%0 Journal Article %1 Mao2014ORCA %A Mao, Longfei %A Verwoerd, Wynand S. %D 2014 %J Bioinformatics (Oxford, England) %K cobra flux-analysis software %N 4 %P 584--585 %R 10.1093/bioinformatics/btt723 %T ORCA: a COBRA toolbox extension for model-driven discovery and analysis. %U http://dx.doi.org/10.1093/bioinformatics/btt723 %V 30 %X Over past decades, constraint-based modelling has emerged as an important approach to obtain referential information about mechanisms behind biological phenotypes and identify physiological and perturbed metabolic states at genome-scale. However, application of this novel approach to systems biology in biotechnology is still hindered by the functionalities of the existing modelling software. To augment the usability of the constraint-based approach for various use scenarios, we present ORCA, a Matlab package, which extends the scope of established Constraint-Based Reconstruction and Analysis metabolic modelling and includes three unique functionalities: (i) a framework method integrating three analyses of multi-objective optimization, robustness analysis and fractional benefit analysis, (ii) metabolic pathways identification with futile loop elimination and (iii) a dynamic flux balance analysis framework incorporating kinetic constraints. ORCA is freely available to academic users and is downloadable from https://sourceforge.net/projects/exorca/; a mini-tutorial is supplied in the package for training purposes as well as a software manual. Longfei.mao@lincolnuni.ac.nz Supplementary data are available at Bioinformatics online.

@article{Mao2014ORCA, abstract = { Over past decades, constraint-based modelling has emerged as an important approach to obtain referential information about mechanisms behind biological phenotypes and identify physiological and perturbed metabolic states at genome-scale. However, application of this novel approach to systems biology in biotechnology is still hindered by the functionalities of the existing modelling software. To augment the usability of the constraint-based approach for various use scenarios, we present {ORCA}, a Matlab package, which extends the scope of established {Constraint-Based} Reconstruction and Analysis metabolic modelling and includes three unique functionalities: (i) a framework method integrating three analyses of multi-objective optimization, robustness analysis and fractional benefit analysis, (ii) metabolic pathways identification with futile loop elimination and (iii) a dynamic flux balance analysis framework incorporating kinetic constraints. {ORCA} is freely available to academic users and is downloadable from https://sourceforge.net/projects/exorca/; a mini-tutorial is supplied in the package for training purposes as well as a software manual. Longfei.mao@lincolnuni.ac.nz Supplementary data are available at Bioinformatics online. }, added-at = {2018-12-02T16:09:07.000+0100}, author = {Mao, Longfei and Verwoerd, Wynand S.}, biburl = {https://www.bibsonomy.org/bibtex/2c1a34bced4c42a86acb0310b93263801/karthikraman}, citeulike-article-id = {13108638}, citeulike-linkout-0 = {http://dx.doi.org/10.1093/bioinformatics/btt723}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/24336807}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=24336807}, day = 15, doi = {10.1093/bioinformatics/btt723}, interhash = {76e1f43c526ee53d98ee1ae90793d9a1}, intrahash = {c1a34bced4c42a86acb0310b93263801}, issn = {1367-4811}, journal = {Bioinformatics (Oxford, England)}, keywords = {cobra flux-analysis software}, month = feb, number = 4, pages = {584--585}, pmid = {24336807}, posted-at = {2014-03-17 07:22:29}, priority = {2}, timestamp = {2018-12-02T16:09:07.000+0100}, title = {{ORCA}: a {COBRA} toolbox extension for model-driven discovery and analysis.}, url = {http://dx.doi.org/10.1093/bioinformatics/btt723}, volume = 30, year = 2014 }