ZCURVE_V: a new self-training system for recognizing protein-coding genes in viral and phage genomes
Identifieur interne : 001011 ( Pmc/Checkpoint ); précédent : 001010; suivant : 001012ZCURVE_V: a new self-training system for recognizing protein-coding genes in viral and phage genomes
Auteurs : Feng-Biao Guo ; Chun-Ting ZhangSource :
- BMC Bioinformatics [ 1471-2105 ] ; 2006.
Abstract
It necessary to use highly accurate and statistics-based systems for viral and phage genome annotations. The GeneMark systems for gene-finding in virus and phage genomes suffer from some basic drawbacks. This paper puts forward an alternative approach for viral and phage gene-finding to improve the quality of annotations, particularly for newly sequenced genomes.
The new system ZCURVE_V has been run for 979 viral and 212 phage genomes, respectively, and satisfactory results are obtained. To have a fair comparison with the currently available software of similar function, GeneMark, a total of 30 viral genomes that have not been annotated by GeneMark are selected to be tested. Consequently, the average specificity of both systems is well matched, however the average sensitivity of ZCURVE_V for smaller viral genomes (< 100 kb), which constitute the main parts of viral genomes sequenced so far, is higher than that of GeneMark. Additionally, for the genome of
ZCURVE_V may serve as a preferred gene-finding tool used for viral and phage genomes, especially for anonymous viral and phage genomes newly sequenced.
The online version of this article (doi:10.1186/1471-2105-7-9) contains supplementary material, which is available to authorized users.
Url:
DOI: 10.1186/1471-2105-7-9
PubMed: 16401352
PubMed Central: 1352377
Affiliations:
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">ZCURVE_V: a new self-training system for recognizing protein-coding genes in viral and phage genomes</title><author><name sortKey="Guo, Feng Biao" sort="Guo, Feng Biao" uniqKey="Guo F" first="Feng-Biao" last="Guo">Feng-Biao Guo</name><affiliation><nlm:aff id="Aff1"></nlm:aff></affiliation></author><author><name sortKey="Zhang, Chun Ting" sort="Zhang, Chun Ting" uniqKey="Zhang C" first="Chun-Ting" last="Zhang">Chun-Ting Zhang</name><affiliation><nlm:aff id="Aff1"></nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">16401352</idno><idno type="pmc">1352377</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1352377</idno><idno type="RBID">PMC:1352377</idno><idno type="doi">10.1186/1471-2105-7-9</idno><date when="2006">2006</date><idno type="wicri:Area/Pmc/Corpus">000272</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000272</idno><idno type="wicri:Area/Pmc/Curation">000272</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Curation">000272</idno><idno type="wicri:Area/Pmc/Checkpoint">001011</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Checkpoint">001011</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">ZCURVE_V: a new self-training system for recognizing protein-coding genes in viral and phage genomes</title><author><name sortKey="Guo, Feng Biao" sort="Guo, Feng Biao" uniqKey="Guo F" first="Feng-Biao" last="Guo">Feng-Biao Guo</name><affiliation><nlm:aff id="Aff1"></nlm:aff></affiliation></author><author><name sortKey="Zhang, Chun Ting" sort="Zhang, Chun Ting" uniqKey="Zhang C" first="Chun-Ting" last="Zhang">Chun-Ting Zhang</name><affiliation><nlm:aff id="Aff1"></nlm:aff></affiliation></author></analytic><series><title level="j">BMC Bioinformatics</title><idno type="eISSN">1471-2105</idno><imprint><date when="2006">2006</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec><title>Background</title><p>It necessary to use highly accurate and statistics-based systems for viral and phage genome annotations. The GeneMark systems for gene-finding in virus and phage genomes suffer from some basic drawbacks. This paper puts forward an alternative approach for viral and phage gene-finding to improve the quality of annotations, particularly for newly sequenced genomes.