Learn to use KEGG the Kyoto Encyclopedia of Genes and Genomes, an extensive and widely used resource containing information on genes and pathways in a wide range of species. KEGG curates, integrates, and displays information that enables deep understanding of biological systems. Genes, ligands that interact with genes, pathways in which they participate, descriptive terms that clarify the relationships of all of these aspects come together in this fundamental resource. KEGG is a knowledgebase with application to many areas of biological investigation from basic research, to pharmaceutical discovery, and environmental investigations as well. In this introductory tutorial, you will learn about the foundations and features of KEGG, enabling you to efficiently use one of the foundational resources for systems biology.
You will learn:
This tutorial is a part of the tutorial group Interaction resources. You might find the other tutorials in the group interesting:
Pathway Interaction Database: A resource of pathway and network data and displays
MINT: Molecular Interaction Database
Cytoscape: An open-source software platform used for visualization and analysis of molecular interaction and network data
BiologicalNetworks: Analyze and visualize molecular interaction networks
BioSystems: Database of Biological Systems
Reactome Legacy: Older version of the current Reactome knowledgebase of biological processes.
Reactome: Knowledgebase of biological processes
GeneMANIA: GeneMANIA: Fast Gene Function Predictions
GenMAPP: A freely available open source software application for visualizing microarray data in the context of biological pathways.
VisANT: A web-based or downloadable software platform used for visualization and analysis of networks and interaction pathways
InterPro: A comprehensive protein signature resource
IntAct protein interaction database: IntAct is an open source database and analysis resource for protein interaction data
Pathways and Interactions : Tools that are involved with protein interactions and pathway features. Some tools are primarily repositories and some offer analysis options.
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Recent BioMed Central research articles citing this resource
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Wang Caihua et al., Predicting target-ligand interactions using protein ligand-binding site and ligand substructures Selected articles from the Thirteenth Asia Pacific Bioinformatics Conference (APBC 2015): Systems Biology The Thirteenth Asia Pacific Bioinformatics Conference (APBC 2015). BMC Systems Biology (2015) doi:10.1186/1752-0509-9-S1-S2