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Cited 4 time in webofscience Cited 4 time in scopus
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dc.contributor.authorEnciso, German-
dc.contributor.authorKim, Jinsu-
dc.date.accessioned2022-03-04T10:20:30Z-
dc.date.available2022-03-04T10:20:30Z-
dc.date.created2022-03-04-
dc.date.issued2019-05-
dc.identifier.issn0092-8240-
dc.identifier.urihttps://oasis.postech.ac.kr/handle/2014.oak/110548-
dc.description.abstractWe provide a short review of stochastic modeling in chemical reaction networks for mathematical and quantitative biologists. We use as case studies two publications appearing in this issue of the Bulletin, on the modeling of quasi-steady-state approximations and cell polarity. Reasons for the relevance of stochastic modeling are described along with some common differences between stochastic and deterministic models.-
dc.languageEnglish-
dc.publisherAcademic Press-
dc.relation.isPartOfBulletin of Mathematical Biology-
dc.titleEmbracing Noise in Chemical Reaction Networks-
dc.typeArticle-
dc.identifier.doi10.1007/s11538-019-00575-3-
dc.type.rimsART-
dc.identifier.bibliographicCitationBulletin of Mathematical Biology, v.81, no.5, pp.1261 - 1267-
dc.identifier.wosid000463753900001-
dc.citation.endPage1267-
dc.citation.number5-
dc.citation.startPage1261-
dc.citation.titleBulletin of Mathematical Biology-
dc.citation.volume81-
dc.contributor.affiliatedAuthorKim, Jinsu-
dc.identifier.scopusid2-s2.0-85061276043-
dc.description.journalClass1-
dc.description.journalClass1-
dc.description.isOpenAccessN-
dc.type.docTypeEditorial Material-
dc.subject.keywordAuthorStochasticity-
dc.subject.keywordAuthorChemical reaction network-
dc.subject.keywordAuthorNoise-
dc.subject.keywordAuthorScaling limit-
dc.subject.keywordAuthorSystems biology-
dc.relation.journalWebOfScienceCategoryBiology-
dc.relation.journalWebOfScienceCategoryMathematical & Computational Biology-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaLife Sciences & Biomedicine - Other Topics-
dc.relation.journalResearchAreaMathematical & Computational Biology-

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