Systems biology ORCA: a COBRA toolbox extension for model-driven discovery and analysis

• Main Authors: Longfei Mao, Wynand S Verwoerd
• Other Authors: The Pennsylvania State University CiteSeerX Archives
• Format: Text
• Language: English
• Subjects: Orca
• Online Access: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1035.4824; http://bioinformatics.oxfordjournals.org/content/early/2013/12/27/bioinformatics.btt723.full.pdf

ABSTRACT Summary: 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. Availability and implementation: 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.