By Topic

Prediction of Protein-Protein Interactions in Saccharomyces cerevisiae Based on Protein Secondary Structure

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)
Lu Cai ; Sch. of Math., Phys. & Biol. Eng., Inner Mongolia Univ. of Sci. & Technol., Baotou, China ; Zhiyong Pei ; Sheng Qin ; Xiujuan Zhao

Protein--protein interaction (PPI) is a major way for proteins to perform their biological functions. Due to the lack of the PPI experimental data, theoretical prediction seems important to understand protein functions. Up to now, there have been various computational methods as for how to predict PPI. This report, however, will present a novel approach to the prediction of PPI by analyzing protein secondary structures. In the model, a support vector machine (SVM) was trained through a positive data set and a negative data set, each of which contains 7,714 protein pairs involving 1,730 proteins. To select PPI pairs in the training negative data sets, a new parameter that describes protein interaction relative bias (PIRB) was introduced as a measure of PPI propensity. The prediction accuracy was 88.01% when the model was employed to predict PPI in Saccharomyces cerevisiae.

Published in:

Biomedical Engineering and Biotechnology (iCBEB), 2012 International Conference on

Date of Conference:

28-30 May 2012