Prediction of the disulphide bridges in proteins using SVM
by Aiguo Du, Xiaohua Hu, Yi Pan
International Journal of Bioinformatics Research and Applications (IJBRA), Vol. 3, No. 2, 2007

Abstract: Disulphide bonds link distant portions of protein chains and provide strong structural constraints in the form of long-range interactions. Prediction and knowledge of disulphide bond connectivity is important in reducing the search space of protein conformation. In this research, we present an effective way to predict disulphide bridges by Support Vector Machine (SVM). The SVM encoding was based on experimental results on the binding motifs of protein disulphide isomerases. The physical-chemical characteristics of the flanking sequences and the linear distance between the concerned cysteine pairs were also included in the encoding. An overall pair wise accuracy of 92% was obtained for the SP39 dataset.

Online publication date: Wed, 09-May-2007

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Bioinformatics Research and Applications (IJBRA):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com