Cargando…

FRED—a framework for T-cell epitope detection

Summary: Over the last decade, immunoinformatics has made significant progress. Computational approaches, in particular the prediction of T-cell epitopes using machine learning methods, are at the core of modern vaccine design. Large-scale analyses and the integration or comparison of different meth...

Descripción completa

Detalles Bibliográficos
Autores principales: Feldhahn, Magdalena, Dönnes, Pierre, Thiel, Philipp, Kohlbacher, Oliver
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2759545/
https://www.ncbi.nlm.nih.gov/pubmed/19578173
http://dx.doi.org/10.1093/bioinformatics/btp409
_version_ 1782172681927393280
author Feldhahn, Magdalena
Dönnes, Pierre
Thiel, Philipp
Kohlbacher, Oliver
author_facet Feldhahn, Magdalena
Dönnes, Pierre
Thiel, Philipp
Kohlbacher, Oliver
author_sort Feldhahn, Magdalena
collection PubMed
description Summary: Over the last decade, immunoinformatics has made significant progress. Computational approaches, in particular the prediction of T-cell epitopes using machine learning methods, are at the core of modern vaccine design. Large-scale analyses and the integration or comparison of different methods become increasingly important. We have developed FRED, an extendable, open source software framework for key tasks in immunoinformatics. In this, its first version, FRED offers easily accessible prediction methods for MHC binding and antigen processing as well as general infrastructure for the handling of antigen sequence data and epitopes. FRED is implemented in Python in a modular way and allows the integration of external methods. Availability: FRED is freely available for download at http://www-bs.informatik.uni-tuebingen.de/Software/FRED. Contact: feldhahn@informatik.uni-tuebingen.de
format Text
id pubmed-2759545
institution National Center for Biotechnology Information
language English
publishDate 2009
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-27595452009-10-15 FRED—a framework for T-cell epitope detection Feldhahn, Magdalena Dönnes, Pierre Thiel, Philipp Kohlbacher, Oliver Bioinformatics Applications Note Summary: Over the last decade, immunoinformatics has made significant progress. Computational approaches, in particular the prediction of T-cell epitopes using machine learning methods, are at the core of modern vaccine design. Large-scale analyses and the integration or comparison of different methods become increasingly important. We have developed FRED, an extendable, open source software framework for key tasks in immunoinformatics. In this, its first version, FRED offers easily accessible prediction methods for MHC binding and antigen processing as well as general infrastructure for the handling of antigen sequence data and epitopes. FRED is implemented in Python in a modular way and allows the integration of external methods. Availability: FRED is freely available for download at http://www-bs.informatik.uni-tuebingen.de/Software/FRED. Contact: feldhahn@informatik.uni-tuebingen.de Oxford University Press 2009-10-15 2009-07-06 /pmc/articles/PMC2759545/ /pubmed/19578173 http://dx.doi.org/10.1093/bioinformatics/btp409 Text en © 2009 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 Applications Note
Feldhahn, Magdalena
Dönnes, Pierre
Thiel, Philipp
Kohlbacher, Oliver
FRED—a framework for T-cell epitope detection
title FRED—a framework for T-cell epitope detection
title_full FRED—a framework for T-cell epitope detection
title_fullStr FRED—a framework for T-cell epitope detection
title_full_unstemmed FRED—a framework for T-cell epitope detection
title_short FRED—a framework for T-cell epitope detection
title_sort fred—a framework for t-cell epitope detection
topic Applications Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2759545/
https://www.ncbi.nlm.nih.gov/pubmed/19578173
http://dx.doi.org/10.1093/bioinformatics/btp409
work_keys_str_mv AT feldhahnmagdalena fredaframeworkfortcellepitopedetection
AT donnespierre fredaframeworkfortcellepitopedetection
AT thielphilipp fredaframeworkfortcellepitopedetection
AT kohlbacheroliver fredaframeworkfortcellepitopedetection