{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T10:08:16Z","timestamp":1784110096977,"version":"3.55.0"},"reference-count":38,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2021,9,22]],"date-time":"2021-09-22T00:00:00Z","timestamp":1632268800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"name":"Strategy Research Grant","award":["7005215"],"award-info":[{"award-number":["7005215"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,1,17]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Next-generation sequencing expands the known phage genomes rapidly. Unlike culture-based methods, the hosts of phages discovered from next-generation sequencing data remain uncharacterized. The high diversity of the phage genomes makes the host assignment task challenging. To solve the issue, we proposed a phage host prediction tool\u2014DeepHost. To encode the phage genomes into matrices, we design a genome encoding method that applied various spaced $k$-mer pairs to tolerate sequence variations, including insertion, deletions, and mutations. DeepHost applies a convolutional neural network to predict host taxonomies. DeepHost achieves the prediction accuracy of 96.05% at the genus level (72 taxonomies) and 90.78% at the species level (118 taxonomies), which outperforms the existing phage host prediction tools by 10.16\u201330.48% and achieves comparable results to BLAST. For the genomes without hits in BLAST, DeepHost obtains the accuracy of 38.00% at the genus level and 26.47% at the species level, making it suitable for genomes of less homologous sequences with the existing datasets. DeepHost is alignment-free, and it is faster than BLAST, especially for large datasets. DeepHost is available at https:\/\/github.com\/deepomicslab\/DeepHost.<\/jats:p>","DOI":"10.1093\/bib\/bbab385","type":"journal-article","created":{"date-parts":[[2021,9,8]],"date-time":"2021-09-08T11:20:51Z","timestamp":1631100051000},"source":"Crossref","is-referenced-by-count":54,"title":["DeepHost: phage host prediction with convolutional neural network"],"prefix":"10.1093","volume":"23","author":[{"given":"Wang","family":"Ruohan","sequence":"first","affiliation":[{"name":"Department of Computer Science at City University of Hong Kong"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhang","family":"Xianglilan","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wang","family":"Jianping","sequence":"additional","affiliation":[{"name":"Department of Computer Science at City University of Hong 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