Abstract
KEGG (http://www.genome.jp/kegg/) is an integrated database resource for linking genomes or molecular datasets to molecular networks (pathways, etc.) representing higher-level systemic functions of the cell, the organism, and the ecosystem. Major efforts have been undertaken for capturing and representing experimental knowledge as manually drawn KEGG pathway maps and for genome-based generalization of experimental knowledge through the KEGG Orthology (KO) system. Current knowledge on diseases and drugs has also been integrated in the KEGG pathway maps, especially in terms of known disease genes and drug targets. Thus, KEGG can be used as a reference knowledge base for integration and interpretation of large-scale datasets generated by high-throughput experimental technologies, as well for finding their practical values. Here we give an introduction to the KEGG Mapper tools, especially for understanding disease mechanisms and adverse drug interactions.
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Kanehisa, M. (2013). Molecular Network Analysis of Diseases and Drugs in KEGG. In: Mamitsuka, H., DeLisi, C., Kanehisa, M. (eds) Data Mining for Systems Biology. Methods in Molecular Biology, vol 939. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-62703-107-3_17
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DOI: https://doi.org/10.1007/978-1-62703-107-3_17
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Publisher Name: Humana Press, Totowa, NJ
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