Simulation methods with extended stability for stiff biochemical Kinetics
Background: With increasing computer power, simulating the dynamics of complex systems in chemistry and biology is becoming increasingly routine. The modelling of individual reactions in (bio)chemical systems involves a large number of random events that can be simulated by the stochastic simulation...
| Autores: | , , |
|---|---|
| Tipo de documento: | artigo |
| Data de publicação: | 2010 |
| País: | España |
| Recursos: | Universitat Politècnica de Catalunya (UPC) |
| Repositório: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglês |
| OAI Identifier: | oai:upcommons.upc.edu:2117/10071 |
| Acesso em linha: | https://hdl.handle.net/2117/10071 https://dx.doi.org/10.1186/1752-0509-4-110 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Biocomputers Poisson τ-leap methods Runge-Kutta (RK) τ-leap methods Stiff biochemical Kinetics Informàtica aplicada -- Medicina Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica |
| id |
ES_f8317bcb4d0404a6139509102e45b299 |
|---|---|
| oai_identifier_str |
oai:upcommons.upc.edu:2117/10071 |
| network_acronym_str |
ES |
| network_name_str |
España |
| repository_id_str |
|
| spelling |
Simulation methods with extended stability for stiff biochemical KineticsRue Queralt, PauVillà-Freixa, JordiBurrage, KevinBiocomputersPoisson τ-leap methodsRunge-Kutta (RK) τ-leap methodsStiff biochemical KineticsInformàtica aplicada -- MedicinaÀrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::BioinformàticaBackground: With increasing computer power, simulating the dynamics of complex systems in chemistry and biology is becoming increasingly routine. The modelling of individual reactions in (bio)chemical systems involves a large number of random events that can be simulated by the stochastic simulation algorithm (SSA). The key quantity is the step size, or waiting time, τ, whose value inversely depends on the size of the propensities of the different channel reactions and which needs to be re-evaluated after every firing event. Such a discrete event simulation may be extremely expensive, in particular for stiff systems where τ can be very short due to the fast kinetics of some of the channel reactions. Several alternative methods have been put forward to increase the integration step size. The so-called τ-leap approach takes a larger step size by allowing all the reactions to fire, from a Poisson or Binomial distribution, within that step. Although the expected value for the different species in the reactive system is maintained with respect to more precise methods, the variance at steady state can suffer from large errors as τ grows. Results: In this paper we extend Poisson τ-leap methods to a general class of Runge-Kutta (RK) τ-leap methods. We show that with the proper selection of the coefficients, the variance of the extended τ-leap can be wellbehaved, leading to significantly larger step sizes. Conclusions: The benefit of adapting the extended method to the use of RK frameworks is clear in terms of speed of calculation, as the number of evaluations of the Poisson distribution is still one set per time step, as in the original τ-leap method. The approach paves the way to explore new multiscale methods to simulate (bio)chemical systems.Peer Reviewed20102010-08-1120102010-11-02journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/10071https://dx.doi.org/10.1186/1752-0509-4-11020701766reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)InglésengEuropean Commission http://dx.doi.org/10.13039/100011102 Seventh Framework Programme 223920 Virtual Physiological Human Network of Excellenceopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/100712026-05-27T15:37:01Z |
| dc.title.none.fl_str_mv |
Simulation methods with extended stability for stiff biochemical Kinetics |
| title |
Simulation methods with extended stability for stiff biochemical Kinetics |
| spellingShingle |
Simulation methods with extended stability for stiff biochemical Kinetics Rue Queralt, Pau Biocomputers Poisson τ-leap methods Runge-Kutta (RK) τ-leap methods Stiff biochemical Kinetics Informàtica aplicada -- Medicina Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica |
| title_short |
Simulation methods with extended stability for stiff biochemical Kinetics |
| title_full |
Simulation methods with extended stability for stiff biochemical Kinetics |
