KEGG Mapper for inferring cellular functions from protein sequences

2019/08/19 by Minoru Kanehisa, Yoko Sato · 14 citations
Biochemistry, Genetics and Molecular Biology · #Genomics and Phylogenetic Studies #Glycosylation and Glycoproteins Research #Machine Learning in Bioinformatics

paper · pdf · doi:10.1002/pro.3711

openalex publication_date 2019/08/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/30

Abstract

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.

Citations

• BlastKOALA and GhostKOALA: KEGG Tools for Functional Characterization of Genome and Metagenome Sequences

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