By Topic

Neural network-based analysis of DNA microarray 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

4 Author(s)
Patra, J.C. ; Sch. of Comput. Eng., Nanyang Technol. Univ. ; Lei Wang ; Ee Luang Ang ; Chaudhari, N.S.

The analysis of DNA microarray expression data has become an important subject in bioinformatics. Scientists have adopted different approaches to select the informative genes those can distinguish different types of cancers. In this paper, we show the use of a dimension reduction technique such as singular value decomposition (SVD) to capture the genes with similar patterns. We propose a novel method of selection of feature genes based on information loss using SVD. To assign the samples to known classes, we design a multi-layer perceptron-based classifier with reduced dimensional input vectors. We provide performance comparison between different selection methods in terms of classification rate

Published in:

Neural Networks, 2005. IJCNN '05. Proceedings. 2005 IEEE International Joint Conference on  (Volume:1 )

Date of Conference: