Title :
Markov Models to Classify M. tuberculosis Spoligotypes
Author :
Valétudie, Georges ; Desachy, Jacky ; Sola, Christophe
Author_Institution :
GRIMAAG, Univ. Antilles-Guyane, Pointe-a-Pitre
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.
Keywords :
DNA; Markov processes; biology computing; diseases; microorganisms; molecular biophysics; pattern classification; probability; DNA analysis technique; M. tuberculosis spoligotypes classification; Markov models; probability; Biological system modeling; Capacitive sensors; Context modeling; DNA; Genetics; Helium; Hidden Markov models; Probability; Robustness; Sequences;
Conference_Titel :
Advanced Information Networking and Applications Workshops, 2007, AINAW '07. 21st International Conference on
Conference_Location :
Niagara Falls, Ont.
Print_ISBN :
978-0-7695-2847-2
DOI :
10.1109/AINAW.2007.229