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Minoru Kanehisa

Researcher at Kyoto University

Publications -  379
Citations -  97487

Minoru Kanehisa is an academic researcher from Kyoto University. The author has contributed to research in topics: KEGG & Genome. The author has an hindex of 83, co-authored 378 publications receiving 79574 citations. Previous affiliations of Minoru Kanehisa include Los Alamos National Laboratory & Osaka Ohtani University.

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KEGG: Kyoto Encyclopedia of Genes and Genomes

TL;DR: The Kyoto Encyclopedia of Genes and Genomes (KEGG) as discussed by the authors is a knowledge base for systematic analysis of gene functions in terms of the networks of genes and molecules.
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KEGG: new perspectives on genomes, pathways, diseases and drugs

TL;DR: The content has been expanded and the quality improved irrespective of whether or not the KOs appear in the three molecular network databases, and the newly introduced addendum category of the GENES database is a collection of individual proteins whose functions are experimentally characterized and from which an increasing number of KOs are defined.
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KEGG for linking genomes to life and the environment

TL;DR: KEGG PATHWAY is now supplemented with a new global map of metabolic pathways, which is essentially a combined map of about 120 existing pathway maps, and the KEGG resource is being expanded to suit the needs for practical applications.
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KEGG as a reference resource for gene and protein annotation

TL;DR: The KEGG GENES database now includes viruses, plasmids, and the addendum category for functionally characterized proteins that are not represented in complete genomes, and new automatic annotation servers, BlastKOalA and GhostKOALA, are made available utilizing the non-redundant pangenome data set generated from theGENES database.
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KEGG for integration and interpretation of large-scale molecular data sets

TL;DR: KEGG Mapper, a collection of tools for KEGG PATHWAY, BRITE and MODULE mapping, enabling integration and interpretation of large-scale data sets and recent enhancements to the K EGG content, especially the incorporation of disease and drug information used in practice and in society, to support translational bioinformatics.