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2013 | OriginalPaper | Buchkapitel

Evolutionary Algorithms for Parameter Estimation of Metabolic Systems

verfasst von: Anastasia Slustikova Lebedik, Ivan Zelinka

Erschienen in: Nostradamus 2013: Prediction, Modeling and Analysis of Complex Systems

Verlag: Springer International Publishing

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For many years, computational tools have been widely applied to study such complex systems as metabolic networks. One of the principal questions in modeling of metabolic systems is the parameter estimation of model, which is related to a nonlinear programming problem. Two types of evolutionary algorithms, Differential Evolution and Self-Organizing Migrating Algorithm, are applied to the well-studied metabolic system, the urea cycle of the mammalian hepatocyte. The algorithms provide an effective approach in parameters identification of the model.

Metadaten
Titel
Evolutionary Algorithms for Parameter Estimation of Metabolic Systems
verfasst von
Anastasia Slustikova Lebedik
Ivan Zelinka
Copyright-Jahr
2013
Verlag
Springer International Publishing
DOI
https://doi.org/10.1007/978-3-319-00542-3_21

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