A distributed approach for parameter estimation in Systems Biology models (Articolo in rivista)

Type
Label
  • A distributed approach for parameter estimation in Systems Biology models (Articolo in rivista) (literal)
Anno
  • 2009-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1393/ncc/i2009-10400-2 (literal)
Alternative label
  • Mosca, E.; Merelli, I.; Alfieri, R.; Milanesi, L. (2009)
    A distributed approach for parameter estimation in Systems Biology models
    in Il Nuovo cimento della Società italiana di fisica. C. Geophysics and space physics (Testo stamp.)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Mosca, E.; Merelli, I.; Alfieri, R.; Milanesi, L. (literal)
Pagina inizio
  • 165 (literal)
Pagina fine
  • 168 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 32 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
  • 4 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
  • 2 (literal)
Note
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Consiglio Nazionale delle Ricerche (CNR) (literal)
Titolo
  • A distributed approach for parameter estimation in Systems Biology models (literal)
Abstract
  • Due to the lack of experimental measurements, biological variability and experimental errors, the value of many parameters of the systems biology mathematical models is yet unknown or uncertain. A possible computational solution is the parameter estimation, that is the identification of the parameter values that determine the best model fitting respect to experimental data. We have developed an experiment to distribute each run of the parameter estimation algorithm on a different computational resource. The key feature of the implementation is a relational database that allows the user to swap the candidate solutions among the working nodes during the computations. The comparison of the distributed implementation with the parallel one showed that the presented approach enables a faster and better estimation of systems biology models. (literal)
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