Title | Epitopia: a web-server for predicting B-cell epitopes. |
Publication Type | Journal Article |
Year of Publication | 2009 |
Authors | Rubinstein ND, Mayrose I, Martz E, Pupko T |
Journal | BMC Bioinformatics |
Volume | 10 |
Pagination | 287 |
Date Published | 2009 |
ISSN | 1471-2105 |
Keywords | Algorithms, Artificial Intelligence, Computational Biology, Epitopes, B-Lymphocyte, Internet, Software |
Abstract | BACKGROUND: Detecting candidate B-cell epitopes in a protein is a basic and fundamental step in many immunological applications. Due to the impracticality of experimental approaches to systematically scan the entire protein, a computational tool that predicts the most probable epitope regions is desirable. RESULTS: The Epitopia server is a web-based tool that aims to predict immunogenic regions in either a protein three-dimensional structure or a linear sequence. Epitopia implements a machine-learning algorithm that was trained to discern antigenic features within a given protein. The Epitopia algorithm has been compared to other available epitope prediction tools and was found to have higher predictive power. A special emphasis was put on the development of a user-friendly graphical interface for displaying the results. CONCLUSION: Epitopia is a user-friendly web-server that predicts immunogenic regions for both a protein structure and a protein sequence. Its accuracy and functionality make it a highly useful tool. Epitopia is available at http://epitopia.tau.ac.il and includes extensive explanations and example predictions. |
DOI | 10.1186/1471-2105-10-287 |
Alternate Journal | BMC Bioinformatics |
PubMed ID | 19751513 |
Department of Microbiology