title: ORCA: a COBRA toolbox extension for model-driven discovery and analysis.
abstract: CONCLUSIONS
  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.
  
  
  METHODS
  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.
authors: Department of Molecular Biosciences, Centre for Advanced Computational Solutions, Lincoln University, Lincoln 7647, New Zealand.
authors: Longfei
authors: L
authors: Mao
authors: Wynand S
authors: WS
authors: Verwoerd
mesh_terms: D018533:Biomass; D019149:Bioreactors; D019295:Computational Biology; D003198:Computer Simulation; D004798:Enzymes; D053858:Metabolic Networks and Pathways; D055432:Metabolomics; D008954:Models, Biological; D012984:Software
chemical_list: D004798:Enzymes