{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T21:02:59Z","timestamp":1776459779230,"version":"3.51.2"},"reference-count":29,"publisher":"Oxford University Press (OUP)","issue":"7","license":[{"start":{"date-parts":[[2018,8,31]],"date-time":"2018-08-31T00:00:00Z","timestamp":1535673600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/501100009708","name":"Novo Nordisk Foundation","doi-asserted-by":"crossref","award":["NNF17OC0027594"],"award-info":[{"award-number":["NNF17OC0027594"]}],"id":[{"id":"10.13039\/501100009708","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100009708","name":"Novo Nordisk Foundation","doi-asserted-by":"crossref","award":["NNF14CC0001 to SB"],"award-info":[{"award-number":["NNF14CC0001 to SB"]}],"id":[{"id":"10.13039\/501100009708","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100012774","name":"Innovation Fund Denmark","doi-asserted-by":"crossref","award":["5184-00102B to JMGI"],"award-info":[{"award-number":["5184-00102B to JMGI"]}],"id":[{"id":"10.13039\/100012774","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,4,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Understanding the specificity of protein receptor\u2013ligand interactions is pivotal for our comprehension of biological mechanisms and systems. Receptor protein families often have a certain level of sequence diversity that converges into fewer conserved protein structures, allowing the exertion of well-defined functions. T and B cell receptors of the immune system and protein kinases that control the dynamic behaviour and decision processes in eukaryotic cells by catalysing phosphorylation represent prime examples. Driven by the large sequence diversity, the receptors within such protein families are often found to share specificities although divergent at the sequence level. This observation has led to the notion that prediction models of such systems are most effectively handled in a receptor-specific manner.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>We show that this approach in many cases is suboptimal, and describe an alternative improved framework for generating models with pan-receptor-predictive power for receptor protein families. The framework is based on deep artificial neural networks and integrates information from individual receptors into a single pan-receptor model, leveraging information across multiple receptor-specific datasets allowing predictions of the receptor specificity for all members of a given protein family including those described by limited or no ligand data. The approach was applied to the protein kinase superfamily, leading to the method NetPhosPan. The method was extensively validated and benchmarked against state-of-the-art prediction methods and was found to have unprecedented performance in particularly for kinase domains characterized by limited or no experimental data.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>The method is freely available to non-commercial users and can be downloaded at http:\/\/www.cbs.dtu.dk\/services\/NetPhospan-1.0.<\/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\/bty715","type":"journal-article","created":{"date-parts":[[2018,8,17]],"date-time":"2018-08-17T19:34:40Z","timestamp":1534534480000},"page":"1098-1107","source":"Crossref","is-referenced-by-count":21,"title":["A generic deep convolutional neural network framework for prediction of receptor\u2013ligand interactions\u2014NetPhosPan: application to kinase phosphorylation prediction"],"prefix":"10.1093","volume":"35","author":[{"given":"Emilio","family":"Fenoy","sequence":"first","affiliation":[{"name":"Laboratorio de Bioinformatica, Instituto de Investigaciones Biotecnologicas, Universidad Nacional de San Martin, San Martin, B, HMP Buenos Aires, Argentina"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jose M G","family":"Izarzugaza","sequence":"additional","affiliation":[{"name":"Department of Bio and Health Informatics, Technical University of Denmark, Kongens Lyngby, Denmark"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vanessa","family":"Jurtz","sequence":"additional","affiliation":[{"name":"Department of Bio and Health Informatics, Technical University of Denmark, Kongens Lyngby, Denmark"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"S\u00f8ren","family":"Brunak","sequence":"additional","affiliation":[{"name":"Translational Disease Systems Biology Group, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Morten","family":"Nielsen","sequence":"additional","affiliation":[{"name":"Laboratorio de Bioinformatica, Instituto de Investigaciones Biotecnologicas, Universidad Nacional de San Martin, San Martin, B, HMP Buenos Aires, Argentina"},{"name":"Department of Bio and Health Informatics, Technical University of Denmark, Kongens Lyngby, Denmark"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2018,8,31]]},"reference":[{"key":"2023013107275088100_bty715-B1","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1007\/s00251-015-0873-y","article-title":"Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identification","volume":"67","author":"Andreatta","year":"2015","journal-title":"Immunogenetics"},{"key":"2023013107275088100_bty715-B2","author":"Al-Rfou","year":"2016"},{"key":"2023013107275088100_bty715-B3","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1093\/nar\/28.1.235","article-title":"The protein data bank","volume":"28","author":"Berman","year":"2000","journal-title":"Nucleic Acids Res"},{"key":"2023013107275088100_bty715-B4","doi-asserted-by":"crossref","first-page":"660","DOI":"10.1093\/bioinformatics\/16.7.660","article-title":"Visualizing large hierarchical clusters in hyperbolic space","volume":"16","author":"Bingham","year":"2000","journal-title":"Bioinformatics"},{"key":"2023013107275088100_bty715-B5","doi-asserted-by":"crossref","first-page":"1351","DOI":"10.1006\/jmbi.1999.3310","article-title":"Sequence- and structure-based prediction of eukaryotic protein phosphorylation sites","volume":"294","author":"Blom","year":"1999","journal-title":"J. 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