References of "Mendes, Pedro"
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See detailA model of yeast glycolysis based on a consistent kinetic characterisation of all its enzymes
Smallbone, Kieran; Messiha, Hanan L.; Carroll, Kathleen M. et al

in FEBS Letters (2013), 587(17), 2832-2841

We present an experimental and computational pipeline for the generation of kinetic models of metabolism, and demonstrate its application to glycolysis in Saccharomyces cerevisiae. Starting from an ... [more ▼]

We present an experimental and computational pipeline for the generation of kinetic models of metabolism, and demonstrate its application to glycolysis in Saccharomyces cerevisiae. Starting from an approximate mathematical model, we employ a ‘‘cycle of knowledge’’ strategy, identifying the steps with most control over flux. Kinetic parameters of the individual isoenzymes within these steps are measured experimentally under a standardised set of conditions. Experimental strategies are applied to establish a set of in vivo concentrations for isoenzymes and metabolites. The data are integrated into a mathematical model that is used to predict a new set of metabolite concentrations and reevaluate the control properties of the system. This bottom-up modelling study reveals that control over the metabolic network most directly involved in yeast glycolysis is more widely distributed than previously thought. [less ▲]

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See detailChasing the flux: selecting target pathways through flux analysis of carbon metabolism
Simeonidis, Vangelis UL; Murabito, Ettore; Smallbone, Kieran et al

Poster (2011, June 26)

One of the goals of Systems Biology is to develop and utilise high-throughput methods for the measurement of parameters and concentrations on a genome-wide scale, while at the same time generating ... [more ▼]

One of the goals of Systems Biology is to develop and utilise high-throughput methods for the measurement of parameters and concentrations on a genome-wide scale, while at the same time generating predictive models for system behaviour. In studying genome-scale metabolic networks, the task of exhaustively assaying and measuring all reaction components can be daunting, because hundreds or even thousands of enzymes (activities and concentrations) need to be considered for the construction of a full-scale, detailed model. There is a clear need for strategies that allow us to systematically select the subsets of pathways and reactions which should be prioritized when studying metabolism. We present a methodology for selecting those reactions that carry the overwhelming majority of the carbon flux through the metabolic network. The recent community-driven reconstruction of the metabolic network of baker’s yeast [1] provides the basis for our analysis. Flux Balance Analysis provides a theoretical flux distribution. Results are constrained with GC-MS exometabolomic measurements of the carbon flux. Flux calculations can also be improved by using 13C measurements to determine intracellular metabolic fluxes. The solution of the constrained FBA problem gives us a ranked list of reactions, based on the amount of carbon flux through each reaction. We improve the specificity of the method further by performing an Elementary Flux Mode analysis, which provides us with target pathways consisting of the reactions that carry the most carbon flux. Our methodology allows us to cover more than 95% of the carbon flux by studying but a small subset of the reactions of the genome-scale metabolic network of baker’s yeast. [less ▲]

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