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FRED--a framework for T-cell epitope detection.
Feldhahn, Magdalena; Dönnes, Pierre; Thiel, Philipp; Kohlbacher, Oliver.
Afiliação
  • Feldhahn M; Division for Simulation of Biological Systems, WSI/ZBIT, University of Tübingen, Sand 14, D-72076 Tübingen, Germany. feldhahn@informatik.uni-tuebingen.de
Bioinformatics ; 25(20): 2758-9, 2009 Oct 15.
Article em En | MEDLINE | ID: mdl-19578173
UNLABELLED: 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.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Epitopos de Linfócito T / Biologia Computacional Tipo de estudo: Diagnostic_studies Idioma: En Revista: Bioinformatics Ano de publicação: 2009 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Epitopos de Linfócito T / Biologia Computacional Tipo de estudo: Diagnostic_studies Idioma: En Revista: Bioinformatics Ano de publicação: 2009 Tipo de documento: Article