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Briefings in Bioinformatics Advance Access originally published online on April 26, 2006
Briefings in Bioinformatics 2006 7(2):140-150; doi:10.1093/bib/bbl007
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© The Author 2006. Published by Oxford University Press. For Permissions, please email: journals.permissions@oxfordjournals.org

Special Issue Papers

Flux balance analysis in the era of metabolomics

Jong Min Lee, Erwin P. Gianchandani and Jason A. Papin

Corresponding author. Jason A. Papin, Department of Biomedical Engineering, University of Virginia, PO Box 800759, Charlottesville, VA 22908, USA. Tel: +1–434-924-8195; E-mail: papin{at}virginia.edu

Flux balance analysis (FBA) has emerged as an effective means to analyse biological networks in a quantitative manner. Much progress has been made on the extension of FBA to incorporate a priori biological knowledge, provide more practical descriptions of observed cell behaviours, and predict the outcome of network perturbations. Metabolomics is independently advancing as a set of high-throughput data acquisition tools providing dynamic profiles of metabolites in an unbiased manner. These data sets are neither yet sufficiently comprehensive nor accurate enough for generating large-scale kinetic models. Thus, there is a pressing need to develop quantitative techniques that can make use of the emerging data and embrace the associated uncertainties. This article reviews recent advances in FBA to meet this need and discusses the utility of FBA as a complement to metabolomics and the expected synergy as a result of combining these two techniques.

Keywords: metabolism, metabolome, genome scale analysis, network reconstruction, objective function, optimization


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