Minoru Kanehisa discusses the development and significance of the KEGG (Kyoto Encyclopedia of Genes and Genomes) resource in understanding the origin and evolution of cellular organisms. KEGG is a comprehensive biological database that integrates genomic and chemical information to provide insights into the functions and interactions of cellular systems. It was developed as part of the Japanese Human Genome Project and has since become one of the most widely used biological databases. KEGG enables the interpretation of genome sequences and high-throughput data by providing pathway maps and other molecular networks that represent biological processes. The KEGG pathway maps are manually drawn diagrams that show the interactions and reactions among molecules, including genes, proteins, and chemical compounds. These maps are designed to link genes in the genome to their corresponding gene products in the pathway. KEGG uses two types of abstractions: generalized protein-protein interactions and functional grouping (KO, KEGG Orthology). KO is a manually defined functional ortholog that allows for the extension of experimental knowledge from specific organisms to others. KEGG also integrates genomic and chemical information to analyze the co-evolution of chemical and genomic networks. The KEGG MEDICUS extension provides health-related information, including drug labels and disease data, supporting translational bioinformatics. KEGG is considered a knowledge base that combines data, information, and knowledge to uncover the principles of biological systems, aligning with the principles of physics and chemistry. Kanehisa emphasizes the importance of manually verified experimental results over computational predictions in KEGG, aiming to develop it into a comprehensive resource for understanding biological systems.Minoru Kanehisa discusses the development and significance of the KEGG (Kyoto Encyclopedia of Genes and Genomes) resource in understanding the origin and evolution of cellular organisms. KEGG is a comprehensive biological database that integrates genomic and chemical information to provide insights into the functions and interactions of cellular systems. It was developed as part of the Japanese Human Genome Project and has since become one of the most widely used biological databases. KEGG enables the interpretation of genome sequences and high-throughput data by providing pathway maps and other molecular networks that represent biological processes. The KEGG pathway maps are manually drawn diagrams that show the interactions and reactions among molecules, including genes, proteins, and chemical compounds. These maps are designed to link genes in the genome to their corresponding gene products in the pathway. KEGG uses two types of abstractions: generalized protein-protein interactions and functional grouping (KO, KEGG Orthology). KO is a manually defined functional ortholog that allows for the extension of experimental knowledge from specific organisms to others. KEGG also integrates genomic and chemical information to analyze the co-evolution of chemical and genomic networks. The KEGG MEDICUS extension provides health-related information, including drug labels and disease data, supporting translational bioinformatics. KEGG is considered a knowledge base that combines data, information, and knowledge to uncover the principles of biological systems, aligning with the principles of physics and chemistry. Kanehisa emphasizes the importance of manually verified experimental results over computational predictions in KEGG, aiming to develop it into a comprehensive resource for understanding biological systems.