{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,7,16]],"date-time":"2024-07-16T11:18:33Z","timestamp":1721128713717},"reference-count":14,"publisher":"Oxford University Press (OUP)","issue":"20","license":[{"start":{"date-parts":[[2016,10,2]],"date-time":"2016-10-02T00:00:00Z","timestamp":1475366400000},"content-version":"vor","delay-in-days":2645,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/2.0\/uk\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2009,10,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>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.<\/jats:p>\n               <jats:p>Availability: FRED is freely available for download at http:\/\/www-bs.informatik.uni-tuebingen.de\/Software\/FRED.<\/jats:p>\n               <jats:p>Contact: \u00a0feldhahn@informatik.uni-tuebingen.de<\/jats:p>","DOI":"10.1093\/bioinformatics\/btp409","type":"journal-article","created":{"date-parts":[[2009,7,5]],"date-time":"2009-07-05T00:13:38Z","timestamp":1246752818000},"page":"2758-2759","source":"Crossref","is-referenced-by-count":17,"title":["FRED\u2014a framework for T-cell epitope detection"],"prefix":"10.1093","volume":"25","author":[{"given":"Magdalena","family":"Feldhahn","sequence":"first","affiliation":[{"name":"1 Division for Simulation of Biological Systems, WSI\/ZBIT, University of T\u00fcbingen, Sand 14, D-72076 T\u00fcbingen, Germany and 2 Present address: Molecular Toxicology, Safety Assessment, AstraZeneca R&D, S-15185 S\u00f6dert\u00e4lje, Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pierre","family":"D\u00f6nnes","sequence":"additional","affiliation":[{"name":"1 Division for Simulation of Biological Systems, WSI\/ZBIT, University of T\u00fcbingen, Sand 14, D-72076 T\u00fcbingen, Germany and 2 Present address: Molecular Toxicology, Safety Assessment, AstraZeneca R&D, S-15185 S\u00f6dert\u00e4lje, Sweden"},{"name":"1 Division for Simulation of Biological Systems, WSI\/ZBIT, University of T\u00fcbingen, Sand 14, D-72076 T\u00fcbingen, Germany and 2 Present address: Molecular Toxicology, Safety Assessment, AstraZeneca R&D, S-15185 S\u00f6dert\u00e4lje, Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Philipp","family":"Thiel","sequence":"additional","affiliation":[{"name":"1 Division for Simulation of Biological Systems, WSI\/ZBIT, University of T\u00fcbingen, Sand 14, D-72076 T\u00fcbingen, Germany and 2 Present address: Molecular Toxicology, Safety Assessment, AstraZeneca R&D, S-15185 S\u00f6dert\u00e4lje, Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Oliver","family":"Kohlbacher","sequence":"additional","affiliation":[{"name":"1 Division for Simulation of Biological Systems, WSI\/ZBIT, University of T\u00fcbingen, Sand 14, D-72076 T\u00fcbingen, Germany and 2 Present address: Molecular Toxicology, Safety Assessment, AstraZeneca R&D, S-15185 S\u00f6dert\u00e4lje, Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2009,7,6]]},"reference":[{"key":"2023013112133153700_B1","doi-asserted-by":"crossref","first-page":"378","DOI":"10.1034\/j.1399-0039.2003.00112.x","article-title":"Sensitive quantitative predictions of peptide-MHC binding by a \u2018Query by Committee\u2019 artificial neural network approach","volume":"62","author":"Buus","year":"2003","journal-title":"Tissue Antigens"},{"key":"2023013112133153700_B2","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1111\/j.1399-0039.2007.00914.x","article-title":"The immunoinformatics of cancer immunotherapy","volume":"70","author":"DeLuca","year":"2007","journal-title":"Tissue Antigens"},{"key":"2023013112133153700_B3","doi-asserted-by":"crossref","first-page":"2132","DOI":"10.1110\/ps.051352405","article-title":"Integrated modeling of the major events in the MHC class I antigen processing pathway","volume":"14","author":"D\u00f6nnes","year":"2005","journal-title":"Protein Sci."},{"key":"2023013112133153700_B4","doi-asserted-by":"crossref","first-page":"W194","DOI":"10.1093\/nar\/gkl284","article-title":"SVMHC: a server for prediction of MHC-binding peptides","volume":"34","author":"D\u00f6nnes","year":"2006","journal-title":"Nucleic Acids Res."},{"key":"2023013112133153700_B5","doi-asserted-by":"crossref","first-page":"6813","DOI":"10.4049\/jimmunol.173.11.6813","article-title":"Transporter associated with antigen processing preselection of peptides binding to the MHC: a bioinformatic evaluation","volume":"173","author":"Doytchinova","year":"2004","journal-title":"J. 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