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EpiToolKit—a web server for computational immunomics

Predicting the T-cell-mediated immune response is an important task in vaccine design and thus one of the key problems in computational immunomics. Various methods have been developed during the last decade and are available online. We present EpiToolKit, a web server that has been specifically desi...

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Detalles Bibliográficos
Autores principales: Feldhahn, Magdalena, Thiel, Philipp, Schuler, Mathias M., Hillen, Nina, Stevanović, Stefan, Rammensee, Hans-Georg, Kohlbacher, Oliver
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2447732/
https://www.ncbi.nlm.nih.gov/pubmed/18440979
http://dx.doi.org/10.1093/nar/gkn229
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author Feldhahn, Magdalena
Thiel, Philipp
Schuler, Mathias M.
Hillen, Nina
Stevanović, Stefan
Rammensee, Hans-Georg
Kohlbacher, Oliver
author_facet Feldhahn, Magdalena
Thiel, Philipp
Schuler, Mathias M.
Hillen, Nina
Stevanović, Stefan
Rammensee, Hans-Georg
Kohlbacher, Oliver
author_sort Feldhahn, Magdalena
collection PubMed
description Predicting the T-cell-mediated immune response is an important task in vaccine design and thus one of the key problems in computational immunomics. Various methods have been developed during the last decade and are available online. We present EpiToolKit, a web server that has been specifically designed to offer a problem-solving environment for computational immunomics. EpiToolKit offers a variety of different prediction methods for major histocompatibility complex class I and II ligands as well as minor histocompatibility antigens. These predictions are embedded in a user-friendly interface allowing refining, editing and constraining the searches conveniently. We illustrate the value of the approach with a set of novel tumor-associated peptides. EpiToolKit is available online at www.epitoolkit.org.
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spelling pubmed-24477322008-07-09 EpiToolKit—a web server for computational immunomics Feldhahn, Magdalena Thiel, Philipp Schuler, Mathias M. Hillen, Nina Stevanović, Stefan Rammensee, Hans-Georg Kohlbacher, Oliver Nucleic Acids Res Articles Predicting the T-cell-mediated immune response is an important task in vaccine design and thus one of the key problems in computational immunomics. Various methods have been developed during the last decade and are available online. We present EpiToolKit, a web server that has been specifically designed to offer a problem-solving environment for computational immunomics. EpiToolKit offers a variety of different prediction methods for major histocompatibility complex class I and II ligands as well as minor histocompatibility antigens. These predictions are embedded in a user-friendly interface allowing refining, editing and constraining the searches conveniently. We illustrate the value of the approach with a set of novel tumor-associated peptides. EpiToolKit is available online at www.epitoolkit.org. Oxford University Press 2008-07-01 2008-04-24 /pmc/articles/PMC2447732/ /pubmed/18440979 http://dx.doi.org/10.1093/nar/gkn229 Text en © 2008 The Author(s) http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Articles
Feldhahn, Magdalena
Thiel, Philipp
Schuler, Mathias M.
Hillen, Nina
Stevanović, Stefan
Rammensee, Hans-Georg
Kohlbacher, Oliver
EpiToolKit—a web server for computational immunomics
title EpiToolKit—a web server for computational immunomics
title_full EpiToolKit—a web server for computational immunomics
title_fullStr EpiToolKit—a web server for computational immunomics
title_full_unstemmed EpiToolKit—a web server for computational immunomics
title_short EpiToolKit—a web server for computational immunomics
title_sort epitoolkit—a web server for computational immunomics
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2447732/
https://www.ncbi.nlm.nih.gov/pubmed/18440979
http://dx.doi.org/10.1093/nar/gkn229
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