<?xml version="1.0" encoding="utf-8"?>
<Journal>
<Journal-Info>
<name>International Journal of Pharma and Bio Sciences</name>
<website>ijpbs.net</website>
<email>editorijpbs@rediffmail.com (or) editorofijpbs@yahoo.com (or) prasmol@rediffmail.com</email>
</Journal-Info>
<article>
<article-id pub-id-type='other'>10.22376/ijpbs.2019.10.1.p1-12</article-id>
<issue_number>Volume 6 Issue 2</issue_number>
<issue_period>2015 (April - June)</issue_period>
<title>GENE SELECTION USING BACTERIAL FORAGING OPTIMIZATION </title>
<abstract>Microarray gene expression data can be analyzed for diagnosis of cancer and its stage. It usually concerns a very large number of variables relative to a small number of observations. This makes application of data mining techniques difficult and so to reduce the data dimensionality some pre-processing technique needs to be used. In this paper dataset used for analysis is about lung cancer consisting of 96 samples. Bacterial foraging optimization algorithm has been used in this paper for selecting relevant genes.The bacterial foraging optimization algorithm is an optimization technique which derives its idea from for aging behavior of Bacteria  lessThan i greaterThan E. coli lessThan /i greaterThan .It shows good performance by selecting less and relevant genes. </abstract>
<authors>SUNITA BENIWAL AND DHARMINDER KUMAR</authors>
<keywords>Microarray, Bacterial Foraging Optimization, Support vector machines.</keywords>
<pages>663-667</pages>
</article>
</Journal>
