Next Article in Journal
On the Numerical Solution of the Incompressible Navier-Stokes Equations in Primitive Variables Using Grid Generation Techniques
Previous Article in Journal
Formulas for the Exponential of a Semi Skew-Symmetric Matrix of Order 4
Article Menu

Article Versions

Export Article

Open AccessArticle
Math. Comput. Appl. 2009, 14(3), 241-251; doi:10.3390/mca14030241

Classification of Helicobacter Pylori according to National Strains using Bayesian Learning

Fatih University, Department of Computer Engineering, Istanbul, Turkey
*
Authors to whom correspondence should be addressed.
Published: 1 December 2009
Download PDF [663 KB, uploaded 30 March 2016]

Abstract

There is many studies about Helicobacter pylori genome and many instances of national strains are sequenced completely. To make a successful classification, the same functional portions have to be used a classifier like Bayesian Learning. Thus suitable genes will be used for classification since genes are portions that work functionally same. The cagA and vacA genes are selected for classification. cagA gene stands for ‘cytotoxin-associated protein A’ gene and vacA gene stands for ‘vacuolating cytotoxin precursor’ gene and these genes have a role of coding of these proteins. The reasons for selecting these genes are that these genes are the genes which affect the bacteria being a pathogen, Nucleotide numbers of these genes are higher than the most of other genes of bacteria, and these genes are the most popular genes of Helicobacter pylori. There are some instances of these genes which are classified with respect to national strains. The national strains are based on the nation of the host human. The cause of the difference on national strains is the difference of the cultural activities. If the national strain of a random Helicobacter pylori bacterium is known, the host human's nation can also be known approximately. The aim of this study is to classify Helicobacter pylori according to National strain using a well-know classification technique named Bayesian Learning.
Keywords: Helicobacter pylori; Bayesian Learning; National strain Helicobacter pylori; Bayesian Learning; National strain
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Karlık, B.; Avcı, A.; Yabanıgül, A.T. Classification of Helicobacter Pylori according to National Strains using Bayesian Learning. Math. Comput. Appl. 2009, 14, 241-251.

Show more citation formats Show less citations formats

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Math. Comput. Appl. EISSN 2297-8747 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top