{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T16:02:12Z","timestamp":1775750532332,"version":"3.50.1"},"reference-count":69,"publisher":"Oxford University Press (OUP)","issue":"17","license":[{"start":{"date-parts":[[2021,3,3]],"date-time":"2021-03-03T00:00:00Z","timestamp":1614729600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research","award":["URF\/1\/3790-01-01"],"award-info":[{"award-number":["URF\/1\/3790-01-01"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,9,9]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>Infectious diseases caused by novel viruses have become a major public health concern. Rapid identification of virus\u2013host interactions can reveal mechanistic insights into infectious diseases and shed light on potential treatments. Current computational prediction methods for novel viruses are based mainly on protein sequences. However, it is not clear to what extent other important features, such as the symptoms caused by the viruses, could contribute to a predictor. Disease phenotypes (i.e. signs and symptoms) are readily accessible from clinical diagnosis and we hypothesize that they may act as a potential proxy and an additional source of information for the underlying molecular interactions between the pathogens and hosts.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We developed DeepViral, a deep learning based method that predicts protein\u2013protein interactions (PPI) between humans and viruses. Motivated by the potential utility of infectious disease phenotypes, we first embedded human proteins and viruses in a shared space using their associated phenotypes and functions, supported by formalized background knowledge from biomedical ontologies. By jointly learning from protein sequences and phenotype features, DeepViral significantly improves over existing sequence-based methods for intra- and inter-species PPI prediction.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>Code and datasets for reproduction and customization are available at https:\/\/github.com\/bio-ontology-research-group\/DeepViral. Prediction results for 14 virus families are available at https:\/\/doi.org\/10.5281\/zenodo.4429824.<\/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\/btab147","type":"journal-article","created":{"date-parts":[[2021,3,1]],"date-time":"2021-03-01T07:36:16Z","timestamp":1614584176000},"page":"2722-2729","source":"Crossref","is-referenced-by-count":60,"title":["DeepViral: prediction of novel virus\u2013host interactions from protein sequences and infectious disease phenotypes"],"prefix":"10.1093","volume":"37","author":[{"given":"Wang","family":"Liu-Wei","sequence":"first","affiliation":[{"name":"Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology , Thuwal 23955, Saudi Arabia"}]},{"given":"\u015eenay","family":"Kafkas","sequence":"additional","affiliation":[{"name":"Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology , Thuwal 23955, Saudi Arabia"},{"name":"Computational Bioscience Research Center, King Abdullah University of Science and Technology , Thuwal 23955, Saudi Arabia"}]},{"given":"Jun","family":"Chen","sequence":"additional","affiliation":[{"name":"Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology , Thuwal 23955, Saudi Arabia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3808-206X","authenticated-orcid":false,"given":"Nicholas J.","family":"Dimonaco","sequence":"additional","affiliation":[{"name":"Institute of Biological, Environmental and Rural Sciences, Aberystwyth University , Wales SY23 3BQ, UK"}]},{"given":"Jesper","family":"Tegn\u00e9r","sequence":"additional","affiliation":[{"name":"Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology , Thuwal 23955, Saudi Arabia"},{"name":"Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology , Thuwal 23955, Saudi Arabia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8149-5890","authenticated-orcid":false,"given":"Robert","family":"Hoehndorf","sequence":"additional","affiliation":[{"name":"Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology , Thuwal 23955, Saudi Arabia"},{"name":"Computational Bioscience Research Center, King Abdullah University of Science and Technology , Thuwal 23955, Saudi Arabia"}]}],"member":"286","published-online":{"date-parts":[[2021,3,3]]},"reference":[{"key":"2023051609220034700_btab147-B1","doi-asserted-by":"crossref","first-page":"1391265","DOI":"10.1155\/2018\/1391265","article-title":"Predicting interactions between virus and host proteins using repeat patterns and composition of amino acids","volume":"2018","author":"Alguwaizani","year":"2018","journal-title":"J. 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