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Inferring the hosts of coronavirus using dual statistical models based on nucleotide composition
Tang, Qin1,2; Song, Yulong1,2; Shi, Mijuan1; Cheng, Yingyin1; Zhang, Wanting1; Xia, Xiao-Qin1
2015-11-26
Source PublicationSCIENTIFIC REPORTS
ISSN2045-2322
Volume5Issue:1Pages:1-8
Abstract

Many coronaviruses are capable of interspecies transmission. Some of them have caused worldwide panic as emerging human pathogens in recent years, e.g., severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV). In order to assess their threat to humans, we explored to infer the potential hosts of coronaviruses using a dual-model approach based on nineteen parameters computed from spike genes of coronaviruses. Both the support vector machine (SVM) model and the Mahalanobis distance (MD) discriminant model achieved high accuracies in leave-one-out cross-validation of training data consisting of 730 representative coronaviruses (99.86% and 98.08% respectively). Predictions on 47 additional coronaviruses precisely conformed to conclusions or speculations by other researchers. Our approach is implemented as a web server that can be accessed at http://bioinfo.ihb.ac.cn/seq2hosts.

SubtypeArticle
DOI10.1038/srep17155
WOS HeadingsScience & Technology
Funding OrganizationChinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences
Indexed BySCI
Language英语
WOS Research AreaScience & Technology - Other Topics
WOS SubjectMultidisciplinary Sciences
WOS IDWOS:000365390700001
WOS KeywordRESPIRATORY SYNDROME CORONAVIRUS ; RECEPTOR-BINDING DOMAIN ; INFLUENZA-A VIRUSES ; CODON USAGE ; SARS CORONAVIRUS ; RNA VIRUSES ; PALM CIVET ; SEQUENCE ; GENOMES ; BETACORONAVIRUS
Funding OrganizationChinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences ; Chinese Academy of Sciences
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Document Type期刊论文
Identifierhttp://ir.ihb.ac.cn/handle/342005/27422
Collection水生生物分子与细胞生物学研究中心_期刊论文
Affiliation1.Chinese Acad Sci, Inst Hydrobiol, Ctr Mol & Cellular Biol Aquat Organisms, Wuhan 430072, Peoples R China
2.Univ Chinese Acad Sci, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Tang, Qin,Song, Yulong,Shi, Mijuan,et al. Inferring the hosts of coronavirus using dual statistical models based on nucleotide composition[J]. SCIENTIFIC REPORTS,2015,5(1):1-8.
APA Tang, Qin,Song, Yulong,Shi, Mijuan,Cheng, Yingyin,Zhang, Wanting,&Xia, Xiao-Qin.(2015).Inferring the hosts of coronavirus using dual statistical models based on nucleotide composition.SCIENTIFIC REPORTS,5(1),1-8.
MLA Tang, Qin,et al."Inferring the hosts of coronavirus using dual statistical models based on nucleotide composition".SCIENTIFIC REPORTS 5.1(2015):1-8.
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