Repetitive element signature-based visualization, distance computation, and classification of 1766 microbial genomes

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dc.contributor.authorLee, Kang-Hoonko
dc.contributor.authorShin, Kyung-Seopko
dc.contributor.authorLim, Deborako
dc.contributor.authorKim, Woo-Chanko
dc.contributor.authorChung, Byung Changko
dc.contributor.authorHan, GyuBumko
dc.contributor.authorRoh, Jeongkyuko
dc.contributor.authorCho, Dong-Hoko
dc.contributor.authorCho, Kihoko
dc.date.accessioned2015-07-01T02:56:17Z-
dc.date.available2015-07-01T02:56:17Z-
dc.date.created2015-06-03-
dc.date.created2015-06-03-
dc.date.created2015-06-03-
dc.date.issued2015-07-
dc.identifier.citationGENOMICS, v.106, no.1, pp.30 - 42-
dc.identifier.issn0888-7543-
dc.identifier.urihttp://hdl.handle.net/10203/199617-
dc.description.abstractThe genomes of living organisms are populated with pleomorphic repetitive elements (REs) of varying densities. Our hypothesis that genomic RE landscapes are species/strain/individual-specific was implemented into the Genome Signature Imaging system to visualize and compute the RE-based signatures of any genome. Following the occurrence profiling of 5-nucleotide REs/words, the information from top-50 frequency words was transformed into a genome-specific signature and visualized as Genome Signature Images (GSIs), using a CMYK scheme. An algorithm for computing distances among GSIs was formulated using the GSIs' variables (word identity, frequency, and frequency order). The utility of the GSI-distance computation system was demonstrated with control genomes. GSI-based computation of genome-relatedness among 1766 microbes (117 archaea and 1649 bacteria) identified their clustering patterns; although the majority paralleled the established classification, some did not. The Genome Signature Imaging system, with its visualization and distance computation functions, enables genome-scale evolutionary studies involving numerous genomes with varying sizes. (C) 2015 Elsevier Inc. All rights reserved.-
dc.languageEnglish-
dc.publisherACADEMIC PRESS INC ELSEVIER SCIENCE-
dc.titleRepetitive element signature-based visualization, distance computation, and classification of 1766 microbial genomes-
dc.typeArticle-
dc.identifier.wosid000355674900005-
dc.identifier.scopusid2-s2.0-84930540255-
dc.type.rimsART-
dc.citation.volume106-
dc.citation.issue1-
dc.citation.beginningpage30-
dc.citation.endingpage42-
dc.citation.publicationnameGENOMICS-
dc.identifier.doi10.1016/j.ygeno.2015.04.004-
dc.contributor.localauthorCho, Dong-Ho-
dc.contributor.nonIdAuthorLee, Kang-Hoon-
dc.contributor.nonIdAuthorLim, Debora-
dc.contributor.nonIdAuthorRoh, Jeongkyu-
dc.contributor.nonIdAuthorCho, Kiho-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorRepetitive element-
dc.subject.keywordAuthorGenome signature-
dc.subject.keywordAuthorGenome visualization-
dc.subject.keywordAuthorGenome distance-
dc.subject.keywordAuthorGenome-scale classification-
dc.subject.keywordAuthorMicrobial genomes-
dc.subject.keywordPlusRIBOSOMAL-RNA GENE-
dc.subject.keywordPlusSQUARE HALOARCHAEON-
dc.subject.keywordPlusK-MERS-
dc.subject.keywordPlusSEQUENCES-
dc.subject.keywordPlusALIGNMENT-
dc.subject.keywordPlusIDENTIFICATION-
dc.subject.keywordPlusPHYLOGENY-
dc.subject.keywordPlusEVOLUTION-
dc.subject.keywordPlusBLAST-
dc.subject.keywordPlusTOOL-
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