The KEGG resource for deciphering the genome

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ID: 289526
2003
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Abstract
A grand challenge in the post-genomic era is a complete computer representation of the cell and the organism, which will enable computational prediction of higher-level complexity of cellular processes and organism behavior from genomic information. Toward this end we have been developing a knowledge-based approach for network prediction, which is to predict, given a complete set of genes in the genome, the protein interaction networks that are responsible for various cellular processes. KEGG at http://www.genome.ad.jp/kegg/ is the reference knowledge base that integrates current knowledge on molecular interaction networks such as pathways and complexes (PATHWAY database), information about genes and proteins generated by genome projects (GENES/SSDB/KO databases) and information about biochemical compounds and reactions (COMPOUND/GLYCAN/REACTION databases). These three types of database actually represent three graph objects, called the protein network, the gene universe and the chemical universe. New efforts are being made to abstract knowledge, both computationally and manually, about ortholog clusters in the KO (KEGG Orthology) database, and to collect and analyze carbohydrate structures in the GLYCAN database.
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openalex_W2142237411 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors M. Kanehisa
Journal Nucleic Acids Research
Year 2003
DOI
10.1093/nar/gkh063
URL
https://doi.org/10.1093/nar/gkh063
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