KEGG Mapper for inferring cellular functions from protein sequences

By Minoru Kanehisa, Yoko Sato. Protein Science, 2019

997 citations recorded by the source corpus.

KEGG is a reference knowledge base for biological interpretation of large‐scale molecular datasets, such as genome and metagenome sequences. It accumulates experimental knowledge about high‐level functions of the cell and the organism represented in terms of KEGG molecular networks, including KEGG pathway maps, BRITE hierarchies, and KEGG modules. By the process called KEGG mapping, a set of protein coding genes in the genome, for example, can be converted to KEGG molecular networks enabling interpretation of cellular functions and other high‐level features. Here we report a new version of KEGG Mapper, a suite of KEGG mapping tools available at the KEGG website (https://www.kegg.jp/ or https://www.genome.jp/kegg/), together with the KOALA family tools for automatic assignment of KO (KEGG Orthology) identifiers used in the mapping.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/82956cdbf2653b08504b145a5fbca9ad627fc501

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Citations in the corpus

KEGG: integrating viruses and cellular organisms (2020, methodology): “The module link mode is also implemented in the Reconstruct Pathway tool of KEGG Mapper (4).”
KEGG mapping tools for uncovering hidden features in biological data (2021, methodology): “This article reports KEGG Mapper Version 5, an updated collection of KEGG mapping tools as a sequel to Version 4 reported in the previous article.(5)”
KEGG: biological systems database as a model of the real world (2024, methodology): “KEGG Mapper is a collection of KEGG mapping tools, which started as a simple tool for searching and coloring pathway maps at the beginning of the KEGG project and was significantly expanded over the years ( 5 ,6 ).”