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dc.contributor.authorSchilstra, M.
dc.contributor.authorMartin, S.R.
dc.date.accessioned2010-01-05T13:39:06Z
dc.date.available2010-01-05T13:39:06Z
dc.date.issued2009
dc.identifier.citationSchilstra , M & Martin , S R 2009 , Simple stochastic simulation . in Methods in Enzymology: Computer Methods . vol. 467 , Elsevier , pp. 381-409 . https://doi.org/10.1016/S0076-6879(09)67015-4
dc.identifier.isbn978-0-12-375023-5
dc.identifier.otherPURE: 90136
dc.identifier.otherPURE UUID: 7b5ddb15-98ec-44ad-a0e2-3780a78cbc57
dc.identifier.otherdspace: 2299/4132
dc.identifier.otherScopus: 71549153473
dc.identifier.urihttp://hdl.handle.net/2299/4132
dc.descriptionOriginal paper can be found at: http://www.sciencedirect.com/science/bookseries/00766879 Copyright Elsevier.
dc.description.abstractStochastic simulations may be used to describe changes with time of a reaction system in a way that explicitly accounts for the fact that molecules show a significant degree of randomness in their dynamic behavior. The stochastic approach is almost invariably used when small numbers of molecules or molecular assemblies are involved because this randomness leads to significant deviations from the predictions of the conventional deterministic (or continuous) approach to the simulation of biochemical kinetics. Advances in computational methods over the three decades that have elapsed since the publication of Daniel Gillespie's seminal paper in 1977 (J. Phys. Chem. 81, 2340–2361) have allowed researchers to produce highly sophisticated models of complex biological systems. However, these models are frequently highly specific for the particular application and their description often involves mathematical treatments inaccessible to the nonspecialist. For anyone completely new to the field to apply such techniques in their own work might seem at first sight to be a rather intimidating prospect. However, the fundamental principles underlying the approach are in essence rather simple, and the aim of this article is to provide an entry point to the field for a newcomer. It focuses mainly on these general principles, both kinetic and computational, which tend to be not particularly well covered in specialist literature, and shows that interesting information may even be obtained using very simple operations in a conventional spreadsheet.en
dc.language.isoeng
dc.publisherElsevier
dc.relation.ispartofMethods in Enzymology: Computer Methods
dc.titleSimple stochastic simulationen
dc.contributor.institutionSchool of Computer Science
dc.contributor.institutionCentre for Computer Science and Informatics Research
dc.contributor.institutionScience & Technology Research Institute
dc.relation.schoolSchool of Computer Science
rioxxterms.versionVoR
rioxxterms.versionofrecordhttps://doi.org/10.1016/S0076-6879(09)67015-4
rioxxterms.typeOther
herts.preservation.rarelyaccessedtrue
herts.rights.accesstypeclosedAccess


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