Evolutionary Algorithms for Parameter Estimation of Metabolic Systems

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F13%3A86088786" target="_blank" >RIV/61989100:27240/13:86088786 - isvavai.cz</a>
Alternative codes found
RIV/70883521:28140/13:43869794
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-00542-3_21" target="_blank" >http://dx.doi.org/10.1007/978-3-319-00542-3_21</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-00542-3_21" target="_blank" >10.1007/978-3-319-00542-3_21</a>

Result language
angličtina
Original language name
Evolutionary Algorithms for Parameter Estimation of Metabolic Systems
Original language 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.
Czech name
—
Czech description
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Project
<a href="/en/project/GA13-08195S" target="_blank" >GA13-08195S: Highly Scalable Parallel and Distributed Methods of Data Processing in E-science</a><br>
Continuities
S - Specificky vyzkum na vysokych skolach

Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Advances in Intelligent Systems and Computing. Volume 210
ISBN
978-3-319-00541-6
ISSN
2194-5357
e-ISSN
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Number of pages
9
Pages from-to
201-209
Publisher name
Springer
Place of publication
Heidelberg
Event location
Ostrava
Event date
Jun 3, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—

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