Fast exact stochastic simulation algorithms using partial propensities
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Author / Producer
Date
2010
Publication Type
Conference Paper
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yes
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Abstract
We review the class of partial‐propensity exact stochastic simulation algorithms (SSA) for chemical reaction networks. We show which modules partial‐propensity SSAs are composed of and how partial‐propensity variants of known SSAs can be constructed by adjusting the sampling strategy used. We demonstrate this on the example of two instances, namely the partial‐propensity variant of Gillespie’s original direct method and that of the SSA with composition‐rejection sampling (SSA‐CR). Partial‐propensity methods may outperform the corresponding classical SSA, particularly on strongly coupled reaction networks. Changing the different modules of partial‐propensity SSAs provides flexibility in tuning them to perform particularly well on certain classes of reaction networks. The framework presented here defines the design space of such adaptations.
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Publication status
published
External links
Book title
ICNAAM 2010: International Conference of Numerical Analysis and Applied Mathematics 2010
Journal / series
Volume
1281
Pages / Article No.
1338 - 1341
Publisher
American Institute of Physics
Event
8th International Conference of Numerical Analysis and Applied Mathematics (ICNAAM 2010)
Edition / version
Methods
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Geographic location
Date collected
Date created
Subject
Stochastic simulation algorithm, SSA; Partial propensities; Chemical reactions; Partial propensity methods
Organisational unit
03749 - Sbalzarini, Ivo F. (ehemalig)