Genomic tree of gene contents based on functional groups of KEGG orthology

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dc.contributor.authorKim, JSko
dc.contributor.authorLee, SangYupko
dc.date.accessioned2013-03-07T16:39:56Z-
dc.date.available2013-03-07T16:39:56Z-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.issued2006-05-
dc.identifier.citationJOURNAL OF MICROBIOLOGY AND BIOTECHNOLOGY, v.16, pp.748 - 756-
dc.identifier.issn1017-7825-
dc.identifier.urihttp://hdl.handle.net/10203/90702-
dc.description.abstractWe propose a genome-scale clustering approach to identify whole genome relationships using the functional groups given by the Kyoto Encyclopedia of Genes and Genomes Orthology (KO) database. The metabolic capabilities of each organism were defined by the number of genes in each functional category. The archaeal, bacterial, and eukaryotic genomes were compared by simultaneously applying a two-step clustering method, comprised of a self-organizing tree algorithm followed by unsupervised hierarchical clustering. The clustering results were consistent with various phenotypic characteristics of the organisms analyzed and, additionally, showed a different aspect of the relationship between genomes that have previously been established through rRNA-based comparisons. The proposed approach to collect and cluster the metabolic functional capabilities of organisms should make it a useful tool in predicting relationships among organisms.-
dc.languageEnglish-
dc.publisherKOREAN SOC MICROBIOLOGY & BIOTECHNOLOGY-
dc.titleGenomic tree of gene contents based on functional groups of KEGG orthology-
dc.typeArticle-
dc.identifier.wosid000237908300014-
dc.identifier.scopusid2-s2.0-33744948536-
dc.type.rimsART-
dc.citation.volume16-
dc.citation.beginningpage748-
dc.citation.endingpage756-
dc.citation.publicationnameJOURNAL OF MICROBIOLOGY AND BIOTECHNOLOGY-
dc.contributor.localauthorLee, SangYup-
dc.contributor.nonIdAuthorKim, JS-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorKEGG orthology-
dc.subject.keywordAuthorself-organizing tree algorithm-
dc.subject.keywordAuthorhierarchical clustering-
dc.subject.keywordAuthorfunctional category-
dc.subject.keywordAuthorgene contents-
dc.subject.keywordPlusGROWING NEURAL-NETWORK-
dc.subject.keywordPlusPHYLOGENETIC ANALYSIS-
dc.subject.keywordPlusEXPRESSION PATTERNS-
dc.subject.keywordPlusSEQUENCE-
dc.subject.keywordPlusCONSERVATION-
dc.subject.keywordPlusEVOLUTION-
dc.subject.keywordPlusPATHWAYS-
dc.subject.keywordPlusARCHAEAL-
dc.subject.keywordPlusHISTORY-
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