KEGG, The Kyoto Encyclopedia of Genes and Genomes
Tutorial and training materials by OpenHelix
|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.|
- how to navigate KEGG and to perform effective searches on topics of interest
- how to set the displays for efficient access to the data of interest to you
- how to customize the colors of displays to represent your own data
- how to investigate reference and disease pathways, genes, ligands, drugs, and more
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Recent BioMed Central research articles citing this resource
Yamamoto Hiroyuki et al., Statistical hypothesis testing of factor loading in principal component analysis and its application to metabolite set enrichment analysis Proteomics. BMC Bioinformatics (2014) doi:10.1186/1471-2105-15-51
Rahmad Norasfaliza et al., Comparative proteomic analysis of different developmental stages of the edible mushroom Termitomyces heimii. Biological Research (2014) doi:10.1186/0717-6287-47-30
Westergaard David et al., Exploring mechanisms of diet-colon cancer associations through candidate molecular interaction networks Human and rodent genomics. BMC Genomics (2014) doi:10.1186/1471-2164-15-380
Abo-Ismail K Mohammed et al., Single nucleotide polymorphisms for feed efficiency and performance in crossbred beef cattle Complex traits and quantitative genetics. BMC Genetics (2014) doi:10.1186/1471-2156-15-14
Souiai Oussema et al., In silico prediction of protein-protein interactions in human macrophages. BMC Research Notes (2014) doi:10.1186/1756-0500-7-157
More about the resource:
KEGG is developed and maintained by the Kanehisa Laboratories. From the first reference in 1996, KEGG has grown beyond the initial focus on metabolic pathway data to integrate more data types and important aspects of biology and biomedical research. They continue to add new data types and representations today. Academic users may freely use the KEGG website. To employ KEGG in commercial tools and applications, a license is required. Licenses can be obtained from Pathway Solutions.
The materials and slides offered can not be resold or used for profit purposes. Reproduction, distribution and/or use is strictly limited to instructional purposes only and can not be used for for monetary gain or wide distribution.
Copyright 2009, OpenHelix, LLC.