A gene selection algorithm using Bayesian classification approach

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Title A gene selection algorithm using Bayesian classification approach
Author Sharma, Alok; Paliwal, Kuldip Kumar
Journal Name American Journal of Applied Sciences
Year Published 2012
Place of publication United States
Publisher Science Publications
Abstract In this study, we propose a new feature (or gene) selection algorithm using Bayes classification approach. The algorithm can find gene subset crucial for cancer classification problem. Problem statement: Gene identification plays important role in human cancer classification problem. Several feature selection algorithms have been proposed for analyzing and understanding influential genes using gene expression profiles. Approach: The feature selection algorithms aim to explore genes that are crucial for accurate cancer classification and also endure biological significance. However, the performance of the algorithms is still limited. In this study, we propose a feature selection algorithm using Bayesian classification approach. Results: This approach gives promising results on gene expression datasets and compares favorably with respect to several other existing techniques. Conclusion: The proposed gene selection algorithm using Bayes classification approach is shown to find important
Peer Reviewed Yes
Published Yes
Publisher URI http://www.doaj.org/doaj?func=abstract&id=1138999&q1=A%20gene%20selection%20algorithm%20using%20Bayesian%20classification&f1=ti&b1=and&q2=&f2=all&recNo=1&uiLanguage=en
Volume 9
Issue Number 1
Page from 127
Page to 131
ISSN 1546-9239
Date Accessioned 2012-05-31
Date Available 2013-06-03T01:25:08Z
Language en_US
Research Centre Institute for Integrated and Intelligent Systems
Faculty Faculty of Science, Environment, Engineering and Technology
Subject Signal Processing
URI http://hdl.handle.net/10072/47190
Publication Type Journal Articles (Refereed Article)
Publication Type Code c1

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