{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T06:50:01Z","timestamp":1772520601129,"version":"3.50.1"},"reference-count":33,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2020,8,10]],"date-time":"2020-08-10T00:00:00Z","timestamp":1597017600000},"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\/501100001659","name":"German Research Foundation","doi-asserted-by":"crossref","award":["CRC 1076"],"award-info":[{"award-number":["CRC 1076"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100004807","name":"DFG","doi-asserted-by":"publisher","award":["SPP 1596"],"award-info":[{"award-number":["SPP 1596"]}],"id":[{"id":"10.13039\/100004807","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100004807","name":"DFG","doi-asserted-by":"publisher","award":["MA 5082\/7-1"],"award-info":[{"award-number":["MA 5082\/7-1"]}],"id":[{"id":"10.13039\/100004807","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,4,20]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>Zoonosis, the natural transmission of infections from animals to humans, is a far-reaching global problem. The recent outbreaks of Zikavirus, Ebolavirus and Coronavirus are examples of viral zoonosis, which occur more frequently due to globalization. In case of a virus outbreak, it is helpful to know which host organism was the original carrier of the virus to prevent further spreading of viral infection. Recent approaches aim to predict a viral host based on the viral genome, often in combination with the potential host genome and arbitrarily selected features. These methods are limited in the number of different hosts they can predict or the accuracy of the prediction.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Here, we present a fast and accurate deep learning approach for viral host prediction, which is based on the viral genome sequence only. We tested our deep neural network (DNN) on three different virus species (influenza A virus, rabies lyssavirus and rotavirus A). We achieved for each virus species an AUC between 0.93 and 0.98, allowing highly accurate predictions while using only fractions (100\u2013400\u2009bp) of the viral genome sequences. We show that deep neural networks are suitable to predict the host of a virus, even with a limited amount of sequences and highly unbalanced available data. The trained DNNs are the core of our virus\u2013host prediction tool VIrus Deep learning HOst Prediction (VIDHOP). VIDHOP also allows the user to train and use models for other viruses.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>VIDHOP is freely available under https:\/\/github.com\/flomock\/vidhop.<\/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\/btaa705","type":"journal-article","created":{"date-parts":[[2020,8,3]],"date-time":"2020-08-03T15:17:38Z","timestamp":1596467858000},"page":"318-325","source":"Crossref","is-referenced-by-count":61,"title":["VIDHOP, viral host prediction with deep learning"],"prefix":"10.1093","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1791-4437","authenticated-orcid":false,"given":"Florian","family":"Mock","sequence":"first","affiliation":[{"name":"RNA Bioinformatics\/High Throughput Analysis, Faculty of Mathematics and Computer Science , Jena 07743, Germany"}]},{"given":"Adrian","family":"Viehweger","sequence":"additional","affiliation":[{"name":"RNA Bioinformatics\/High Throughput Analysis, Faculty of Mathematics and Computer Science , Jena 07743, Germany"}]},{"given":"Emanuel","family":"Barth","sequence":"additional","affiliation":[{"name":"Bioinformatics Core Facility Jena, Friedrich Schiller University Jena , Jena 07743, Germany"}]},{"given":"Manja","family":"Marz","sequence":"additional","affiliation":[{"name":"RNA Bioinformatics\/High Throughput Analysis, Faculty of Mathematics and Computer Science , Jena 07743, Germany"},{"name":"RNA Bioinformatics\/High Throughput Analysis, Leibnitz Institute for Age Research \u2013 Fritz Lipmann Institute (FLI) , Jena 07743, Germany"},{"name":"RNA Bioinformatics\/High Throughput Analysis, German Center for Integrative Biodiversity Research (iDiv) , Halle-Jena-Leipzig 04103, Germany"},{"name":"RNA Bioinformatics\/High Throughput Analysis, European Virus Bioinformatics Center (EVBC) , Jena 07743, Germany"}]}],"member":"286","published-online":{"date-parts":[[2020,8,10]]},"reference":[{"key":"2023051604082390000_btaa705-B1","first-page":"265","author":"ABADI","year":"2016"},{"key":"2023051604082390000_btaa705-B2","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1093\/nar\/gkw1002","article-title":"Alignment-free d2* oligonucleotide frequency dissimilarity measure improves prediction of hosts from metagenomically-derived viral sequences","volume":"45","author":"Ahlgren","year":"2017","journal-title":"Nucleic Acids Res"},{"key":"2023051604082390000_btaa705-B3","doi-asserted-by":"publisher","first-page":"3159","DOI":"10.1609\/aaai.v33i01.33013159","article-title":"Character-Level Language Modeling with Deeper Self-Attention","volume":"33","author":"Al-Rfou","year":"2019","journal-title":"Proceedings of the AAAI Conference on Artificial Intelligence"},{"key":"2023051604082390000_btaa705-B4","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1038\/msb.2009.71","article-title":"Viral adaptation to host: a proteome-based analysis of codon usage and amino acid preferences","volume":"5","author":"Bahir","year":"2009","journal-title":"Mol. 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