KEGG Overview

1. KEGG Databases

KEGG is an integrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information as shown below. Genomic and chemical information represents the molecular building blocks of life in the genomic and chemical spaces, respectively, and systems information represents functional aspects of the biological systems, such as the cell and the organism, that are built from the building blocks. KEGG has been widely used as a reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.

2. KEGG Objects

KEGG is a computer representation of the biological systems. It is based on the concept of graph for representation and manipulation of various KEGG objects from molecular to higher levels. Mathematically, a graph is a set of nodes (KEGG objects) and edges (biological relationships). Each of the KEGG objects (database entries) is given an unique identifier shown below.

KEGG objects are linked to/from major life science databases. KEGG objects are also part of the Web; they can be found by Web search engines.

3. Network Hierarchy

The molecular interaction/reaction network is the most unique data object in KEGG, which is stored as a collection of pathway maps (graphical diagrams) in the PATHWAY database. Reflecting the map resolution, KEGG PATHWAY is organized in a hierarchy. The top two levels in the current hierarchy is the following.

4. Network Reconstruction

Originally, the integration of pathway information and genomic information was first achieved in KEGG by the EC numbers. Once the EC numbers were correctly assigned to enzyme genes in the genome, organism-specific pathways could be generated automatically by matching against the networks of EC numbers (enzymes) in the reference metabolic pathways. However, in order to incorporate non-metabolic pathways and to overcome various problems inherent in the enzyme nomenclature, a new scheme based on the ortholog IDs was introduced replacing the EC numbers. KO (KEGG Orthology) is a further extension of ortholog IDs based on not only the pathway maps but also the BRITE functional hierarchies, most notably classifications of protein families.

Thus, under the current KO system, the KO identifiers (K numbers) are placed at the fourth (lowest) level in the network hierarchy shown above, or at the lowest level of the BRITE hierarchy.

5. BRITE Functional Hierarchy

The BRITE database is a collection of hierarchical text files and binary relation files. It is intended to supplement the PATHWAY database in two ways. One is to computerize higher-level knowledge that cannot easily be represented as molecular interaction/reaction networks, in terms of the hierarchically structured vocabulary. The other is to integrate our knowledge about the genomic space (K numbers) with different types of knowledge in the chemical space (C/D/G/R/RP/EC numbers in the LIGAND database). The BRITE collection is currently categorized as follows.

References

1. Kanehisa, M.; Toward pathway engineering: a new database of genetic and molecular pathways. Science & Technology Japan, No. 59, pp. 34-38 (1996). [pdf]
2. Kanehisa, M.; A database for post-genome analysis. Trends Genet. 13, 375-376 (1997). [pubmed]
3. Ogata, H., Goto, S., Sato, K., Fujibuchi, W., Bono, H., and Kanehisa, M.; KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 27, 29-34 (1999). [pubmed] [pdf]
4. Kanehisa, M. and Goto, S.; KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 28, 27-30 (2000). [pubmed] [pdf]
5. Kanehisa, M., Goto, S., Kawashima, S., and Nakaya, A.; The KEGG databases at GenomeNet. Nucleic Acids Res. 30, 42-46 (2002). [pubmed] [pdf]
6. Kanehisa, M., Goto, S., Kawashima, S., Okuno, Y., and Hattori, M.; The KEGG resources for deciphering the genome. Nucleic Acids Res. 32, D277-D280 (2004). [pubmed] [pdf]
7. Kanehisa, M., Goto, S., Hattori, M., Aoki-Kinoshita, K.F., Itoh, M., Kawashima, S., Katayama, T., Araki, M., and Hirakawa, M.; From genomics to chemical genomics: new developments in KEGG. Nucleic Acids Res. 34, D354-357 (2006). [pubmed] [pdf]
8. Kanehisa, M., Araki, M., Goto, S., Hattori, M., Hirakawa, M., Itoh, M., Katayama, T., Kawashima, S., Okuda, S., Tokimatsu, T., and Yamanishi, Y.; KEGG for linking genomes to life and the environment. Nucleic Acids Res. 36, D480-D484 (2008). [pubmed] [pdf]
9. Kanehisa, M., Goto, S., Furumichi, M., Tanabe, M., and Hirakawa, M.; KEGG for representation and analysis of molecular networks involving diseases and drugs. Nucleic Acids Res. 38, D355-D360 (2010). [pubmed] [pdf]