Comparing the performance of a reversible jump Markov chain Monte Carlo algorithm for DNA sequences alignment

dc.creatorAlvarez, LJ
dc.creatorGarcia, NL
dc.creatorRodrigues, ER
dc.date2006
dc.dateJUL
dc.date2014-11-17T00:39:04Z
dc.date2015-11-26T16:33:18Z
dc.date2014-11-17T00:39:04Z
dc.date2015-11-26T16:33:18Z
dc.date.accessioned2018-03-28T23:15:07Z
dc.date.available2018-03-28T23:15:07Z
dc.identifierJournal Of Statistical Computation And Simulation. Taylor & Francis Ltd, v. 76, n. 7, n. 567, n. 584, 2006.
dc.identifier0094-9655
dc.identifierWOS:000237679800001
dc.identifier10.1080/10629360500109226
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/56195
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/56195
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/56195
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1270809
dc.descriptionAssume that K independent copies are made from a common prototype DNA sequence whose length is a random variable. In this paper, the problem of aligning those copies and therefore the problem of estimating the prototype sequence that produced the copies is addressed. A hidden Markov chain is used to model the copying procedure, and a reversible jump Markov chain Monte Carlo algorithm is used to sample the parameters of the model from their posterior distribution. Using the sample obtained, the Bayesian model and the prototype sequence may be selected using the maximum a posteriori estimate. A prior distribution for the prototype DNA sequence that incorporates a correlation among neighbouring bases is also considered. In addition, an analysis of the performance of the algorithm is presented when different scenarios are taken into account.
dc.description76
dc.description7
dc.description567
dc.description584
dc.languageen
dc.publisherTaylor & Francis Ltd
dc.publisherAbingdon
dc.publisherInglaterra
dc.relationJournal Of Statistical Computation And Simulation
dc.relationJ. Stat. Comput. Simul.
dc.rightsfechado
dc.rightshttp://journalauthors.tandf.co.uk/permissions/reusingOwnWork.asp
dc.sourceWeb of Science
dc.subjectBayesian inference
dc.subjectsequences alignment
dc.subjectreversible jump Markov chain Monte Carlo method
dc.subjecthidden Markov model
dc.subjectPotts model
dc.subjectMaximum-likelihood Alignment
dc.subjectConvergence Assessment
dc.subjectModel
dc.subjectRestoration
dc.subjectImages
dc.titleComparing the performance of a reversible jump Markov chain Monte Carlo algorithm for DNA sequences alignment
dc.typeArtículos de revistas


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