INCA: a computational platform for isotopically non-stationary metabolic flux analysis
Author(s) -
Jamey D. Young
Publication year - 2014
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btu015
Subject(s) - metabolic flux analysis , flux (metallurgy) , computer science , isotopomers , transient (computer programming) , flux balance analysis , biological system , metabolic network , steady state (chemistry) , software , component (thermodynamics) , metabolic engineering , metabolomics , biochemical engineering , network analysis , chemistry , physics , chromatography , thermodynamics , metabolism , biochemistry , biology , engineering , enzyme , organic chemistry , quantum mechanics , molecule , programming language , operating system
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.
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