KEGG as a reference resource for gene and protein annotation
By Minoru Kanehisa, Yoko Sato, Masayuki Kawashima, Miho Furumichi, Mao Tanabe. Nucleic Acids Res., 2015
6,660 citations recorded by the source corpus.
KEGG (http://www.kegg.jp/ or http://www.genome.jp/kegg/) is an integrated database resource for biological interpretation of genome sequences and other high-throughput data. Molecular functions of genes and proteins are associated with ortholog groups and stored in the KEGG Orthology (KO) database. The KEGG pathway maps, BRITE hierarchies and KEGG modules are developed as networks of KO nodes, representing high-level functions of the cell and the organism. Currently, more than 4000 complete genomes are annotated with KOs in the KEGG GENES database, which can be used as a reference data set for KO assignment and subsequent reconstruction of KEGG pathways and other molecular networks. As an annotation resource, the following improvements have been made. First, each KO record is re-examined and associated with protein sequence data used in experiments of functional characterization. Second, the GENES database now includes viruses, plasmids, and the addendum category for functionally characterized proteins that are not represented in complete genomes. Third, new automatic annotation servers, BlastKOALA and GhostKOALA, are made available utilizing the non-redundant pangenome data set generated from the GENES database. As a resource for translational bioinformatics, various data sets are created for antimicrobial resistance and drug interaction networks.
Subfields: Molecular Biology
View Paper: https://www.semanticscholar.org/paper/b106e566f4ff5a4d2c5d9347ee69d5feba3482e8
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In Molecular Biology
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Citations in the corpus
- Untargeted metabolomics strategies – Challenges and Emerging Directions (2016, neutral): “Levels 2 and 1 (Putative identification or Validation) Integration with known biology Pathway and network analyses MetaboAnalyst [40] Kyoto Encyclopedia of Genes and Genomes (KEGG) [41] Mbrole (Metabolite Biological Role) [42] MetaCyc/BioCyc [43]”
- FungiDB: An Integrated Bioinformatic Resource for Fungi and Oomycetes (2018, methodology): “Interactive pathway map for KEGG ec00620 (Pyruvate metabolism).”
- Identification of genetic elements in metabolism by high-throughput mouse phenotyping (2018, neutral): “Zranb2 shares two central MORE sets with the Dtnbp1 and Epha5 genes, which con fi rms their previously reported functional links with Zranb2 42 – 45 .”
- Improvements to PATRIC, the all-bacterial Bioinformatics Database and Analysis Resource Center (2016, background): “PATRIC also assigns protein family membership to protein encoding genes in order to drive its comparative analysis tools and metabolic pathway information, which can be viewed on the KEGG map (29) under the ‘Pathways’.”
- Species-level functional profiling of metagenomes and metatranscriptomes (2018, neutral): “To analyze the synthetic gut metagenome with HUMAnN1 (updated to use DIAMOND 16 for translated search) we constructed a database from HUMAnN1’s default protein sequence collection: the last public release of KEGG (v56) 26 .”