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dc.contributor.authorLakatos, Eszteren
dc.contributor.authorAle, Angeliqueen
dc.contributor.authorKirk, Paulen
dc.contributor.authorStumpf, Michael PHen
dc.date.accessioned2018-07-16T11:09:40Z
dc.date.available2018-07-16T11:09:40Z
dc.date.issued2015-09en
dc.identifier.issn0021-9606
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/278116
dc.description.abstractStochastic effects dominate many chemical and biochemical processes. Their analysis, however, can be computationally prohibitively expensive and a range of approximation schemes have been proposed to lighten the computational burden. These, notably the increasingly popular linear noise approximation and the more general moment expansion methods, perform well for many dynamical regimes, especially linear systems. At higher levels of nonlinearity, it comes to an interplay between the nonlinearities and the stochastic dynamics, which is much harder to capture correctly by such approximations to the true stochastic processes. Moment-closure approaches promise to address this problem by capturing higher-order terms of the temporally evolving probability distribution. Here, we develop a set of multivariate moment-closures that allows us to describe the stochastic dynamics of nonlinear systems. Multivariate closure captures the way that correlations between different molecular species, induced by the reaction dynamics, interact with stochastic effects. We use multivariate Gaussian, gamma, and lognormal closure and illustrate their use in the context of two models that have proved challenging to the previous attempts at approximating stochastic dynamics: oscillations in p53 and Hes1. In addition, we consider a larger system, Erk-mediated mitogen-activated protein kinases signalling, where conventional stochastic simulation approaches incur unacceptably high computational costs.
dc.format.mediumPrinten
dc.languageengen
dc.subjectMultivariate Analysisen
dc.subjectStochastic Processesen
dc.subjectKineticsen
dc.subjectModels, Chemicalen
dc.titleMultivariate moment closure techniques for stochastic kinetic models.en
dc.typeArticle
prism.issueIdentifier9en
prism.publicationDate2015en
prism.publicationNameThe Journal of chemical physicsen
prism.startingPage094107
prism.volume143en
dc.identifier.doi10.17863/CAM.25455
dcterms.dateAccepted2015-08-02en
rioxxterms.versionofrecord10.1063/1.4929837en
rioxxterms.versionVoR*
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2015-09en
dc.contributor.orcidLakatos, Eszter [0000-0002-7221-6850]
dc.contributor.orcidKirk, Paul [0000-0002-5931-7489]
dc.contributor.orcidStumpf, Michael PH [0000-0002-3577-1222]
dc.identifier.eissn1089-7690
rioxxterms.typeJournal Article/Reviewen


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