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

Protein crystallization prediction with a combined feature set

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)
Hui-Huang Hsu ; Dept. of Comput. Sci. & Inf. Eng., Tamkang Univ., Taipei ; Shiang-Ming Wang

Using X-ray crystallography to determine the 3D structure of a protein is a costly and time-consuming process. One of the major reasons is that the protein needs to be purified and crystallized first, and the failure rate of protein crystallization is quite high. Thus it is desired to use a computational method to predict protein crystallizability based on the primary structure information before the whole process starts. This can dramatically lower the average cost for protein structure determination. In this paper, we investigated the feature sets used in previous research. The support vector machine (SVM) was chosen as the predictor. Different weightings are set for the penalty parameters of the two classes to deal with the imbalanced data problem. As a result, a combined set of features is able to produce better results, especially on the specificity.

Published in:

Innovations in Information Technology, 2008. IIT 2008. International Conference on

Date of Conference:

16-18 Dec. 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.