Cargando…

COBRApy: COnstraints-Based Reconstruction and Analysis for Python

BACKGROUND: COnstraint-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 integrate...

Descripción completa

Detalles Bibliográficos
Autores principales: Ebrahim, Ali, Lerman, Joshua A, Palsson, Bernhard O, Hyduke, Daniel R
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3751080/
https://www.ncbi.nlm.nih.gov/pubmed/23927696
http://dx.doi.org/10.1186/1752-0509-7-74
_version_ 1782281529225904128
author Ebrahim, Ali
Lerman, Joshua A
Palsson, Bernhard O
Hyduke, Daniel R
author_facet Ebrahim, Ali
Lerman, Joshua A
Palsson, Bernhard O
Hyduke, Daniel R
author_sort Ebrahim, Ali
collection PubMed
description BACKGROUND: COnstraint-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. RESULTS: Here, 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. CONCLUSION: COBRApy 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. AVAILABILITY: http://opencobra.sourceforge.net/
format Online
Article
Text
id pubmed-3751080
institution National Center for Biotechnology Information
language English
publishDate 2013
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-37510802013-08-24 COBRApy: COnstraints-Based Reconstruction and Analysis for Python Ebrahim, Ali Lerman, Joshua A Palsson, Bernhard O Hyduke, Daniel R BMC Syst Biol Software BACKGROUND: COnstraint-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. RESULTS: Here, 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. CONCLUSION: COBRApy 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. AVAILABILITY: http://opencobra.sourceforge.net/ BioMed Central 2013-08-08 /pmc/articles/PMC3751080/ /pubmed/23927696 http://dx.doi.org/10.1186/1752-0509-7-74 Text en Copyright © 2013 Ebrahim et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software
Ebrahim, Ali
Lerman, Joshua A
Palsson, Bernhard O
Hyduke, Daniel R
COBRApy: COnstraints-Based Reconstruction and Analysis for Python
title COBRApy: COnstraints-Based Reconstruction and Analysis for Python
title_full COBRApy: COnstraints-Based Reconstruction and Analysis for Python
title_fullStr COBRApy: COnstraints-Based Reconstruction and Analysis for Python
title_full_unstemmed COBRApy: COnstraints-Based Reconstruction and Analysis for Python
title_short COBRApy: COnstraints-Based Reconstruction and Analysis for Python
title_sort cobrapy: constraints-based reconstruction and analysis for python
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3751080/
https://www.ncbi.nlm.nih.gov/pubmed/23927696
http://dx.doi.org/10.1186/1752-0509-7-74
work_keys_str_mv AT ebrahimali cobrapyconstraintsbasedreconstructionandanalysisforpython
AT lermanjoshuaa cobrapyconstraintsbasedreconstructionandanalysisforpython
AT palssonbernhardo cobrapyconstraintsbasedreconstructionandanalysisforpython
AT hydukedanielr cobrapyconstraintsbasedreconstructionandanalysisforpython