Fast exact stochastic simulation algorithms using partial propensities

Publikation: Beitrag in FachzeitschriftKonferenzartikelBeigetragenBegutachtung

Beitragende

  • Rajesh Ramaswamy - , ETH Zurich (Autor:in)
  • Ivo F. Sbalzarini - , ETH Zurich (Autor:in)

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.

Details

OriginalspracheEnglisch
Seiten (von - bis)1338-1341
Seitenumfang4
FachzeitschriftAIP Conference Proceedings
Jahrgang1281
PublikationsstatusVeröffentlicht - 30 Sept. 2010
Peer-Review-StatusJa
Extern publiziertJa

Konferenz

TitelInternational Conference on Numerical Analysis and Applied Mathematics 2010, ICNAAM-2010
Dauer19 - 25 September 2010
StadtRhodes
LandGriechenland

Externe IDs

ORCID /0000-0003-4414-4340/work/159608315

Schlagworte

ASJC Scopus Sachgebiete

Schlagwörter

  • chemical reactions, partial propensities, partial propensity methods, SSA, stochastic simulation algorithm