{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T20:34:03Z","timestamp":1772138043943,"version":"3.50.1"},"reference-count":25,"publisher":"Oxford University Press (OUP)","issue":"19","license":[{"start":{"date-parts":[[2021,3,11]],"date-time":"2021-03-11T00:00:00Z","timestamp":1615420800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01CA218094"],"award-info":[{"award-number":["R01CA218094"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["P30CA14051"],"award-info":[{"award-number":["P30CA14051"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,10,11]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Summary<\/jats:title>\n                    <jats:p>T cells play a critical role in cellular immune responses to pathogens and cancer and can be activated and expanded by Major Histocompatibility Complex (MHC)-presented antigens contained in peptide vaccines. We present a machine learning method to optimize the presentation of peptides by class II MHCs by modifying their anchor residues. Our method first learns a model of peptide affinity for a class II MHC using an ensemble of deep residual networks, and then uses the model to propose anchor residue changes to improve peptide affinity. We use a high throughput yeast display assay to show that anchor residue optimization improves peptide binding.<\/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\/btab131","type":"journal-article","created":{"date-parts":[[2021,3,9]],"date-time":"2021-03-09T07:53:00Z","timestamp":1615276380000},"page":"3160-3167","source":"Crossref","is-referenced-by-count":12,"title":["Machine learning optimization of peptides for presentation by class II MHCs"],"prefix":"10.1093","volume":"37","author":[{"given":"Zheng","family":"Dai","sequence":"first","affiliation":[{"name":"Computer Science and Artificial Intelligence Laboratory, MIT , Cambridge, MA, USA"},{"name":"Department of Computer Science and Electrical Engineering, MIT , Cambridge, MA, USA"}]},{"given":"Brooke D","family":"Huisman","sequence":"additional","affiliation":[{"name":"Department of Biological Engineering, MIT , Cambridge, MA, USA"}]},{"given":"Haoyang","family":"Zeng","sequence":"additional","affiliation":[{"name":"Computer Science and Artificial Intelligence Laboratory, MIT , Cambridge, MA, USA"},{"name":"Department of Computer Science and Electrical Engineering, MIT , Cambridge, MA, USA"}]},{"given":"Brandon","family":"Carter","sequence":"additional","affiliation":[{"name":"Computer Science and Artificial Intelligence Laboratory, MIT , Cambridge, MA, USA"},{"name":"Department of Computer Science and Electrical Engineering, MIT , Cambridge, MA, USA"}]},{"given":"Siddhartha","family":"Jain","sequence":"additional","affiliation":[{"name":"Computer Science and Artificial Intelligence Laboratory, MIT , Cambridge, MA, USA"},{"name":"Department of Computer Science and Electrical Engineering, MIT , Cambridge, MA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2281-3518","authenticated-orcid":false,"given":"Michael E","family":"Birnbaum","sequence":"additional","affiliation":[{"name":"Department of Biological Engineering, MIT , Cambridge, MA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1709-4034","authenticated-orcid":false,"given":"David K","family":"Gifford","sequence":"additional","affiliation":[{"name":"Computer Science and Artificial Intelligence Laboratory, MIT , Cambridge, MA, USA"},{"name":"Department of Computer Science and Electrical Engineering, MIT , Cambridge, MA, USA"},{"name":"Department of Biological Engineering, MIT , Cambridge, MA, USA"}]}],"member":"286","published-online":{"date-parts":[[2021,3,11]]},"reference":[{"key":"2023051608262533500_btab131-B1","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1016\/j.immuni.2017.02.007","article-title":"Mass spectrometry profiling of HLA-associated peptidomes in mono-allelic cells enables more accurate epitope prediction","volume":"46","author":"Abelin","year":"2017","journal-title":"Immunity"},{"key":"2023051608262533500_btab131-B2","doi-asserted-by":"crossref","first-page":"766","DOI":"10.1016\/j.immuni.2019.08.012","article-title":"Defining HLA-II ligand processing and binding rules with mass spectrometry enhances cancer epitope prediction","volume":"51","author":"Abelin","year":"2019","journal-title":"Immunity"},{"key":"2023051608262533500_btab131-B3","doi-asserted-by":"crossref","first-page":"755","DOI":"10.1038\/nprot.2006.94","article-title":"Isolating and engineering human antibodies using yeast surface display","volume":"1","author":"Chao","year":"2006","journal-title":"Nat. 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