| title_fullStr |
Simulation methods with extended stability for stiff biochemical Kinetics |
| title_full_unstemmed |
Simulation methods with extended stability for stiff biochemical Kinetics |
| title_sort |
Simulation methods with extended stability for stiff biochemical Kinetics |
| dc.creator.none.fl_str_mv |
Rue Queralt, Pau Villà-Freixa, Jordi Burrage, Kevin |
| author |
Rue Queralt, Pau |
| author_facet |
Rue Queralt, Pau Villà-Freixa, Jordi Burrage, Kevin |
| author_role |
author |
| author2 |
Villà-Freixa, Jordi Burrage, Kevin |
| author2_role |
author author |
| dc.subject.none.fl_str_mv |
Biocomputers Poisson τ-leap methods Runge-Kutta (RK) τ-leap methods Stiff biochemical Kinetics Informàtica aplicada -- Medicina Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica |
| topic |
Biocomputers Poisson τ-leap methods Runge-Kutta (RK) τ-leap methods Stiff biochemical Kinetics Informàtica aplicada -- Medicina Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica |
| description |
Background: With increasing computer power, simulating the dynamics of complex systems in chemistry and biology is becoming increasingly routine. The modelling of individual reactions in (bio)chemical systems involves a large number of random events that can be simulated by the stochastic simulation algorithm (SSA). The key quantity is the step size, or waiting time, τ, whose value inversely depends on the size of the propensities of the different channel reactions and which needs to be re-evaluated after every firing event. Such a discrete event simulation may be extremely expensive, in particular for stiff systems where τ can be very short due to the fast kinetics of some of the channel reactions. Several alternative methods have been put forward to increase the integration step size. The so-called τ-leap approach takes a larger step size by allowing all the reactions to fire, from a Poisson or Binomial distribution, within that step. Although the expected value for the different species in the reactive system is maintained with respect to more precise methods, the variance at steady state can suffer from large errors as τ grows. Results: In this paper we extend Poisson τ-leap methods to a general class of Runge-Kutta (RK) τ-leap methods. We show that with the proper selection of the coefficients, the variance of the extended τ-leap can be wellbehaved, leading to significantly larger step sizes. Conclusions: The benefit of adapting the extended method to the use of RK frameworks is clear in terms of speed of calculation, as the number of evaluations of the Poisson distribution is still one set per time step, as in the original τ-leap method. The approach paves the way to explore new multiscale methods to simulate (bio)chemical systems. |
| publishDate |
2010 |
| dc.date.none.fl_str_mv |
2010 2010-08-11 2010 2010-11-02 |
| dc.type.none.fl_str_mv |
journal article http://purl.org/coar/resource_type/c_6501 VoR http://purl.org/coar/version/c_970fb48d4fbd8a85 |
| dc.type.openaire.fl_str_mv |
info:eu-repo/semantics/article |
| format |
article |
| dc.identifier.none.fl_str_mv |
https://hdl.handle.net/2117/10071 https://dx.doi.org/10.1186/1752-0509-4-110 20701766 |
| url |
https://hdl.handle.net/2117/10071 https://dx.doi.org/10.1186/1752-0509-4-110 |
| identifier_str_mv |
20701766 |
| dc.language.none.fl_str_mv |
Inglés eng |
| language_invalid_str_mv |
Inglés |
| language |
eng |
| dc.relation.none.fl_str_mv |
European Commission http://dx.doi.org/10.13039/100011102 Seventh Framework Programme 223920 Virtual Physiological Human Network of Excellence |
| dc.rights.none.fl_str_mv |
open access http://purl.org/coar/access_right/c_abf2 |
| dc.rights.openaire.fl_str_mv |
info:eu-repo/semantics/openAccess |
| rights_invalid_str_mv |
open access http://purl.org/coar/access_right/c_abf2 |
| eu_rights_str_mv |
openAccess |
| dc.format.none.fl_str_mv |
application/pdf |
| dc.source.none.fl_str_mv |
reponame:UPCommons. Portal del coneixement obert de la UPC instname:Universitat Politècnica de Catalunya (UPC) |
| instname_str |
Universitat Politècnica de Catalunya (UPC) |
| reponame_str |
UPCommons. Portal del coneixement obert de la UPC |
| collection |
UPCommons. Portal del coneixement obert de la UPC |
| repository.name.fl_str_mv |
|
| repository.mail.fl_str_mv |
|
| _version_ |
1869424978945900544 |
| score |
15.301603 |