COBRApy: COnstraints-Based Reconstruction and Analysis for Python

By Ali Ebrahim, Joshua A. Lerman, Bernhard O. Palsson, Daniel R. Hyduke. BMC Systems Biology, 2013

1,250 citations recorded by the source corpus.

BackgroundCOnstraint-Based Reconstruction and Analysis (COBRA) methods are widely used for genome-scale modeling of metabolic networks in both prokaryotes and eukaryotes. Due to the successes with metabolism, there is an increasing effort to apply COBRA methods to reconstruct and analyze integrated models of cellular processes. The COBRA Toolbox for MATLAB is a leading software package for genome-scale analysis of metabolism; however, it was not designed to elegantly capture the complexity inherent in integrated biological networks and lacks an integration framework for the multiomics data used in systems biology. The openCOBRA Project is a community effort to promote constraints-based research through the distribution of freely available software.ResultsHere, we describe COBRA for Python (COBRApy), a Python package that provides support for basic COBRA methods. COBRApy is designed in an object-oriented fashion that facilitates the representation of the complex biological processes of metabolism and gene expression. COBRApy does not require MATLAB to function; however, it includes an interface to the COBRA Toolbox for MATLAB to facilitate use of legacy codes. For improved performance, COBRApy includes parallel processing support for computationally intensive processes.ConclusionCOBRApy is an object-oriented framework designed to meet the computational challenges associated with the next generation of stoichiometric constraint-based models and high-density omics data sets.Availabilityhttp://opencobra.sourceforge.net/

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/5a4f5a00e3ada771129e85a503d9962333acfd16

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Citations in the corpus

The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases (2015, methodology): “A similar technique has also been implemented by the COBRA (COnstraints-Based Reconstruction and Analysis) group (16).”
BiGG Models: A platform for integrating, standardizing and sharing genome-scale models (2015, methodology): “The BiGG Models resource is compatible with other tools such as CO-BRApy (32) and Escher (24), which can also be deployed in other research labs.”
Using Genome-Scale Models to Predict Biological Capabilities (2015, neutral): “Several tools for reactome assembly and curation exist, including the COBRA Toolbox (Ebrahim et al., 2013; Schellenberger et al., 2011b), KEGG (Kanehisa et al.”
RAVEN 2.0: A versatile toolbox for metabolic network reconstruction and a case study on Streptomyces coelicolor (2018, methodology): “Models can be handled in various file-formats, including the community standard SBML L3V1 FBCv2 that is compatible with many other constraint-based modelling tools, including the COBRA Toolbox [23], as well as non-MATLAB tools as COBRApy [35] and SBML-R [36].”
Escher: A Web Application for Building, Sharing, and Embedding Data-Rich Visualizations of Biological Pathways (2015, methodology): “The Python package works directly with COBRA models using COBRApy [40].”