Constraint-based approaches have been proven useful to determine steady state fluxes in metabolic models, however they are not able to determine metabolite concentrations and they imply the assumption that a biological process is optimized towards a given function. In this work we define a computational strategy exploiting mechanism based simulations as a framework to determine, through a filtering procedure, ensembles of kinetic constants and steady state metabolic concentrations that are in agreement with one or more metabolic phenotypes, avoiding at the same time the need of assuming an optimization mechanism. To test our procedure we exploited a model of yeast metabolism and we filtered trajectories accordingly to a loose definition of the Crabtree phenotype.
CITATION STYLE
Colombo, R., Damiani, C., Mauri, G., & Pescini, D. (2017). Constraining mechanism based simulations to identify ensembles of parametrizations to characterize metabolic features. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10477 LNBI, pp. 107–117). Springer Verlag. https://doi.org/10.1007/978-3-319-67834-4_9
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