</p></sec><sec><title>Results</title><p>The new system ZCURVE_V has been run for 979 viral and 212 phage genomes, respectively, and satisfactory results are obtained. To have a fair comparison with the currently available software of similar function, GeneMark, a total of 30 viral genomes that have not been annotated by GeneMark are selected to be tested. Consequently, the average specificity of both systems is well matched, however the average sensitivity of ZCURVE_V for smaller viral genomes (< 100 kb), which constitute the main parts of viral genomes sequenced so far, is higher than that of GeneMark. Additionally, for the genome of <italic>Amsacta moorei</italic> entomopoxvirus, probably with the lowest genomic GC content among the sequenced organisms, the accuracy of ZCURVE_V is much better than that of GeneMark, because the later predicts hundreds of false-positive genes. ZCURVE_V is also used to analyze well-studied genomes, such as HIV-1, HBV and SARS-CoV. Accordingly, the performance of ZCURVE_V is generally better than that of GeneMark. Finally, ZCURVE_V may be downloaded and run locally, particularly facilitating its utilization, whereas GeneMark is not downloadable. Based on the above comparison, it is suggested that ZCURVE_V may serve as a preferred gene-finding tool for viral and phage genomes newly sequenced. However, it is also shown that the joint application of both systems, ZCURVE_V and GeneMark, leads to better gene-finding results. The system ZCURVE_V is freely available at: <ext-link ext-link-type="uri" xlink:href="http://tubic.tju.edu.cn/Zcurve_V/">http://tubic.tju.edu.cn/Zcurve_V/</ext-link>.</p></sec><sec><title>Conclusion</title><p>ZCURVE_V may serve as a preferred gene-finding tool used for viral and phage genomes, especially for anonymous viral and phage genomes newly sequenced.</p></sec><sec><title>Electronic supplementary material</title><p>The online version of this article (doi:10.1186/1471-2105-7-9) contains supplementary material, which is available to authorized users.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Besemer, J" uniqKey="Besemer J">J Besemer</name></author><author><name sortKey="Lomsadze, A" uniqKey="Lomsadze A">A Lomsadze</name></author><author><name sortKey="Borodovsky, M" uniqKey="Borodovsky M">M Borodovsky</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Salzberg, Sl" 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M" uniqKey="Czub M">M Czub</name></author><author><name sortKey="Drebot, M" uniqKey="Drebot M">M Drebot</name></author><author><name sortKey="Fernando, L" uniqKey="Fernando L">L Fernando</name></author><author><name sortKey="Flick, R" uniqKey="Flick R">R Flick</name></author><author><name sortKey="Garbutt, M" uniqKey="Garbutt M">M Garbutt</name></author><author><name sortKey="Gray, M" uniqKey="Gray M">M Gray</name></author><author><name sortKey="Grolla, A" uniqKey="Grolla A">A Grolla</name></author><author><name sortKey="Jones, S" uniqKey="Jones S">S Jones</name></author><author><name sortKey="Feldmann, H" uniqKey="Feldmann H">H Feldmann</name></author><author><name sortKey="Meyers, A" uniqKey="Meyers A">A Meyers</name></author><author><name sortKey="Kabani, A" uniqKey="Kabani A">A Kabani</name></author><author><name sortKey="Li, Y" uniqKey="Li Y">Y Li</name></author><author><name sortKey="Normand, S" uniqKey="Normand S">S Normand</name></author><author><name sortKey="Stroher, U" 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sortKey="Maglott, Dr" uniqKey="Maglott D">DR Maglott</name></author></analytic></biblStruct><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Trifonov, En" uniqKey="Trifonov E">EN Trifonov</name></author></analytic></biblStruct><biblStruct></biblStruct></listBibl></div1></back></TEI><pmc article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">BMC Bioinformatics</journal-id><journal-id journal-id-type="iso-abbrev">BMC Bioinformatics</journal-id><journal-title-group><journal-title>BMC Bioinformatics</journal-title></journal-title-group><issn pub-type="epub">1471-2105</issn><publisher><publisher-name>BioMed Central</publisher-name><publisher-loc>London</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">16401352</article-id><article-id pub-id-type="pmc">1352377</article-id><article-id pub-id-type="publisher-id">748</article-id><article-id pub-id-type="doi">10.1186/1471-2105-7-9</article-id><article-categories><subj-group subj-group-type="heading"><subject>Software</subject></subj-group></article-categories><title-group><article-title>ZCURVE_V: a new self-training system for recognizing protein-coding genes in viral and phage genomes</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Guo</surname><given-names>Feng-Biao</given-names></name><address><email>guofengbiao@eyou.com</email></address><xref ref-type="aff" rid="Aff1"></xref></contrib><contrib