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

Identification of 5' Pre-miRNAs and 3' Pre-miRNAs Employing Support Vector Machine and Local Structure Units

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)
Weibo Jin ; Coll. of Life Sci., Northwest A&F Univ., Yangling ; Dong Kong ; Fangli Wu ; Aiguang Guo

MicroKNAs (miRNA) are essential 21-22 nucleotides regulatory RNAs produced from larger hairpin precursors (pre-miRNA), and regulate gene expression through mRNA degradation or translational inhibition. We applied functional strand support vector machine (FS-SVM), a new method for prediction of functional strand on the miRNA precursors, to classifying 5' and 3' pre-miRNAs and achieved about 94% accuracy on human or mouse data. The FS-SVM classifier built on human and mouse data can correctly identify up to 90.9% of the pre-miRNAs from primates, and up to about 89.0% of the pre-miRNAs from other mammals.

Published in:

Bioinformatics and Biomedical Engineering, 2007. ICBBE 2007. The 1st International Conference on

Date of Conference:

6-8 July 2007

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.