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KEGG OC: a large-scale automatic construction of taxonomy-based ortholog clusters

The identification of orthologous genes in an increasing number of fully sequenced genomes is a challenging issue in recent genome science. Here we present KEGG OC (http://www.genome.jp/tools/oc/), a novel database of ortholog clusters (OCs). The current version of KEGG OC contains 1 176 030 OCs, ob...

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Autores principales: Nakaya, Akihiro, Katayama, Toshiaki, Itoh, Masumi, Hiranuka, Kazushi, Kawashima, Shuichi, Moriya, Yuki, Okuda, Shujiro, Tanaka, Michihiro, Tokimatsu, Toshiaki, Yamanishi, Yoshihiro, Yoshizawa, Akiyasu C., Kanehisa, Minoru, Goto, Susumu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3531156/
https://www.ncbi.nlm.nih.gov/pubmed/23193276
http://dx.doi.org/10.1093/nar/gks1239
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author Nakaya, Akihiro
Katayama, Toshiaki
Itoh, Masumi
Hiranuka, Kazushi
Kawashima, Shuichi
Moriya, Yuki
Okuda, Shujiro
Tanaka, Michihiro
Tokimatsu, Toshiaki
Yamanishi, Yoshihiro
Yoshizawa, Akiyasu C.
Kanehisa, Minoru
Goto, Susumu
author_facet Nakaya, Akihiro
Katayama, Toshiaki
Itoh, Masumi
Hiranuka, Kazushi
Kawashima, Shuichi
Moriya, Yuki
Okuda, Shujiro
Tanaka, Michihiro
Tokimatsu, Toshiaki
Yamanishi, Yoshihiro
Yoshizawa, Akiyasu C.
Kanehisa, Minoru
Goto, Susumu
author_sort Nakaya, Akihiro
collection PubMed
description The identification of orthologous genes in an increasing number of fully sequenced genomes is a challenging issue in recent genome science. Here we present KEGG OC (http://www.genome.jp/tools/oc/), a novel database of ortholog clusters (OCs). The current version of KEGG OC contains 1 176 030 OCs, obtained by clustering 8 357 175 genes in 2112 complete genomes (153 eukaryotes, 1830 bacteria and 129 archaea). The OCs were constructed by applying the quasi-clique-based clustering method to all possible protein coding genes in all complete genomes, based on their amino acid sequence similarities. It is computationally efficient to calculate OCs, which enables to regularly update the contents. KEGG OC has the following two features: (i) It consists of all complete genomes of a wide variety of organisms from three domains of life, and the number of organisms is the largest among the existing databases; and (ii) It is compatible with the KEGG database by sharing the same sets of genes and identifiers, which leads to seamless integration of OCs with useful components in KEGG such as biological pathways, pathway modules, functional hierarchy, diseases and drugs. The KEGG OC resources are accessible via OC Viewer that provides an interactive visualization of OCs at different taxonomic levels.
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spelling pubmed-35311562013-03-07 KEGG OC: a large-scale automatic construction of taxonomy-based ortholog clusters Nakaya, Akihiro Katayama, Toshiaki Itoh, Masumi Hiranuka, Kazushi Kawashima, Shuichi Moriya, Yuki Okuda, Shujiro Tanaka, Michihiro Tokimatsu, Toshiaki Yamanishi, Yoshihiro Yoshizawa, Akiyasu C. Kanehisa, Minoru Goto, Susumu Nucleic Acids Res Articles The identification of orthologous genes in an increasing number of fully sequenced genomes is a challenging issue in recent genome science. Here we present KEGG OC (http://www.genome.jp/tools/oc/), a novel database of ortholog clusters (OCs). The current version of KEGG OC contains 1 176 030 OCs, obtained by clustering 8 357 175 genes in 2112 complete genomes (153 eukaryotes, 1830 bacteria and 129 archaea). The OCs were constructed by applying the quasi-clique-based clustering method to all possible protein coding genes in all complete genomes, based on their amino acid sequence similarities. It is computationally efficient to calculate OCs, which enables to regularly update the contents. KEGG OC has the following two features: (i) It consists of all complete genomes of a wide variety of organisms from three domains of life, and the number of organisms is the largest among the existing databases; and (ii) It is compatible with the KEGG database by sharing the same sets of genes and identifiers, which leads to seamless integration of OCs with useful components in KEGG such as biological pathways, pathway modules, functional hierarchy, diseases and drugs. The KEGG OC resources are accessible via OC Viewer that provides an interactive visualization of OCs at different taxonomic levels. Oxford University Press 2013-01 2012-11-26 /pmc/articles/PMC3531156/ /pubmed/23193276 http://dx.doi.org/10.1093/nar/gks1239 Text en © The Author(s) 2012. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial reuse, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com.
spellingShingle Articles
Nakaya, Akihiro
Katayama, Toshiaki
Itoh, Masumi
Hiranuka, Kazushi
Kawashima, Shuichi
Moriya, Yuki
Okuda, Shujiro
Tanaka, Michihiro
Tokimatsu, Toshiaki
Yamanishi, Yoshihiro
Yoshizawa, Akiyasu C.
Kanehisa, Minoru
Goto, Susumu
KEGG OC: a large-scale automatic construction of taxonomy-based ortholog clusters
title KEGG OC: a large-scale automatic construction of taxonomy-based ortholog clusters
title_full KEGG OC: a large-scale automatic construction of taxonomy-based ortholog clusters
title_fullStr KEGG OC: a large-scale automatic construction of taxonomy-based ortholog clusters
title_full_unstemmed KEGG OC: a large-scale automatic construction of taxonomy-based ortholog clusters
title_short KEGG OC: a large-scale automatic construction of taxonomy-based ortholog clusters
title_sort kegg oc: a large-scale automatic construction of taxonomy-based ortholog clusters
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3531156/
https://www.ncbi.nlm.nih.gov/pubmed/23193276
http://dx.doi.org/10.1093/nar/gks1239
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