ArticleNucleic acids research2013
KEGG OC: a large-scale automatic construction of taxonomy-based ortholog clusters.
Article in Nucleic acids research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers.
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68 citing papers in PubMed.
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- OrthoDB v11: annotation of orthologs in the widest sampling of organismal diversity.Nucleic acids research · 2023Article
- OncoboxPD: human 51 672 molecular pathways database with tools for activity calculating and visualization.Computational and structural biotechnology journal · 2022Article
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- Hi-C deconvolution of a textile dye-related microbiome reveals novel taxonomic landscapes and links phenotypic potential to individual genomes.International microbiology : the official journal of the Spanish Society for Microbiology · 2022Article
- OrthoDB in 2020: evolutionary and functional annotations of orthologs.Nucleic acids research · 2021Article
- The Functional Classification of ORF8 in SARS-CoV-2 Replication, Immune Evasion, and Viral Pathogenesis Inferred through Phylogenetic Profiling.Evolutionary bioinformatics online · 2021Article
- Next-Generation Sequencing for Whole-Genome Characterization ofFrontiers in microbiology · 2021Article
- System, Method and Software for Calculation of a Cannabis Drug Efficiency Index for the Reduction of Inflammation.International journal of molecular sciences · 2020Article
- Molecular pathophysiology of diabetes mellitus during pregnancy with antenatal complications.Scientific reports · 2020Article
- Proteome of Glioblastoma-Derived Exosomes as a Source of Biomarkers.Biomedicines · 2020Article
8 more citing papers are in PubMed but not listed here.
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13 authors.
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Abstract
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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