INCA: a computational platform for isotopically non-stationary metabolic flux analysis

JD Young - Bioinformatics, 2014 - academic.oup.com
Bioinformatics, 2014academic.oup.com
13C flux analysis studies have become an essential component of metabolic engineering
research. The scope of these studies has gradually expanded to include both isotopically
steady-state and transient labeling experiments, the latter of which are uniquely applicable
to photosynthetic organisms and slow-to-label mammalian cell cultures. Isotopomer network
compartmental analysis (INCA) is the first publicly available software package that can
perform both steady-state metabolic flux analysis and isotopically non-stationary metabolic …
Abstract
Summary:  13C flux analysis studies have become an essential component of metabolic engineering research. The scope of these studies has gradually expanded to include both isotopically steady-state and transient labeling experiments, the latter of which are uniquely applicable to photosynthetic organisms and slow-to-label mammalian cell cultures. Isotopomer network compartmental analysis (INCA) is the first publicly available software package that can perform both steady-state metabolic flux analysis and isotopically non-stationary metabolic flux analysis. The software provides a framework for comprehensive analysis of metabolic networks using mass balances and elementary metabolite unit balances. The generation of balance equations and their computational solution is completely automated and can be performed on networks of arbitrary complexity.
Availability and implementation: MATLAB p-code files are freely available for non-commercial use and can be downloaded at http://mfa.vueinnovations.com. Commercial licenses are also available.
Contact:  j.d.young@vanderbilt.edu
Oxford University Press