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1、ParameterInferenceforStochasticKineticModelsofBacterialGeneRegulation:ABayesianApproachtoSystemsBiologyUniversityPressScholarshipOnlineOxfordScholarshipOnlineBayesianStatistics9JoséM.Bernardo,M.J.Bayarri,JamesO.Berger,A.P.Dawid,DavidHeckerman,AdrianF.M.Smith
2、,andMikeWestPrintpublicationdate:2011PrintISBN-13:9780199694587PublishedtoOxfordScholarshipOnline:January2012DOI:10.1093/acprof:oso/9780199694587.001.0001ParameterInferenceforStochasticKineticModelsofBacterialGeneRegulation:ABayesianApproachtoSystemsBiologyD
3、arrenJ.WilkinsonDOI:10.1093/acprof:oso/9780199694587.003.0023AbstractandKeywordsBacteriaaresingle‐celledorganismswhichoftendisplayheterogeneousbehaviour,evenamongpopulationsofgeneticallyidenticalcellsinuniformenvironmentalconditions.Markovprocessmodelsarisin
4、gfromthetheoryofstochasticchemicalkineticsareoftenusedtounderstandthegeneticregulationofthebehaviourofindividualbacterialcells.However,suchmodelsoftencontainuncertainparameterswhichneedtobeestimatedfromexperimentaldata.Parameterestimationforcomplexhigh‐dimen
5、sionalMarkovprocessmodelsusingdiverse,partial,noisyandpoorlycalibratedtime‐courseexperimentaldataisachallenginginferentialproblem,butacomputationallyintensiveBayesianapproachturnsouttobeeffective.Theutilityandadded‐valueoftheapproachisdemonstratedinthecontex
6、tofastochasticmodelofakeycellulardecisionmadebythegram‐positivebacteriumBacillussubtilis,usingquantitativedatafromsingle‐cellPage1of32ParameterInferenceforStochasticKineticModelsofBacterialGeneRegulation:ABayesianApproachtoSystemsBiologyfluorescencemicroscop
7、yandflowcytometryexperiments.Keywords:Bacillussubtilus,GeneticRegulation,GFP,Likelihood-freeMCMC,Motility,Time-lapseFluorescenceMicroscopySummaryBacteriaaresingle‐celledorganismswhichoftendisplayheterogeneousbehaviour,evenamongpopulationsofgeneticallyidentic
8、alcellsinuniformenvironmentalconditions.Markovprocessmodelsarisingfromthetheoryofstochasticchemicalkineticsareoftenusedtounderstandthegeneticregulationofthebehaviourofindividualbacterialcells.Ho
