Journal Article

FRED—a framework for T-cell epitope detection

Magdalena Feldhahn, Pierre Dönnes, Philipp Thiel and Oliver Kohlbacher

in Bioinformatics

Volume 25, issue 20, pages 2758-2759
Published in print October 2009 | ISSN: 1367-4803
Published online July 2009 | e-ISSN: 1460-2059 | DOI: http://dx.doi.org/10.1093/bioinformatics/btp409

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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

Journal Article.  1142 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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