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Träfflista för sökning "LAR1:gu ;mspu:(article);lar1:(cth);pers:(Hermansson Malte 1954);pers:(Dalevi Daniel 1974)"

Sökning: LAR1:gu > Tidskriftsartikel > Chalmers tekniska högskola > Hermansson Malte 1954 > Dalevi Daniel 1974

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1.
  • Dalevi, Daniel, 1974, et al. (författare)
  • A New Order Estimator for Fixed and Variable Length Markov Models with Applications to DNA Sequence Similarity
  • 2006
  • Ingår i: Statistical Applications in Genetics and Molecular Biology. - : Walter de Gruyter GmbH. - 1544-6115. ; 5:1, s. i-24
  • Tidskriftsartikel (refereegranskat)abstract
    • Recently Peres and Shields discovered a new method for estimating the order of a stationary fixed order Markov chain. They showed that the estimator is consistent by proving a threshold result. While this threshold is valid asymptotically in the limit, it is not very useful for DNA sequence analysis where data sizes are moderate. In this paper we give a novel interpretation of the Peres-Shields estimator as a sharp transition phenomenon. This yields a precise and powerful estimator that quickly identifies the core dependencies in data. We show that it compares favorably to other estimators, especially in the presence of variable dependencies. Motivated by this last point, we extend the Peres-Shields estimator to Variable Length Markov Chains. We compare it to a well-established estimator and show that it is superior in terms of the predictive likelihood. We give an application to the problem of detecting DNA sequence similarity in plasmids. Copyright ©2006 The Berkeley Electronic Press. All rights reserved.
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2.
  • Dalevi, Daniel, 1974, et al. (författare)
  • Bayesian classifiers for detecting HGT using fixed and variable order Markov models of genomic signatures
  • 2006
  • Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 22:5, s. 517-522
  • Tidskriftsartikel (refereegranskat)abstract
    • Analyses of genomic signatures are gaining attention as they allow studies of species-specific relationships without involving alignments of homologous sequences. A naïve Bayesian classifier was built to discriminate between different bacterial compositions of short oligomers, also known as DNA words. The classifier has proven successful in identifying foreign genes in Neisseria meningitis. In this study we extend the classifier approach using either a fixed higher order Markov model (Mk) or a variable length Markov model (VLMk).
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