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Statements

Subject Item
n2:RIV%2F61989100%3A27240%2F13%3A86088786%21RIV14-GA0-27240___
rdf:type
n19:Vysledek skos:Concept
dcterms:description
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. 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.
dcterms:title
Evolutionary Algorithms for Parameter Estimation of Metabolic Systems Evolutionary Algorithms for Parameter Estimation of Metabolic Systems
skos:prefLabel
Evolutionary Algorithms for Parameter Estimation of Metabolic Systems Evolutionary Algorithms for Parameter Estimation of Metabolic Systems
skos:notation
RIV/61989100:27240/13:86088786!RIV14-GA0-27240___
n19:predkladatel
n21:orjk%3A27240
n3:aktivita
n22:S n22:P
n3:aktivity
P(GA13-08195S), S
n3:dodaniDat
n4:2014
n3:domaciTvurceVysledku
n18:3433390
n3:druhVysledku
n10:D
n3:duvernostUdaju
n16:S
n3:entitaPredkladatele
n20:predkladatel
n3:idSjednocenehoVysledku
73814
n3:idVysledku
RIV/61989100:27240/13:86088786
n3:jazykVysledku
n11:eng
n3:klicovaSlova
Self-organizing migrating algorithm.; Parameters identification; Nonlinear programming problem; Metabolic systems; Metabolic network; Effective approaches; Differential Evolution; Computational tools
n3:klicoveSlovo
n6:Self-organizing%20migrating%20algorithm. n6:Differential%20Evolution n6:Metabolic%20network n6:Metabolic%20systems n6:Effective%20approaches n6:Nonlinear%20programming%20problem n6:Parameters%20identification n6:Computational%20tools
n3:kontrolniKodProRIV
[88547DF8B642]
n3:mistoKonaniAkce
Ostrava
n3:mistoVydani
Heidelberg
n3:nazevZdroje
Advances in Intelligent Systems and Computing. Volume 210
n3:obor
n14:IN
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
2
n3:projekt
n12:GA13-08195S
n3:rokUplatneniVysledku
n4:2013
n3:tvurceVysledku
Sluštíková Lebedik, Anastasia Zelinka, Ivan
n3:typAkce
n5:WRD
n3:zahajeniAkce
2013-06-03+02:00
s:issn
2194-5357
s:numberOfPages
9
n15:doi
10.1007/978-3-319-00542-3_21
n17:hasPublisher
Springer-Verlag
n23:isbn
978-3-319-00541-6
n13:organizacniJednotka
27240