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

A Wrapper Feature Selection Method Based on Simulated Annealing Algorithm for Prostate Protein Mass Spectrometry 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

2 Author(s)
Yifeng Li ; Sch. of Inf. Sci. & Technol., Inst. of Intell. Inf. Process., Jinan ; Yihui Liu

Protein mass spectrometry is an integration of mass spectrometry and biological chip techniques, and it shows great potential for exploration of biomarkers and diagnosis of diseases. But the curse of dimensionality inherently from mass spectrometry data makes the dimensionality reduction a necessary phase of proteomic pattern recognition before classification. This paper presents a simulated annealing algorithm to select discriminant feature subsets. Experiments indicate that this wrapper feature selection method performs well and outperforms the other reported methods.

Published in:

Computational Intelligence in Bioinformatics and Computational Biology, 2008. CIBCB '08. IEEE Symposium on

Date of Conference:

15-17 Sept. 2008

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.