contrib-type="author" corresp="yes"><name><surname>Zhang</surname><given-names>Chun-Ting</given-names></name><address><email>ctzhang@tju.edu.cn</email></address><xref ref-type="aff" rid="Aff1"></xref></contrib><aff id="Aff1"><institution-wrap><institution-id institution-id-type="GRID">grid.33763.32</institution-id><institution-id institution-id-type="ISNI">0000000417612484</institution-id><institution>Department of Physics,</institution><institution>Tianjin University,</institution></institution-wrap>Tianjin, 300072 China</aff></contrib-group><pub-date pub-type="epub"><day>10</day><month>1</month><year>2006</year></pub-date><pub-date pub-type="pmc-release"><day>10</day><month>1</month><year>2006</year></pub-date><pub-date pub-type="collection"><year>2006</year></pub-date><volume>7</volume><elocation-id>9</elocation-id><history><date date-type="received"><day>20</day><month>7</month><year>2005</year></date><date date-type="accepted"><day>10</day><month>1</month><year>2006</year></date></history><permissions><copyright-statement>© Guo and Zhang; licensee BioMed Central Ltd. 2006</copyright-statement><license><license-p>This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.</license-p></license></permissions><abstract id="Abs1"><sec><title>Background</title><p>It necessary to use highly accurate and statistics-based systems for viral and phage genome annotations. The GeneMark systems for gene-finding in virus and phage genomes suffer from some basic drawbacks. This paper puts forward an alternative approach for viral and phage gene-finding to improve the quality of annotations, particularly for newly sequenced genomes.</p></sec><sec><title>Results</title><p>The new system ZCURVE_V has been run for 979 viral and 212 phage genomes, respectively, and satisfactory results are obtained. To have a fair comparison with the currently available software of similar function, GeneMark, a total of 30 viral genomes that have not been annotated by GeneMark are selected to be tested. Consequently, the average specificity of both systems is well matched, however the average sensitivity of ZCURVE_V for smaller viral genomes (< 100 kb), which constitute the main parts of viral genomes sequenced so far, is higher than that of GeneMark. Additionally, for the genome of <italic>Amsacta moorei</italic> entomopoxvirus, probably with the lowest genomic GC content among the sequenced organisms, the accuracy of ZCURVE_V is much better than that of GeneMark, because the later predicts hundreds of false-positive genes. ZCURVE_V is also used to analyze well-studied genomes, such as HIV-1, HBV and SARS-CoV. Accordingly, the performance of ZCURVE_V is generally better than that of GeneMark. Finally, ZCURVE_V may be downloaded and run locally, particularly facilitating its utilization, whereas GeneMark is not downloadable. Based on the above comparison, it is suggested that ZCURVE_V may serve as a preferred gene-finding tool for viral and phage genomes newly sequenced. However, it is also shown that the joint application of both systems, ZCURVE_V and GeneMark, leads to better gene-finding results. The system ZCURVE_V is freely available at: <ext-link ext-link-type="uri" xlink:href="http://tubic.tju.edu.cn/Zcurve_V/">http://tubic.tju.edu.cn/Zcurve_V/</ext-link>.</p></sec><sec><title>Conclusion</title><p>ZCURVE_V may serve as a preferred gene-finding tool used for viral and phage genomes, especially for anonymous viral and phage genomes newly sequenced.</p></sec><sec><title>Electronic supplementary material</title><p>The online version of this article (doi:10.1186/1471-2105-7-9) contains supplementary material, which is available to authorized users.</p></sec></abstract><kwd-group xml:lang="en"><title>Keywords</title><kwd>Viral Genome</kwd><kwd>Phage Genome</kwd><kwd>Joint Application</kwd><kwd>RefSeq Annotation</kwd><kwd>Cereal Yellow Dwarf Virus</kwd></kwd-group><custom-meta-group><custom-meta><meta-name>issue-copyright-statement</meta-name><meta-value>© The Author(s) 2006</meta-value></custom-meta></custom-meta-group></article-meta></front></pmc><affiliations><list></list><tree><noCountry><name sortKey="Guo, Feng Biao" sort="Guo, Feng Biao" uniqKey="Guo F" first="Feng-Biao" last="Guo">Feng-Biao Guo</name><name sortKey="Zhang, Chun Ting" sort="Zhang, Chun Ting" uniqKey="Zhang C" first="Chun-Ting" last="Zhang">Chun-Ting Zhang</name></noCountry></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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