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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
Book Section, Bibliographie

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.

Item Type: Book Section
Erschienen: 2016
Creators: Ganguly, A. ; Altintan, D. ; Koeppl, H.
Type of entry: Bibliographie
Title: Efficient Simulation of Multiscale Reaction
Language: English
Date: July 2016
Place of Publication: New York, USA
Publisher: IEEE
Book Title: Proceedings of the American Control Conference 2016, Boston, MA, July 6-8, 2016
DOI: 10.1109/ACC.2016.7526623
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.

Divisions: 18 Department of Electrical Engineering and Information Technology
18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications > Bioinspired Communication Systems
18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications
Date Deposited: 10 Feb 2016 10:04
Last Modified: 29 May 2024 06:43
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