New approach for understanding genome variations in KEGG

Area of Science:

• Bioinformatics
• Genomics
• Systems Biology

Background:

• KEGG is a vital knowledge base for interpreting biological data, including genomic and chemical information.
• Existing KEGG resources utilize generic molecular networks applicable across organisms.
• The previous generic approach was insufficient for representing human health information, particularly disease-related genetic variations.

Purpose of the Study:

• To address limitations in representing human-specific health information within KEGG.
• To introduce a novel approach for incorporating human gene variations into molecular network knowledge.
• To develop a resource for understanding disease mechanisms and supporting clinical applications.

Main Methods:

• Development of the KEGG NETWORK database.
• Explicit incorporation of human gene variants as 'network variants'.
• Integration of knowledge on disease-related perturbed molecular networks.

Main Results:

• KEGG NETWORK explicitly represents human gene variants, overcoming limitations of generic models.
• The database accumulates knowledge on perturbed molecular networks influenced by gene variants, pathogens, environmental factors, and drugs.
• A new framework for representing human health information within KEGG has been established.

Conclusions:

• KEGG NETWORK provides a specialized resource for human health information, building upon the established KEGG framework.
• This new database is expected to advance the understanding of disease mechanisms.
• KEGG NETWORK is poised to be a valuable tool for clinical sequencing and drug development.