Genomic Tree of Gene Contents Based on Functional Groups of KEGG Orthology

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We 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 twostep 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.
Publisher
The Korean Society for Applied Microbiology
Issue Date
2006
Keywords

KEGG; orthology; self-organizing tree algorithm; hierarchical clustering; functional category; gene contents; KEGG; orthology; self-organizing tree algorithm; hierarchical clustering; functional category; gene contents

Citation

Journal of Microbiology and Biotechnology, Vol.16, No.5, pp.748-756

URI
http://hdl.handle.net/10203/22637
Appears in Collection
CBE-Journal Papers(저널논문)
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