Name
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. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/AINAW.2007.229 | AINA Workshops (1) |
Keywords | Field | DocType |
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 | Markov process,Computer science,Robustness (computer science),Context model,Artificial intelligence,Classifier (linguistics),Binary number,Distributed computing,Sequential data,Pattern recognition,Markov model,Hidden Markov model,Machine learning | Conference |
ISBN | Citations | PageRank |
0-7695-2847-3 | 0 | 0.34 |
References | Authors | |
2 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Georges Valetudie | 1 | 0 | 0.68 |
| Jacky Desachy | 2 | 34 | 9.25 |
| Christophe Sola | 3 | 15 | 2.72 |