ZCURVE_V: a new self-training system for recognizing protein-coding genes in viral and phage genomes
Identifieur interne : 001332 ( Ncbi/Merge ); précédent : 001331; suivant : 001333ZCURVE_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.
Descripteurs français
- KwdFr :
- Algorithmes, Bactériophages (génétique), Bases de données génétiques, Biologie informatique (), Cadres ouverts de lecture, Faux positifs, Génome, Génome bactérien, Génome viral, Interprétation statistique de données, Logiciel, Modèles statistiques, VIH-1 (Virus de l'Immunodéficience Humaine de type 1) (génétique), Virus de l'hépatite B (génétique).
- MESH :
- génétique : Bactériophages, VIH-1 (Virus de l'Immunodéficience Humaine de type 1), Virus de l'hépatite B.
- Algorithmes, Bases de données génétiques, Biologie informatique, Cadres ouverts de lecture, Faux positifs, Génome, Génome bactérien, Génome viral, Interprétation statistique de données, Logiciel, Modèles statistiques.
English descriptors
- KwdEn :
- MESH :
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
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PMC:1352377Le document en format XML
<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" 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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><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms</term><term>Bacteriophages (genetics)</term><term>Computational Biology (methods)</term><term>Data Interpretation, Statistical</term><term>Databases, Genetic</term><term>False Positive Reactions</term><term>Genome</term><term>Genome, Bacterial</term><term>Genome, Viral</term><term>HIV-1 (genetics)</term><term>Hepatitis B virus (genetics)</term><term>Models, Statistical</term><term>Open Reading Frames</term><term>Software</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Algorithmes</term><term>Bactériophages (génétique)</term><term>Bases de données génétiques</term><term>Biologie informatique ()</term><term>Cadres ouverts de lecture</term><term>Faux positifs</term><term>Génome</term><term>Génome bactérien</term><term>Génome viral</term><term>Interprétation statistique de données</term><term>Logiciel</term><term>Modèles statistiques</term><term>VIH-1 (Virus de l'Immunodéficience Humaine de type 1) (génétique)</term><term>Virus de l'hépatite B (génétique)</term></keywords><keywords scheme="MESH" qualifier="genetics" xml:lang="en"><term>Bacteriophages</term><term>HIV-1</term><term>Hepatitis B virus</term></keywords><keywords scheme="MESH" qualifier="génétique" xml:lang="fr"><term>Bactériophages</term><term>VIH-1 (Virus de l'Immunodéficience Humaine de type 1)</term><term>Virus de l'hépatite B</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Computational Biology</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Algorithms</term><term>Data Interpretation, Statistical</term><term>Databases, Genetic</term><term>False Positive Reactions</term><term>Genome</term><term>Genome, Bacterial</term><term>Genome, Viral</term><term>Models, Statistical</term><term>Open Reading Frames</term><term>Software</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Algorithmes</term><term>Bases de données génétiques</term><term>Biologie informatique</term><term>Cadres ouverts de lecture</term><term>Faux positifs</term><term>Génome</term><term>Génome bactérien</term><term>Génome viral</term><term>Interprétation statistique de données</term><term>Logiciel</term><term>Modèles statistiques</term></keywords></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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sortKey="Mchardy, Ac" uniqKey="Mchardy A">AC McHardy</name></author><author><name sortKey="Goesmann, A" uniqKey="Goesmann A">A Goesmann</name></author><author><name sortKey="Puhler, A" uniqKey="Puhler A">A Puhler</name></author><author><name sortKey="Meyer, F" uniqKey="Meyer F">F Meyer</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Benson, Da" uniqKey="Benson D">DA Benson</name></author><author><name sortKey="Karsch Mizrachi, I" uniqKey="Karsch Mizrachi I">I Karsch-Mizrachi</name></author><author><name sortKey="Lipman, Dj" uniqKey="Lipman D">DJ Lipman</name></author><author><name sortKey="Ostell, J" uniqKey="Ostell J">J Ostell</name></author><author><name sortKey="Wheeler, Dl" uniqKey="Wheeler D">DL Wheeler</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Pruitt, Kd" uniqKey="Pruitt K">KD Pruitt</name></author><author><name sortKey="Tatusova, T" uniqKey="Tatusova T">T Tatusova</name></author><author><name 