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Issue 9, 2012
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Inferring differences in the distribution of reaction rates across conditions

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Abstract

Elucidating changes in the distribution of reaction rates in metabolic pathways under different conditions is a central challenge in systems biology. Here we present a method for inferring regulation mechanisms responsible for changes in the distribution of reaction rates across conditions from correlations in time-resolved data. A reversal of correlations between conditions reveals information about regulation mechanisms. With the use of a small in silico hypothetical network, based on only the topology and directionality of a known pathway, several regulation scenarios can be formulated. Confronting these scenarios with experimental data results in a short list of possible pathway regulation mechanisms associated with the reversal of correlations between conditions. This procedure allows for the formulation of regulation scenarios without detailed prior knowledge of kinetics and for the inference of reaction rate changes without rate information. The method was applied to experimental time-resolved metabolomics data from multiple short-term perturbation-response experiments in S. cerevisiae across aerobic and anaerobic conditions. The method's output was validated against a detailed kinetic model of glycolysis in S. cerevisiae, which showed that the method can indeed infer the correct regulation scenario.

Graphical abstract: Inferring differences in the distribution of reaction rates across conditions

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Publication details

The article was received on 13 Jan 2012, accepted on 28 May 2012 and first published on 30 May 2012


Article type: Paper
DOI: 10.1039/C2MB25015B
Citation: Mol. BioSyst., 2012,8, 2415-2423
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    Inferring differences in the distribution of reaction rates across conditions

    D. M. Hendrickx, H. C. J. Hoefsloot, M. M. W. B. Hendriks, D. J. Vis, A. B. Canelas, B. Teusink and A. K. Smilde, Mol. BioSyst., 2012, 8, 2415
    DOI: 10.1039/C2MB25015B

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