Skip Navigation



Bioinformatics Advance Access published online on April 28, 2008
Bioinformatics, doi:10.1093/bioinformatics/btn199
This Article
Right arrow Advance Access manuscript (PDF) Freely available
Right arrow Supplementary Data
Right arrow All Versions of this Article:
24/12/1459    most recent
btn199v1
Right arrow Comments: Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when Comments are posted
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Sweredoski, M. J.
Right arrow Articles by Baldi, P.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Sweredoski, M. J.
Right arrow Articles by Baldi, P.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author (2008). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

PEPITO: Improved Discontinuous B-Cell Epitope Prediction Using Multiple Distance Thresholds and Half Sphere Exposure

Michael J. Sweredoski 1,2 and Pierre Baldi 1,2,*

1Department of Computer Science 2Institute for Genomics and Bioinformatics

*To whom correspondence should be addressed. Prof. Pierre Baldi, E-mail: pfbaldi{at}ics.uci.edu


  Abstract

Motivation: Accurate prediction of B-cell epitopes is an important goal of computational immunology. Up to 90% of B-cell epitopes are discontinuous in nature, yet most predictors focus on linear epitopes. Even whenith the tertiary structure of the antigen is available, the accurate prediction of B-cell epitopes remains challenging.

Results: Our predictor, PEPITO, uses a combination of amino acid propensity scores and half sphere exposure values at multiple distances to achieve state-of-the-art performance. PEPITO achieves an Area Under the Curve (AUC) of 75.4 on the Discotope dataset. Additionally, we benchmark PEPITO as well as the Discotope predictor on the more recent Epitome datasaset, achieving AUCs of 68.3 and 66.0 respectively.

Availability: PEPITO is available as part of the SCRATCH suite of protein structure predictors via www.igb.uci.edu

Associate Editor: Prof. Anna Tramontano

Received on March 3, 2008; revised on April 18, 2008; accepted on April 20, 2008

Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 Nucleic Acids ResHome page
J. Sun, D. Wu, T. Xu, X. Wang, X. Xu, L. Tao, Y. X. Li, and Z. W. Cao
SEPPA: a computational server for spatial epitope prediction of protein antigens
Nucleic Acids Res., July 1, 2009; 37(suppl_2): W612 - W616.
[Abstract] [Full Text] [PDF]

Home page
 Protein Eng Des SelHome page
M. J. Sweredoski and P. Baldi
COBEpro: a novel system for predicting continuous B-cell epitopes
Protein Eng. Des. Sel., March 1, 2009; 22(3): 113 - 120.
[Abstract] [Full Text] [PDF]


Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.