Inferring the hosts of coronavirus using dual statistical models based on nucleotide composition.
Identifieur interne : 001372 ( PubMed/Corpus ); précédent : 001371; suivant : 001373Inferring the hosts of coronavirus using dual statistical models based on nucleotide composition.
Auteurs : Qin Tang ; Yulong Song ; Mijuan Shi ; Yingyin Cheng ; Wanting Zhang ; Xiao-Qin XiaSource :
- Scientific reports [ 2045-2322 ] ; 2015.
English descriptors
- KwdEn :
- MESH :
- chemical , genetics : Nucleotides.
- genetics : Coronavirus.
- virology : Coronavirus Infections.
- Base Composition, Host-Pathogen Interactions, Humans, Models, Statistical, Reproducibility of Results, Support Vector Machine.
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.
DOI: 10.1038/srep17155
PubMed: 26607834
Links to Exploration step
pubmed:26607834Le document en format XML
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Cellular Biology of Aquatic Organisms, Institute of Hydrobiology, the Chinese Academy of Sciences, Wuhan 430072, China.</nlm:affiliation></affiliation></author><author><name sortKey="Cheng, Yingyin" sort="Cheng, Yingyin" uniqKey="Cheng Y" first="Yingyin" last="Cheng">Yingyin Cheng</name><affiliation><nlm:affiliation>Center for Molecular and Cellular Biology of Aquatic Organisms, Institute of Hydrobiology, the Chinese Academy of Sciences, Wuhan 430072, China.</nlm:affiliation></affiliation></author><author><name sortKey="Zhang, Wanting" sort="Zhang, Wanting" uniqKey="Zhang W" first="Wanting" last="Zhang">Wanting Zhang</name><affiliation><nlm:affiliation>Center for Molecular and Cellular Biology of Aquatic Organisms, Institute of Hydrobiology, the Chinese Academy of Sciences, Wuhan 430072, China.</nlm:affiliation></affiliation></author><author><name sortKey="Xia, Xiao Qin" sort="Xia, Xiao Qin" uniqKey="Xia X" first="Xiao-Qin" last="Xia">Xiao-Qin Xia</name><affiliation><nlm:affiliation>Center for Molecular and Cellular Biology of Aquatic Organisms, Institute of Hydrobiology, the Chinese Academy of Sciences, Wuhan 430072, China.</nlm:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2015">2015</date><idno type="RBID">pubmed:26607834</idno><idno type="pmid">26607834</idno><idno type="doi">10.1038/srep17155</idno><idno type="wicri:Area/PubMed/Corpus">001372</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">001372</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Inferring the hosts of coronavirus using dual statistical models based on nucleotide composition.</title><author><name sortKey="Tang, Qin" sort="Tang, Qin" uniqKey="Tang Q" first="Qin" last="Tang">Qin Tang</name><affiliation><nlm:affiliation>Center for Molecular and Cellular Biology of Aquatic Organisms, Institute of Hydrobiology, the Chinese Academy of Sciences, Wuhan 430072, China.</nlm:affiliation></affiliation></author><author><name sortKey="Song, Yulong" sort="Song, Yulong" uniqKey="Song Y" first="Yulong" last="Song">Yulong Song</name><affiliation><nlm:affiliation>Center for Molecular and Cellular Biology of Aquatic Organisms, Institute of Hydrobiology, the Chinese Academy of Sciences, Wuhan 430072, China.</nlm:affiliation></affiliation></author><author><name sortKey="Shi, Mijuan" sort="Shi, Mijuan" uniqKey="Shi M" first="Mijuan" last="Shi">Mijuan Shi</name><affiliation><nlm:affiliation>Center for Molecular and Cellular Biology of Aquatic Organisms, Institute of Hydrobiology, the Chinese Academy of Sciences, Wuhan 430072, China.</nlm:affiliation></affiliation></author><author><name sortKey="Cheng, Yingyin" sort="Cheng, Yingyin" uniqKey="Cheng Y" first="Yingyin" last="Cheng">Yingyin Cheng</name><affiliation><nlm:affiliation>Center for Molecular and Cellular Biology of Aquatic Organisms, Institute of Hydrobiology, the Chinese Academy of Sciences, Wuhan 430072, China.</nlm:affiliation></affiliation></author><author><name sortKey="Zhang, Wanting" sort="Zhang, Wanting" uniqKey="Zhang W" first="Wanting" last="Zhang">Wanting Zhang</name><affiliation><nlm:affiliation>Center for Molecular and Cellular Biology of Aquatic Organisms, Institute of Hydrobiology, the Chinese Academy of Sciences, Wuhan 430072, China.</nlm:affiliation></affiliation></author><author><name sortKey="Xia, Xiao Qin" sort="Xia, Xiao Qin" uniqKey="Xia X" first="Xiao-Qin" last="Xia">Xiao-Qin Xia</name><affiliation><nlm:affiliation>Center for Molecular and Cellular Biology of Aquatic Organisms, Institute of Hydrobiology, the Chinese Academy of Sciences, Wuhan 430072, China.