{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T08:57:54Z","timestamp":1776329874698,"version":"3.50.1"},"reference-count":14,"publisher":"Oxford University Press (OUP)","issue":"7","license":[{"start":{"date-parts":[[2019,11,22]],"date-time":"2019-11-22T00:00:00Z","timestamp":1574380800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100010105","name":"Austrian Cancer Aid\/Tyrol","doi-asserted-by":"crossref","award":["17003"],"award-info":[{"award-number":["17003"]}],"id":[{"id":"10.13039\/501100010105","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100002428","name":"Austrian Science Fund","doi-asserted-by":"publisher","award":["T 974-B30"],"award-info":[{"award-number":["T 974-B30"]}],"id":[{"id":"10.13039\/501100002428","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100010663","name":"European Research Council","doi-asserted-by":"publisher","award":["786295"],"award-info":[{"award-number":["786295"]}],"id":[{"id":"10.13039\/100010663","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,4,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Summary<\/jats:title>\n                  <jats:p>Gene fusions can generate immunogenic neoantigens that mediate anticancer immune responses. However, their computational prediction from RNA sequencing (RNA-seq) data requires deep bioinformatics expertise to assembly a computational workflow covering the prediction of: fusion transcripts, their translated proteins and peptides, Human Leukocyte Antigen (HLA) types, and peptide-HLA binding affinity. Here, we present NeoFuse, a computational pipeline for the prediction of fusion neoantigens from tumor RNA-seq data. NeoFuse can be applied to cancer patients\u2019 RNA-seq data to identify fusion neoantigens that might expand the repertoire of suitable targets for immunotherapy.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>NeoFuse source code and documentation are available under GPLv3 license at https:\/\/icbi.i-med.ac.at\/NeoFuse\/.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Supplementary information<\/jats:title>\n                  <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btz879","type":"journal-article","created":{"date-parts":[[2019,11,21]],"date-time":"2019-11-21T12:11:30Z","timestamp":1574338290000},"page":"2260-2261","source":"Crossref","is-referenced-by-count":46,"title":["NeoFuse: predicting fusion neoantigens from RNA sequencing data"],"prefix":"10.1093","volume":"36","author":[{"given":"Georgios","family":"Fotakis","sequence":"first","affiliation":[{"name":"Biocenter, Institute of Bioinformatics, Medical University of Innsbruck , Innsbruck 6020, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dietmar","family":"Rieder","sequence":"additional","affiliation":[{"name":"Biocenter, Institute of Bioinformatics, Medical University of Innsbruck , Innsbruck 6020, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marlene","family":"Haider","sequence":"additional","affiliation":[{"name":"Biocenter, Institute of Bioinformatics, Medical University of Innsbruck , Innsbruck 6020, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zlatko","family":"Trajanoski","sequence":"additional","affiliation":[{"name":"Biocenter, Institute of Bioinformatics, Medical University of Innsbruck , Innsbruck 6020, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0712-4658","authenticated-orcid":false,"given":"Francesca","family":"Finotello","sequence":"additional","affiliation":[{"name":"Biocenter, Institute of Bioinformatics, Medical University of Innsbruck , Innsbruck 6020, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2019,11,22]]},"reference":[{"key":"2023062300071811000_btz879-B1","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1093\/bioinformatics\/bts635","article-title":"Star: ultrafast universal RNA-seq aligner","volume":"29","author":"Dobin","year":"2013","journal-title":"Bioinformatics"},{"key":"2023062300071811000_btz879-B2","doi-asserted-by":"crossref","first-page":"724","DOI":"10.1038\/s41576-019-0166-7","article-title":"Next- generation computational tools for interrogating cancer immunity","volume":"20","author":"Finotello","year":"2019","journal-title":"Nat. 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Genet"},{"key":"2023062300071811000_btz879-B3","first-page":"120295","article-title":"STAR-fusion: fast and accurate fusion transcript detection from RNA-seq","author":"Haas","year":"2017","journal-title":"BioRxiv"},{"key":"2023062300071811000_btz879-B114","doi-asserted-by":"crossref","first-page":"3360","DOI":"10.4049\/jimmunol.1700893","article-title":"NetMHCpan-4.0: improved peptide MHC class I interaction predictions integrating eluted ligand and peptide binding affinity data","volume":"199","author":"Jurtz","year":"2017","journal-title":"J Immunol"},{"key":"2023062300071811000_btz879-B4","doi-asserted-by":"crossref","first-page":"536","DOI":"10.1016\/j.it.2018.04.005","article-title":"Update on tumor neoantigens and their utility: why it is good to be different","volume":"39","author":"Lee","year":"2018","journal-title":"Trends Immunol"},{"key":"2023062300071811000_btz879-B5","doi-asserted-by":"crossref","first-page":"923","DOI":"10.1093\/bioinformatics\/btt656","article-title":"Featurecounts: an efficient general purpose program for assigning sequence reads to genomic features","volume":"30","author":"Liao","year":"2014","journal-title":"Bioinformatics"},{"key":"2023062300071811000_btz879-B6","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1016\/j.cels.2018.05.014","article-title":"Mhcflurry: open-source class I MHC binding affinity prediction","volume":"7","author":"O\u2019Donnell","year":"2018","journal-title":"Cell Syst"},{"key":"2023062300071811000_btz879-B7","doi-asserted-by":"crossref","first-page":"2198","DOI":"10.1038\/s41467-019-09940-1","article-title":"Functional linkage of gene fusions to cancer cell fitness assessed by pharmacological and CRISPR-Cas9 screening","volume":"10","author":"Picco","year":"2019","journal-title":"Nat. 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