References of "Kell, Douglas B"
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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 detailAutomated workflows for accurate mass-based putative metabolite identification in LC/MS-derived metabolomic datasets.
Brown, Marie; Wedge, David C.; Goodacre, Royston et al

in Bioinformatics (2011), 27(8), 1108-12

MOTIVATION: The study of metabolites (metabolomics) is increasingly being applied to investigate microbial, plant, environmental and mammalian systems. One of the limiting factors is that of chemically ... [more ▼]

MOTIVATION: The study of metabolites (metabolomics) is increasingly being applied to investigate microbial, plant, environmental and mammalian systems. One of the limiting factors is that of chemically identifying metabolites from mass spectrometric signals present in complex datasets. RESULTS: Three workflows have been developed to allow for the rapid, automated and high-throughput annotation and putative metabolite identification of electrospray LC-MS-derived metabolomic datasets. The collection of workflows are defined as PUTMEDID_LCMS and perform feature annotation, matching of accurate m/z to the accurate mass of neutral molecules and associated molecular formula and matching of the molecular formulae to a reference file of metabolites. The software is independent of the instrument and data pre-processing applied. The number of false positives is reduced by eliminating the inaccurate matching of many artifact, isotope, multiply charged and complex adduct peaks through complex interrogation of experimental data. AVAILABILITY: The workflows, standard operating procedure and further information are publicly available at http://www.mcisb.org/resources/putmedid.html. CONTACT: warwick.dunn@manchester.ac.uk. [less ▲]

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