KEGG as a reference resource for gene and protein annotation

Area of Science:

• Bioinformatics
• Genomics
• Systems Biology

Background:

• KEGG is an integrated database for biological interpretation of high-throughput data.
• It utilizes KEGG Orthology (KO) to associate molecular functions with genes and proteins.
• KEGG pathway maps, BRITE hierarchies, and modules represent cellular and organismal functions as networks of KO nodes.

Purpose of the Study:

• To enhance KEGG as an annotation resource for biological interpretation.
• To improve the accuracy and scope of functional annotations.
• To provide new tools for automatic gene and protein annotation.

Main Methods:

• Re-examination of KEGG Orthology (KO) records with associated protein sequence data.
• Expansion of the KEGG GENES database to include viruses, plasmids, and functionally characterized proteins outside complete genomes.
• Development and utilization of new automatic annotation servers, BlastKOALA and GhostKOALA, with non-redundant pangenome data.

Main Results:

• Improved functional characterization of genes and proteins through re-examined KO records.
• Expanded KEGG GENES database with broader coverage of biological entities.
• Introduction of user-friendly automatic annotation servers for efficient KO assignment.
• Creation of datasets for translational bioinformatics, including antimicrobial resistance and drug interaction networks.

Conclusions:

• KEGG has been significantly enhanced as a comprehensive resource for biological data interpretation.
• New annotation tools and expanded databases facilitate more accurate and extensive genomic analysis.
• KEGG supports translational bioinformatics with specialized datasets for drug discovery and resistance studies.