Cart (Loading....) | Create Account
Close category search window
 

Data Mining Based on Colon Cancer Gene Expression Profiles

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

2 Author(s)

This research is based on biological information theory. In order to study the selection of colon cancer samples in normal samples and the classification of information gene, the use of pattern recognition and data mining methods were applied to analyze gene expression data for colon cancer. Firstly, signal to noise ratio (SNR) and the Bhattacharyya distance (BHA) were used to remove the irrelevant genes and noise, on the basis of deletion by mistake. After that, 100 information genes could be obtained respectively. Secondly, we calculate the union set of the 200 information genes called union C, and 102 information genes left. Thirdly, the minimum redundancy maximum relevance (MRMR) method was used to search for the information gene set in the union C. Finally, support vector machine (SVM) was used as the classifier to identify normal samples from colon cancer samples and 12 information genes were extracted based on the average classification rate. Several random sampling results showed that 12 information gene extracted in the study can classify normal samples and colon cancer samples at a high correct rate of 93.70%.

Published in:

Computational and Information Sciences (ICCIS), 2011 International Conference on

Date of Conference:

21-23 Oct. 2011

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.