Simulation methods with extended stability for stiff biochemical Kinetics

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To access the full text documents, please follow this link: http://hdl.handle.net/20.500.12328/1697

dc.contributor.author	Rué, Pau
dc.contributor.author	Villà-Freixa, Jordi
dc.contributor.author	Burrage, Kevin
dc.date	2020-10-28T13:38:29Z
dc.date	2020-10-28T13:38:29Z
dc.date	2010
dc.identifier	Rué, Pau; Villà-Freixa, Jordi; Burrage, Kevin. Simulation methods with extended stability for stiff biochemical Kinetics. BMC Systems Biology, 2010, 4, p. 1-13. Disponible en: <https://bmcsystbiol.biomedcentral.com/articles/10.1186/1752-0509-4-110>. Fecha de acceso: 28 oct. 2020. DOI: 10.1186/1752-0509-4-110
dc.identifier	1752-0509
dc.identifier	http://hdl.handle.net/20.500.12328/1697
dc.identifier	https://dx.doi.org/10.1186/1752-0509-4-110
dc.identifier.uri	http://hdl.handle.net/20.500.12328/1697
dc.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.
dc.format	13
dc.format	application/pdf
dc.language	eng
dc.publisher	Springer Nature
dc.relation	BMC Systems Biology
dc.relation	4;
dc.relation	info:eu-repo/grantAgreement/ES/3PN/CTQ2008-00755/BQU
dc.rights	© 2010 Rué et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
dc.rights	https://creativecommons.org/licenses/by/2.0/
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	Cinètica química
dc.subject	Reaccions químiques
dc.subject	Bioquímica
dc.subject	Cinética química
dc.subject	Reacciones químicas
dc.subject	Bioquímica
dc.subject	Chemical kinetics
dc.subject	Chemical reactions
dc.subject	Biochemistry
dc.subject	57
dc.title	Simulation methods with extended stability for stiff biochemical Kinetics
dc.type	info:eu-repo/semantics/article
dc.type	info:eu-repo/semantics/publishedVersion

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