DocumentCode
464224
Title
Markov Models to Classify M. tuberculosis Spoligotypes
Author
Valétudie, Georges ; Desachy, Jacky ; Sola, Christophe
Author_Institution
GRIMAAG, Univ. Antilles-Guyane, Pointe-a-Pitre
Volume
1
fYear
2007
fDate
21-23 May 2007
Firstpage
668
Lastpage
671
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;
fLanguage
English
Publisher
ieee
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
Type
conf
DOI
10.1109/AINAW.2007.229
Filename
4221134
Link To Document