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><double pmid="16401352"><pmc><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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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><pubmed><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 wicri:level="1"><nlm:affiliation>Department of Physics, Tianjin University, Tianjin 300072, China. guofengbiao@eyou.com</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Department of Physics, Tianjin University, Tianjin 300072</wicri:regionArea><placeName><settlement type="city">Tianjin</settlement></placeName></affiliation></author><author><name sortKey="Zhang, Chun Ting" sort="Zhang, Chun Ting" uniqKey="Zhang C" first="Chun-Ting" last="Zhang">Chun-Ting Zhang</name></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2006">2006</date><idno type="RBID">pubmed:16401352</idno><idno type="pmid">16401352</idno><idno type="doi">10.1186/1471-2105-7-9</idno><idno type="wicri:Area/PubMed/Corpus">002384</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">002384</idno><idno type="wicri:Area/PubMed/Curation">002384</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Curation">002384</idno><idno type="wicri:Area/PubMed/Checkpoint">001F22</idno><idno type="wicri:explorRef" wicri:stream="Checkpoint" wicri:step="PubMed">001F22</idno></publicationStmt><sourceDesc><biblStruct><analytic><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 wicri:level="1"><nlm:affiliation>Department of Physics, Tianjin University, Tianjin 300072, China. guofengbiao@eyou.com</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Department of Physics, Tianjin University, Tianjin 300072</wicri:regionArea><placeName><settlement type="city">Tianjin</settlement></placeName></affiliation></author><author><name sortKey="Zhang, Chun Ting" sort="Zhang, Chun Ting" uniqKey="Zhang C" first="Chun-Ting" last="Zhang">Chun-Ting Zhang</name></author></analytic><series><title level="j">BMC bioinformatics</title><idno type="eISSN">1471-2105</idno><imprint><date when="2006" type="published">2006</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms</term><term>Bacteriophages (genetics)</term><term>Computational Biology (methods)</term><term>Data Interpretation, Statistical</term><term>Databases, Genetic</term><term>False Positive Reactions</term><term>Genome</term><term>Genome, Bacterial</term><term>Genome, Viral</term><term>HIV-1 (genetics)</term><term>Hepatitis B virus (genetics)</term><term>Models, Statistical</term><term>Open Reading Frames</term><term>Software</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Algorithmes</term><term>Bactériophages (génétique)</term><term>Bases de données génétiques</term><term>Biologie informatique ()</term><term>Cadres ouverts de lecture</term><term>Faux positifs</term><term>Génome</term><term>Génome bactérien</term><term>Génome viral</term><term>Interprétation statistique de données</term><term>Logiciel</term><term>Modèles statistiques</term><term>VIH-1 (Virus de l'Immunodéficience Humaine de type 1) (génétique)</term><term>Virus de l'hépatite B (génétique)</term></keywords><keywords scheme="MESH" qualifier="genetics" xml:lang="en"><term>Bacteriophages</term><term>HIV-1</term><term>Hepatitis B virus</term></keywords><keywords scheme="MESH" qualifier="génétique" xml:lang="fr"><term>Bactériophages</term><term>VIH-1 (Virus de l'Immunodéficience Humaine de type 1)</term><term>Virus de l'hépatite B</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Computational Biology</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Algorithms</term><term>Data Interpretation, Statistical</term><term>Databases, Genetic</term><term>False Positive Reactions</term><term>Genome</term><term>Genome, Bacterial</term><term>Genome, Viral</term><term>Models, Statistical</term><term>Open Reading Frames</term><term>Software</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Algorithmes</term><term>Bases de données génétiques</term><term>Biologie informatique</term><term>Cadres ouverts de lecture</term><term>Faux positifs</term><term>Génome</term><term>Génome bactérien</term><term>Génome viral</term><term>Interprétation statistique de données</term><term>Logiciel</term><term>Modèles statistiques</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">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.</div></front></TEI></pubmed></double></record>Pour manipuler ce document sous Unix (Dilib)
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