although COBRA methods may not provide a unique solution, they provide a reduced set of solutions that may be used to guide biological hypothesis development. Given its success, COBRA has attracted attention from many investigators and has developed rapidly in recent years based on contributions from a growing number of laboratories – COBRA methods have been used in hundreds of studies to deal with the complex relationships and high dimensionality of the next generation of COBRA models.

Representation of a stoichiometric matrix
[2785 x 3820] - Human Model Recon 1.

History

The openCOBRA project has arisen to provide researchers with easy access to core COBRA methodologies, and to provide a repository for community contributed modules that build off of these core COBRA features. The openCOBRA project was initiated with tools for MATLAB but has now grown to include Python and Julia-based modules for dealing with the complex relationships of the next generation of COBRA models.


The openCOBRA project is currently lead by Ronan Fleming from the University of Luxembourg, Nikolaus Sonnenschein from the Technical University of Denmark, and Nathan Lewis from UCSD.

Evolution of the repository of
The COBRA Toolbox (2016-2017).

How to cite an openCOBRA package?

The COBRA Toolbox

Schellenberger J, Que R, Fleming RMT, Thiele I, Orth JD, Feist AM, Zielinski DC, Bordbar A, Lewis NE, Rahmanian S, Kang J, Hyduke DR, Palsson BØ. 2011, Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0. Nature Protocols 6 : 1290-1307.


COBRApy

Ebrahim A, Lerman JA, Palsson BO, Hyduke DR. 2013, COBRApy: COnstraints-Based Reconstruction and Analysis for Python. BMC Syst Bio 7 : 74.


COBRA.jl

Heirendt L, Thiele I. 2016, Fleming RMT, DistributedFBA.jl: High-level, high-performance flux balance analysis in Julia, Bioinformatics 2017 btw838. doi - 10.1093/bioinformatics/btw838


MASS Toolbox

Neema Jamshidi, Bernhard Ø. Palsson Mass Action Stoichiometric Simulation Models - Incorporating Kinetics and Regulation into Stoichiometric Models, Biophysical Journal , Volume 98 , Issue 2 , 175 - 185.


Who is working on the openCOBRA project?

In partnership with developers around the world: