This paper introduces HRSSA (Hybrid Rejection-based Stochastic simulation Algorithm), a new efficient hybrid stochastic simulation algorithm for spatially homogeneous biochemical reaction networks. HRSSA is built on top of RSSA, an exact stochastic simulation algorithm which relies on propensity bounds to select next reaction firings and to reduce the average number of reaction propensity updates needed during the simulation. HRSSA exploits the computational advantage of propensity bounds to manage time-varying transition propensities and to apply dynamic partitioning of reactions, which constitute the two most significant bottlenecks of hybrid simulation. A comprehensive set of simulation benchmarks is provided for evaluating performance and accuracy of HRSSA against other state of the art algorithms. © 2016 Elsevier Inc. All rights reserved

HRSSA – Efficient hybrid stochastic simulation for spatially homogeneous biochemical reaction networks / Marchetti, Luca; Priami, Corrado; Vo Hong, Thanh. - In: JOURNAL OF COMPUTATIONAL PHYSICS. - ISSN 0021-9991. - 317:(2016), pp. 301-317. [10.1016/j.jcp.2016.04.056]

HRSSA – Efficient hybrid stochastic simulation for spatially homogeneous biochemical reaction networks

Marchetti, Luca;Priami, Corrado;Thanh, Vo Hong
2016-01-01

Abstract

This paper introduces HRSSA (Hybrid Rejection-based Stochastic simulation Algorithm), a new efficient hybrid stochastic simulation algorithm for spatially homogeneous biochemical reaction networks. HRSSA is built on top of RSSA, an exact stochastic simulation algorithm which relies on propensity bounds to select next reaction firings and to reduce the average number of reaction propensity updates needed during the simulation. HRSSA exploits the computational advantage of propensity bounds to manage time-varying transition propensities and to apply dynamic partitioning of reactions, which constitute the two most significant bottlenecks of hybrid simulation. A comprehensive set of simulation benchmarks is provided for evaluating performance and accuracy of HRSSA against other state of the art algorithms. © 2016 Elsevier Inc. All rights reserved
2016
Marchetti, Luca; Priami, Corrado; Vo Hong, Thanh
HRSSA – Efficient hybrid stochastic simulation for spatially homogeneous biochemical reaction networks / Marchetti, Luca; Priami, Corrado; Vo Hong, Thanh. - In: JOURNAL OF COMPUTATIONAL PHYSICS. - ISSN 0021-9991. - 317:(2016), pp. 301-317. [10.1016/j.jcp.2016.04.056]
File in questo prodotto:
File Dimensione Formato  
HRSSA.pdf

Solo gestori archivio

Tipologia: Versione editoriale (Publisher’s layout)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 1.2 MB
Formato Adobe PDF
1.2 MB Adobe PDF   Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/326048
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 24
  • ???jsp.display-item.citation.isi??? 23
social impact