Metabolic models are the most widespread type of models in systems biology and are currently used in several applications, including metabolic engineering and investigations of pathological states in which metabolic disorders play a relevant role. Once a model has been defined and corroborated, sensitivity analysis techniques can be used to study the model behavior in relation to perturbations of the model parameters. Here, we describe how it is possible to combine regionalized sensitivity analysis and response surface methodology to screen and quantitatively characterize the relation between metabolic phenotypes and biochemical reactions rates. By means of this approach, we identi¯ed the most important reactions for the citric acid e®lux from mitochondria, one of the key metabolic traits of cancer cells.
Maj, C., Mosca, E., Merelli, I., Mauri, G., Milanesi, L. (2013). Sensitivity analysis for studying the relation between biochemical reactions and metabolic phenotypes. JOURNAL OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY, 11(01) [10.1142/S0219720013400027].
Sensitivity analysis for studying the relation between biochemical reactions and metabolic phenotypes
MAJ, CARLO;MOSCA, ETTORE;MERELLI, IVAN;MAURI, GIANCARLO;
2013
Abstract
Metabolic models are the most widespread type of models in systems biology and are currently used in several applications, including metabolic engineering and investigations of pathological states in which metabolic disorders play a relevant role. Once a model has been defined and corroborated, sensitivity analysis techniques can be used to study the model behavior in relation to perturbations of the model parameters. Here, we describe how it is possible to combine regionalized sensitivity analysis and response surface methodology to screen and quantitatively characterize the relation between metabolic phenotypes and biochemical reactions rates. By means of this approach, we identi¯ed the most important reactions for the citric acid e®lux from mitochondria, one of the key metabolic traits of cancer cells.File | Dimensione | Formato | |
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