Maintained by Niko Sonnenschein at the Technical University of Denmark.
- 2015.03.04: cobrapy 0.3.2 Released
- 2014.06.06: PathwayPioneer visual reconstruction beta available
- 2014.01.13: modelBorgifier Published.
- 2013.10.01: E. coli ME-Model in Action
- 2013.08.23: GIM3E Published
- 2013.08.17: Yeast M-Model 6.0 Published
- 2013.08.08: COBRA for Python App Note Published
- 2013.04.19: COBRA for Python 0.2.1 Released
- 2013.03.13: Human Metabolism Recon 2.0 Published
- 2012.10.18: Paint4Net added to the Foundry.
- 2012.08.07: The ME Generation in the Jacobs School News
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 the genome scale. The COBRA approach focuses on employing physicochemical constraints 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 initial 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.
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-based modules for dealing with the complex relationships of the next generation of COBRA models.
Ebrahim A, Lerman JA, Palsson BO, Hyduke DR. 2013 COBRApy: COnstraints-Based Reconstruction and Analysis for Python. BMC Syst Bio 7:74.
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.