A method for estimating metabolic fluxes from incomplete isotopomer information

Juho Rousu, Ari Rantanen, Hannu Maaheimo, Esa Pitkänen, Katja Saarela, Esko Ukkonen

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

9 Citations (Scopus)

Abstract

Metabolic flux estimation-the problem of finding out the rates of reactions in metabolic pathways-is an important problem area in the study of metabolism. The most accurate technique for this task today is the use of isotopic tracer experiments, where a mixture of differently isotope-labeled substrates is fed to a cell culture and the propagation of the labels is observed from the products and intermediate metabolites, where possible. We present a generic methodology for solving the fluxes of a metabolic network in a steady state. The method differs from most previous approaches by not making prior assumptions about the topology of the metabolic network. Also, only very mild assumptions are made about the available measurement data, for example, both positional enrichment and mass isotopomer data can be used.
Original languageEnglish
Title of host publicationComputational Methods in Systems Biology
PublisherSpringer
Pages88-103
VolumePart II
ISBN (Electronic)978-3-540-36481-8
ISBN (Print)978-3-540-00605-3
DOIs
Publication statusPublished - 2003
MoE publication typeA4 Article in a conference publication
Event1st International Workshop on Computational Methods in Systems Biology, CMSB 2003 - Rovereto, Italy
Duration: 24 Feb 200326 Feb 2003

Publication series

SeriesLecture Notes in Computer Science
Volume2602
ISSN0302-9743

Conference

Conference1st International Workshop on Computational Methods in Systems Biology, CMSB 2003
CountryItaly
CityRovereto
Period24/02/0326/02/03

Keywords

  • Mass-spectrometry
  • Networks

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  • Cite this

    Rousu, J., Rantanen, A., Maaheimo, H., Pitkänen, E., Saarela, K., & Ukkonen, E. (2003). A method for estimating metabolic fluxes from incomplete isotopomer information. In Computational Methods in Systems Biology (Vol. Part II, pp. 88-103). Springer. Lecture Notes in Computer Science, Vol.. 2602 https://doi.org/10.1007/3-540-36481-1_8