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

Efficient mining from heterogeneous data sets for predicting protein-protein interactions

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

1 Author(s)
Mamitsuka, H. ; Inst. for Chem. Res., Kyoto Univ., Uji, Japan

One of the most important issues in current molecular biology is to build exact networks of protein-protein interactions from currently available biological knowledge and information. We describe and demonstrate the effectiveness of a method for the issue of predicting protein-protein interactions, using a stochastic model as model for combining the data of protein-protein interactions with existing knowledge of proteins. In this paper, we consider a classification of proteins as the knowledge, and in a normally available classification of proteins, a protein falls into multiple classes. Focusing on this property of protein classes, we use the class of proteins as a latent variable in the stochastic model and estimate the model parameters with both the interaction data and protein classes using time-efficient EM (Expectation-Maximization) algorithm. We evaluate the method with the experiment using actual protein-protein interactions and a classification of proteins, and experimental results have shown that the method significantly outperformed other methods tested in our experiments.

Published in:

Database and Expert Systems Applications, 2003. Proceedings. 14th International Workshop on

Date of Conference:

1-5 Sept. 2003

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.