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

Biclustering of Gene Expression Data Using Genetic Algorithm

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)
Chakraborty, A. ; Department of Computer Science & Engineering Indian Institute of Technology, Kharagpur-721302, India, Email: anupamc@iitkgp.ernet.in ; Maka, H.

The biclustering problem of gene expression data deals with finding a subset of genes which exhibit similar expression patterns along a subset of conditions. Most of the current algorithms use a statistically predefined threshold as an input parameter for biclustering. This threshold defines the maximum allowable dissimilarity between the cells of a bicluster and is very hard to determine beforehand. Hence we propose two genetic algorithms that embed greedy algorithm as local search procedure and find the best biclusters independent of this threshold score. We also establish that the HScore of a bicluster under the additive model approximately follows chi-square distribution. We found that these genetic algorithms outperformed other greedy algorithms on yeast and lymphoma datasets.

Published in:

Computational Intelligence in Bioinformatics and Computational Biology, 2005. CIBCB '05. Proceedings of the 2005 IEEE Symposium on

Date of Conference:

14-15 Nov. 2005

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.