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Efficient Simulation of Multiscale Reaction

Ganguly, A. ; Altintan, D. ; Koeppl, H. (2016)
Efficient Simulation of Multiscale Reaction.
In: Proceedings of the American Control Conference 2016, Boston, MA, July 6-8, 2016
doi: 10.1109/ACC.2016.7526623
Buchkapitel, Bibliographie

Kurzbeschreibung (Abstract)

Cellular reaction systems are often multiscale in nature due to wide variation in the species abundance and reaction rates. Traditional deterministic or stochastic modeling of such systems, which do not exploit this multiscale behavior, will be computationally expensive for simulation or inference purposes. This necessitates developing simplified hybrid models combining both stochastic and deterministic approaches that can substantially speed up simulation of such reaction networks. The paper proposes a layered partitioning approach which not only split the reaction set into the usual ‘fast’ and the ‘slow’ groups, but further subdivides the fast group into subgroups of super fast and moderately fast reactions. While the occurrences of reactions from the super fast and moderately fast groups are approximated by ordinary differential equations (ODEs) and Itô diffusions respectively, the discrete counting process formulation is maintained for the reactions from the slow group. The paper develops a mathematical framework for objectively identifying these three groups and performs a rigorous error analysis for the approximation proposed. One important highlight of the paper is the utilization of the error analysis in constructing an efficient dynamic algorithm that can fully automate the partitioning process and make necessary adjustments, if needed, over the course of time.

Typ des Eintrags: Buchkapitel
Erschienen: 2016
Autor(en): Ganguly, A. ; Altintan, D. ; Koeppl, H.
Art des Eintrags: Bibliographie
Titel: Efficient Simulation of Multiscale Reaction
Sprache: Englisch
Publikationsjahr: Juli 2016
Ort: New York, USA
Verlag: IEEE
Buchtitel: Proceedings of the American Control Conference 2016, Boston, MA, July 6-8, 2016
DOI: 10.1109/ACC.2016.7526623
Kurzbeschreibung (Abstract):

Cellular reaction systems are often multiscale in nature due to wide variation in the species abundance and reaction rates. Traditional deterministic or stochastic modeling of such systems, which do not exploit this multiscale behavior, will be computationally expensive for simulation or inference purposes. This necessitates developing simplified hybrid models combining both stochastic and deterministic approaches that can substantially speed up simulation of such reaction networks. The paper proposes a layered partitioning approach which not only split the reaction set into the usual ‘fast’ and the ‘slow’ groups, but further subdivides the fast group into subgroups of super fast and moderately fast reactions. While the occurrences of reactions from the super fast and moderately fast groups are approximated by ordinary differential equations (ODEs) and Itô diffusions respectively, the discrete counting process formulation is maintained for the reactions from the slow group. The paper develops a mathematical framework for objectively identifying these three groups and performs a rigorous error analysis for the approximation proposed. One important highlight of the paper is the utilization of the error analysis in constructing an efficient dynamic algorithm that can fully automate the partitioning process and make necessary adjustments, if needed, over the course of time.

Fachbereich(e)/-gebiet(e): 18 Fachbereich Elektrotechnik und Informationstechnik
18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Nachrichtentechnik > Bioinspirierte Kommunikationssysteme
18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Nachrichtentechnik
Hinterlegungsdatum: 10 Feb 2016 10:04
Letzte Änderung: 29 Mai 2024 06:43
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