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.

Colombo, R., Damiani, C., Mauri, G., Pescini, D. (2017). Constraining mechanism based simulations to identify ensembles of parametrizations to characterize metabolic features. In Computational Intelligence Methods for Bioinformatics and Biostatistics. 13th International Meeting, CIBB 2016, Stirling, UK, September 1-3, 2016, Revised Selected Papers (pp.107-117). Springer Verlag [10.1007/978-3-319-67834-4_9].

Constraining mechanism based simulations to identify ensembles of parametrizations to characterize metabolic features

Colombo, R
;
Damiani, C;Mauri, G;Pescini, D
2017

Abstract

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.
No
paper
Scientifica
Ensembles; Fluxes; Kinetic parameters; Mechanistic simulations; Metabolism; ODEs; Steady state; Systems biology; Theoretical Computer Science; Computer Science (all)
English
13th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2016
9783319678337
http://springerlink.com/content/0302-9743/copyright/2005/
Colombo, R., Damiani, C., Mauri, G., Pescini, D. (2017). Constraining mechanism based simulations to identify ensembles of parametrizations to characterize metabolic features. In Computational Intelligence Methods for Bioinformatics and Biostatistics. 13th International Meeting, CIBB 2016, Stirling, UK, September 1-3, 2016, Revised Selected Papers (pp.107-117). Springer Verlag [10.1007/978-3-319-67834-4_9].
Colombo, R; Damiani, C; Mauri, G; Pescini, D
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10281/183667
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