4.7 Article

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

期刊

BIOINFORMATICS
卷 30, 期 9, 页码 1333-1335

出版社

OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btu015

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资金

  1. National Science Foundation [CBET-0955251, CBET-1067766, CBET-1105991, EF-1105249]
  2. Department of Energy [DE-SC0008118]
  3. National Institutes of Health [CA155964, DK072856]
  4. U.S. Department of Energy (DOE) [DE-SC0008118] Funding Source: U.S. Department of Energy (DOE)
  5. Directorate For Engineering
  6. Div Of Chem, Bioeng, Env, & Transp Sys [1067766, 1106254] Funding Source: National Science Foundation
  7. Div Of Chem, Bioeng, Env, & Transp Sys
  8. Directorate For Engineering [1105991, 0955251] Funding Source: National Science Foundation

向作者/读者索取更多资源

C-13 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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