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Bayesian classifiers for detecting HGT using fixed and variable order Markov models of genomic signatures
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- Dalevi, Daniel, 1974 (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Dubhashi, Devdatt, 1965 (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Hermansson, Malte, 1954 (author)
- Gothenburg University,Göteborgs universitet,Institutionen för cell- och molekylärbiologi,Department of Cell and Molecular Biology,University of Gothenburg
- (creator_code:org_t)
- 2006-01-10
- 2006
- English.
- In: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 22:5, s. 517-522
- Journal article (peer-reviewed)
Abstract
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- 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).
Subject headings
- NATURVETENSKAP -- Biologi -- Bioinformatik och systembiologi (hsv//swe)
- NATURAL SCIENCES -- Biological Sciences -- Bioinformatics and Systems Biology (hsv//eng)
- NATURVETENSKAP -- Biologi -- Annan biologi (hsv//swe)
- NATURAL SCIENCES -- Biological Sciences -- Other Biological Topics (hsv//eng)
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