The KEGG databases at GenomeNet

The Kyoto Encyclopedia of Genes and Genomes (KEGG) is the primary database resource of the Japanese GenomeNet service (http://www.genome.ad.jp/) for understanding higher order functional meanings and utilities of the cell or the organism from its genome information. KEGG consists of the PATHWAY database for the computerized knowledge on molecular interaction networks such as pathways and complexes, the GENES database for the information about genes and proteins generated by genome sequencing projects, and the LIGAND database for the information about chemical compounds and chemical reactions that are relevant to cellular processes. In addition to these three main databases, limited amounts of experimental data for microarray gene expression profiles and yeast two-hybrid systems are stored in the EXPRESSION and BRITE databases, respectively. Furthermore, a new database, named SSDB, is available for exploring the universe of all protein coding genes in the complete genomes and for identifying functional links and ortholog groups. The data objects in the KEGG databases are all represented as graphs and various computational methods are developed to detect graph features that can be related to biological functions. For example, the correlated clusters are graph similarities which can be used to predict a set of genes coding for a pathway or a complex, as summarized in the ortholog group tables, and the cliques in the SSDB graph are used to annotate genes. The KEGG databases are updated daily and made freely available (http://www.genome.ad.jp/kegg/).

[1]  M. Kanehisa,et al.  DBGET/LinkDB: an integrated database retrieval system. , 1998, Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing.

[2]  Amos Bairoch,et al.  The PROSITE database, its status in 2002 , 2002, Nucleic Acids Res..

[3]  Susumu Goto,et al.  LIGAND: database of chemical compounds and reactions in biological pathways , 2002, Nucleic Acids Res..

[4]  M. Kanehisa,et al.  Reconstruction of amino acid biosynthesis pathways from the complete genome sequence. , 1998, Genome research.

[5]  Hiroyuki Ogata,et al.  KEGG: Kyoto Encyclopedia of Genes and Genomes , 1999, Nucleic Acids Res..

[6]  A. Ogiwara,et al.  Searching for amino acid sequence motifs among enzymes: the Enzyme- Reaction Database , 1993, Comput. Appl. Biosci..

[7]  M. Kanehisa,et al.  A heuristic graph comparison algorithm and its application to detect functionally related enzyme clusters. , 2000, Nucleic acids research.

[8]  M. Kanehisa.  Linking databases and organisms: GenomeNet resources in Japan. , 1997, Trends in biochemical sciences.

[9]  Amos Bairoch,et al.  The PROSITE database, its status in 1999 , 1999, Nucleic Acids Res..

[10]  M Kanehisa,et al.  Pathway databases and higher order function. , 2000, Advances in protein chemistry.

[11]  金久 実,et al.  Post-genome informatics , 2000 .

[12]  W. Pearson.  Effective protein sequence comparison. , 1996, Methods in enzymology.

[13]  M. Kanehisa.  A database for post-genome analysis. , 1997, Trends in genetics : TIG.