Markov Models to Classify M. tuberculosis Spoligotypes
Advanced Information Networking and Applications Workshops, 2007, AINAW '07. 21st International Conference（2007）
Abstract
In this paper we use Markov Models to classify automatically spoligotypes. A spoligotype is a sequence of 43 binary values provided by a DNA analysis technique. These methods, robust and well adapted to sequential data, allow us to generate a model on the basis of probabilities, calculated directly on the observations. We use these techniques to create one classifier for each searched class.
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Key words
binary value,markov models,classify m. tuberculosis spoligotypes,dna analysis technique,markov model,sequences,markov processes,hidden markov models,capacitive sensors,robustness,genetics,dna analysis,probability,context modeling,helium,microorganisms,molecular biophysics,dna
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