</nlm:affiliation></affiliation></author></analytic><series><title level="j">Scientific reports</title><idno type="eISSN">2045-2322</idno><imprint><date when="2015" type="published">2015</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Base Composition</term><term>Coronavirus (genetics)</term><term>Coronavirus Infections (virology)</term><term>Host-Pathogen Interactions</term><term>Humans</term><term>Models, Statistical</term><term>Nucleotides (genetics)</term><term>Reproducibility of Results</term><term>Support Vector Machine</term></keywords><keywords scheme="MESH" type="chemical" qualifier="genetics" xml:lang="en"><term>Nucleotides</term></keywords><keywords scheme="MESH" qualifier="genetics" xml:lang="en"><term>Coronavirus</term></keywords><keywords scheme="MESH" qualifier="virology" xml:lang="en"><term>Coronavirus Infections</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Base Composition</term><term>Host-Pathogen Interactions</term><term>Humans</term><term>Models, Statistical</term><term>Reproducibility of Results</term><term>Support Vector Machine</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">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. </div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">26607834</PMID><DateCompleted><Year>2016</Year><Month>10</Month><Day>05</Day></DateCompleted><DateRevised><Year>2018</Year><Month>11</Month><Day>13</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">2045-2322</ISSN><JournalIssue CitedMedium="Internet"><Volume>5</Volume><PubDate><Year>2015</Year><Month>Nov</Month><Day>26</Day></PubDate></JournalIssue><Title>Scientific reports</Title><ISOAbbreviation>Sci Rep</ISOAbbreviation></Journal><ArticleTitle>Inferring the hosts of coronavirus using dual statistical models based on nucleotide composition.</ArticleTitle><Pagination><MedlinePgn>17155</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1038/srep17155</ELocationID><Abstract><AbstractText>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. </AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Tang</LastName><ForeName>Qin</ForeName><Initials>Q</Initials><AffiliationInfo><Affiliation>Center for Molecular and Cellular Biology of Aquatic Organisms, Institute of Hydrobiology, the Chinese Academy of Sciences, Wuhan 430072, China.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>University of Chinese Academy of Sciences, Beijing, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Song</LastName><ForeName>Yulong</ForeName><Initials>Y</Initials><AffiliationInfo><Affiliation>Center for Molecular and Cellular Biology of Aquatic Organisms, Institute of Hydrobiology, the Chinese Academy of Sciences, Wuhan 430072, China.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>University of Chinese Academy of Sciences, Beijing, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Shi</LastName><ForeName>Mijuan</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Center for Molecular and Cellular Biology of Aquatic Organisms, Institute of Hydrobiology, the Chinese Academy of Sciences, Wuhan 430072, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Cheng</LastName><ForeName>Yingyin</ForeName><Initials>Y</Initials><AffiliationInfo><Affiliation>Center for Molecular and Cellular Biology of Aquatic Organisms, Institute of Hydrobiology, the Chinese Academy of Sciences, Wuhan 430072, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Zhang</LastName><ForeName>Wanting</ForeName><Initials>W</Initials><AffiliationInfo><Affiliation>Center for Molecular and Cellular Biology of Aquatic Organisms, Institute of Hydrobiology, the Chinese Academy of Sciences, Wuhan 430072, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Xia</LastName><ForeName>Xiao-Qin</ForeName><Initials>XQ</Initials><AffiliationInfo><Affiliation>Center for Molecular and Cellular Biology of Aquatic Organisms, Institute of Hydrobiology, the Chinese Academy of Sciences, Wuhan 430072, China.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2015</Year><Month>11</Month><Day>26</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>Sci Rep</MedlineTA><NlmUniqueID>101563288</NlmUniqueID><ISSNLinking>2045-2322</ISSNLinking></MedlineJournalInfo><ChemicalList><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D009711">Nucleotides</NameOfSubstance></Chemical></ChemicalList><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D001482" MajorTopicYN="Y">Base 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