Notification:
We are currently experiencing intermittent issues impacting performance. We apologize for the inconvenience.
By Topic

Identification of Salient Patterns for Classification of Gene Expression Data

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Gouchol Pok ; Dept. of Comput. Sci., Yanbian Univ. of Sci. & Technol., Yanji, China ; Guangri Quan ; Keun Ho Ryu

Identification of salient patterns for the classification of gene expression profiles is a useful step in examining the biological significance and correlation of genes with disease states. We propose a clustering-based approach in which feature selection is first carried out to identify influential genes and then salient patterns are determined to characterize each of the different classes. The proposed method has been tested with the complicated colon tumor data and the experimental results are evaluated in comparison with the published ones.

Published in:

Bioinformatics and Biomedical Engineering (iCBBE), 2010 4th International Conference on

Date of Conference:

18-20 June 2010