Exact simulation of hybrid stochastic and deterministic models for biochemical systems

Abstract : Motivation : Over the last years it has become evident that stochastic effects play an important role in biological processes leading to an increase in stochastic modelling attempts. Despite the availability of exact algorithms to numerically solve the chemical master equation that entirely describes a stochastic system, stochastic simulations are most of the times very computationally expensive. Hybrid methods that treat some processes as in the deterministic framework and others as stochastic are a promising way to speed up simulations for those cases involving different time scales, e.g., systems integrating metabolic pathways and gene regulatory networks.
Type de document :
Rapport
[Research Report] RR-5435, INRIA. 2004, pp.20
Liste complète des métadonnées

https://hal.inria.fr/inria-00070572
Contributeur : Rapport de Recherche Inria <>
Soumis le : vendredi 19 mai 2006 - 20:54:49
Dernière modification le : samedi 17 septembre 2016 - 01:27:14
Document(s) archivé(s) le : dimanche 4 avril 2010 - 21:29:33

Fichiers

Identifiants

  • HAL Id : inria-00070572, version 1

Collections

Citation

Aurélien Alfonsi, Eric Cancès, Gabriel Turinici, Barbara Di Ventura, Wilhelm Huisinga. Exact simulation of hybrid stochastic and deterministic models for biochemical systems. [Research Report] RR-5435, INRIA. 2004, pp.20. 〈inria-00070572〉

Partager

Métriques

Consultations de
la notice

525

Téléchargements du document

644