{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,22]],"date-time":"2025-06-22T19:21:01Z","timestamp":1750620061977,"version":"3.37.3"},"reference-count":12,"publisher":"Oxford University Press (OUP)","issue":"23","license":[{"start":{"date-parts":[[2021,10,3]],"date-time":"2021-10-03T00:00:00Z","timestamp":1633219200000},"content-version":"vor","delay-in-days":1,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"European Union\u2019s Horizon 2020 research and innovation programme"},{"name":"Marie Sk\u0142odowska-Curie","award":["765158"],"award-info":[{"award-number":["765158"]}]},{"name":"Spanish Ministry for Science, Innovation and Universities","award":["PID2019-111364RB-I00"],"award-info":[{"award-number":["PID2019-111364RB-I00"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,12,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Summary<\/jats:title>\n                  <jats:p>The ability to unveil binding patterns in peptide sets has important applications in several biomedical areas, including the development of vaccines. We present an open-source tool, CNN-PepPred, that uses convolutional neural networks to discover such patterns, along with its application to peptide\u2013HLA class II binding prediction. The tool can be used locally on different operating systems, with CPUs or GPUs, to train, evaluate, apply and visualize models.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>CNN-PepPred is freely available as a Python tool with a detailed User\u2019s Guide at https:\/\/github.com\/ComputBiol-IBB\/CNN-PepPred. The site includes the peptide sets used in this study, extracted from IEDB (www.iedb.org).<\/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\/btab687","type":"journal-article","created":{"date-parts":[[2021,9,30]],"date-time":"2021-09-30T16:18:42Z","timestamp":1633018722000},"page":"4567-4568","source":"Crossref","is-referenced-by-count":9,"title":["CNN-PepPred: an open-source tool to create convolutional NN models for the discovery of patterns in peptide sets\u2014application to peptide\u2013MHC class II binding prediction"],"prefix":"10.1093","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6138-0612","authenticated-orcid":false,"given":"Valentin","family":"Junet","sequence":"first","affiliation":[{"name":"Anaxomics Biotech SL , Barcelona 08008, Spain"},{"name":"Institute of Biotechnology and Biomedicine, Universitat Aut\u00f2noma de Barcelona , Barcelona 08193, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9235-6730","authenticated-orcid":false,"given":"Xavier","family":"Daura","sequence":"additional","affiliation":[{"name":"Institute of Biotechnology and Biomedicine, Universitat Aut\u00f2noma de Barcelona , Barcelona 08193, Spain"},{"name":"Catalan Institution for Research and Advanced Studies (ICREA) , Barcelona 08010, Spain"},{"name":"Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN) , Madrid 28029, Spain"}]}],"member":"286","published-online":{"date-parts":[[2021,10,2]]},"reference":[{"key":"2023061310544984900_btab687-B1","doi-asserted-by":"crossref","first-page":"2459","DOI":"10.1074\/mcp.TIR119.001658","article-title":"NNAlign_MA; MHC peptidome deconvolution for accurate MHC binding motif characterization and improved T-cell epitope predictions","volume":"18","author":"Alvarez","year":"2019","journal-title":"Mol. Cell. Proteom"},{"key":"2023061310544984900_btab687-B2","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1007\/s00251-015-0873-y","article-title":"Accurate pan-specific prediction of peptide\u2013MHC class II binding affinity with improved binding core identification","volume":"67","author":"Andreatta","year":"2015","journal-title":"Immunogenetics"},{"key":"2023061310544984900_btab687-B3","doi-asserted-by":"crossref","first-page":"3105","DOI":"10.1074\/mcp.O115.052431","article-title":"Analysis of major histocompatibility complex (MHC) immunopeptidomes using mass spectrometry","volume":"14","author":"Caron","year":"2015","journal-title":"Mol. Cell. Proteom"},{"key":"2023061310544984900_btab687-B4","doi-asserted-by":"crossref","first-page":"1332","DOI":"10.1038\/s41587-019-0280-2","article-title":"Predicting HLA class II antigen presentation through integrated deep learning","volume":"37","author":"Chen","year":"2019","journal-title":"Nat. Biotechnol"},{"key":"2023061310544984900_btab687-B5","doi-asserted-by":"crossref","first-page":"10915","DOI":"10.1073\/pnas.89.22.10915","article-title":"Amino acid substitution matrices from protein blocks","volume":"89","author":"Henikoff","year":"1992","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"2023061310544984900_btab687-B6","doi-asserted-by":"crossref","first-page":"394","DOI":"10.1111\/imm.12889","article-title":"Improved methods for predicting peptide binding affinity to MHC class II molecules","volume":"154","author":"Jensen","year":"2018","journal-title":"Immunology"},{"key":"2023061310544984900_btab687-B7","doi-asserted-by":"crossref","first-page":"W344","DOI":"10.1093\/nar\/gkx276","article-title":"NNAlign: a platform to construct and evaluate artificial neural network models of receptor-ligand interactions","volume":"45","author":"Nielsen","year":"2017","journal-title":"Nucleic Acids Res"},{"key":"2023061310544984900_btab687-B8","doi-asserted-by":"crossref","first-page":"296","DOI":"10.1186\/1471-2105-10-296","article-title":"NN-align. An artificial neural network-based alignment algorithm for MHC class II peptide binding prediction","volume":"10","author":"Nielsen","year":"2009","journal-title":"BMC Bioinformatics"},{"key":"2023061310544984900_btab687-B9","doi-asserted-by":"crossref","first-page":"1283","DOI":"10.1038\/s41587-019-0289-6","article-title":"Robust prediction of HLA class II epitopes by deep motif deconvolution of immunopeptidomes","volume":"37","author":"Racle","year":"2019","journal-title":"Nat. Biotechnol"},{"key":"2023061310544984900_btab687-B10","doi-asserted-by":"crossref","first-page":"W449","DOI":"10.1093\/nar\/gkaa379","article-title":"NetMHCpan-4.1 and NetMHCIIpan-4.0: improved predictions of MHC antigen presentation by concurrent motif deconvolution and integration of MS MHC eluted ligand data","volume":"48","author":"Reynisson","year":"2020","journal-title":"Nucleic Acids Res"},{"key":"2023061310544984900_btab687-B11","doi-asserted-by":"crossref","first-page":"2272","DOI":"10.1093\/bioinformatics\/btz921","article-title":"Logomaker: beautiful sequence logos in Python","volume":"36","author":"Tareen","year":"2020","journal-title":"Bioinformatics"},{"key":"2023061310544984900_btab687-B12","doi-asserted-by":"crossref","first-page":"568","DOI":"10.1186\/1471-2105-11-568","article-title":"Peptide binding predictions for HLA DR, DP and DQ molecules","volume":"11","author":"Wang","year":"2010","journal-title":"BMC Bioinformatics"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btab687\/40593308\/btab687.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/37\/23\/4567\/50579623\/btab687.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/37\/23\/4567\/50579623\/btab687.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,13]],"date-time":"2023-06-13T10:55:53Z","timestamp":1686653753000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/37\/23\/4567\/6380549"}},"subtitle":[],"editor":[{"given":"Tobias","family":"Marschall","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2021,10,2]]},"references-count":12,"journal-issue":{"issue":"23","published-print":{"date-parts":[[2021,12,7]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btab687","relation":{},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"type":"print","value":"1367-4803"},{"type":"electronic","value":"1367-4811"}],"subject":[],"published-other":{"date-parts":[[2021,12,1]]},"published":{"date-parts":[[2021,10,2]]}}}