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Methods Mol Biol. 2018;1807:225-239. doi: 10.1007/978-1-4939-8561-6_17.

Inferring Antimicrobial Resistance from Pathogen Genomes in KEGG.

Author information

1
Institute for Chemical Research, Kyoto University, Uji, Kyoto, Japan. kanehisa@kuicr.kyoto-u.ac.jp.

Abstract

The KEGG database is widely used as a reference knowledge base for biological interpretation of genome sequences and other high-throughput data. It contains, among others, KEGG pathway maps and BRITE hierarchies (ontologies) representing high-level systemic functions of the cell and the organism. By the processes called pathway mapping and BRITE mapping, information encoded in the genome, especially the repertoire of genes, is converted to such high-level functional information. This general methodology can be applied to microbial genomes to infer antimicrobial resistance (AMR), which is becoming an increasingly serious threat to the global public health. Here we present how knowledge on AMR is accumulated in the KEGG Pathogen resource and how such knowledge can be utilized by BlastKOALA and other web tools.

KEYWORDS:

Beta-lactamase; BlastKOALA; Genome annotation; KEGG Orthology (KO); KEGG module

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