Using the KEGG Database Resource
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- Abstract
- Table of Contents
- Figures
- Literature Cited
Abstract
KEGG (Kyoto Encyclopedia of Genes and Genomes) is a bioinformatics resource for understanding the functions and utilities of cells and organisms from both high?level and genomic perspectives. It is a self?sufficient, integrated resource consisting of genomic, chemical, and network information, with cross?references to numerous outside databases. The genomic and chemical information is a complete set of building blocks (genes and molecules) and the network information includes molecular wiring diagrams (interaction/reaction networks) and hierarchical classifications (relation networks) to represent high?level functions. This unit describes protocols for using KEGG, focusing on molecular network information in KEGG PATHWAY, KEGG BRITE, and KEGG MODULE, perturbed molecular networks in KEGG DISEASE and KEGG DRUG, molecular building block information in KEGG GENES and KEGG LIGAND, and a mechanism for linking genomes to molecular networks in KEGG ORTHOLOGY (KO). All of these many protocols enable the user to take advantage of the full breadth of the functionality provided by KEGG. Curr. Protoc. Bioinform. 38:1.12.1?1.12.43. © 2012 by John Wiley & Sons, Inc.
Keywords: KEGG pathway map; BRITE functional hierarchy; molecular network; genome annotation; chemical information analysis
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PDF or HTML at Wiley Online LibraryTable of Contents
- Introduction
- Basic Protocol 1: The KEGG Database Resource: Getting Started
- Basic Protocol 2: KEGG Pathway: Metabolic Pathway Map
- Basic Protocol 3: KEGG Pathway: Genome Comparison and Combination
- Basic Protocol 4: KEGG Pathway: Regulatory Pathway Map
- Basic Protocol 5: KEGG Pathway: Disease Pathway Map
- Basic Protocol 6: KEGG Drug: Network‐Based Drug Information Resource
- Basic Protocol 7: KEGG Disease: Disease Genes and Pathogen Genomes
- Basic Protocol 8: KEGG Disease/Drug Mapping
- Basic Protocol 9: KEGG BRITE: Functional Hierarchy of Genes and Proteins
- Basic Protocol 10: KEGG BRITE: Functional Hierarchy of Other Entities
- Basic Protocol 11: KEGG GENES: Gene Catalogs of Complete Genomes
- Basic Protocol 12: KEGG SSDB: Analysis of Gene/Protein Universe
- Basic Protocol 13: KEGG Orthology: Linking Genome to Molecular Network
- Basic Protocol 14: KEGG GENOME: Genome Metadata and Taxonomy
- Basic Protocol 15: KEGG LIGAND: Chemical Structure and Similarity Search
- Basic Protocol 16: KEGG LIGAND: Biochemical Reaction and Path Prediction
- Basic Protocol 17: KEGG MODULE: Functional Units and Signatures
- Basic Protocol 18: KEGG Mapper: Pathway Mapping
- Basic Protocol 19: KEGG Mapper: BRITE Mapping
- Basic Protocol 20: KEGG Atlas: Advanced Visualization Tool
- Commentary
- Literature Cited
- Figures
- Tables
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Figure 1.12.1 The KEGG home page and the KEGG2 (Table of Contents) page are the entry points to the various databases and analysis tools, such as the KEGG PATHWAY database. View Image -
Figure 1.12.2 The KEGG metabolic pathway map for citrate cycle (TCA cycle) (map0020). View Image -
Figure 1.12.3 The KEGG global metabolism map (map01100) used to compare metabolic capabilities of Homo sapiens and Arabidopsis thaliana . View Image -
Figure 1.12.4 The KEGG regulatory pathway map for MAPK signaling pathway for human (hsa04010). View Image -
Figure 1.12.5 The KEGG disease pathway map for chronic myeloid leukemia (hsa05220). View Image -
Figure 1.12.6 The KEGG drug entry for Gleevec (D01441) with links to the KEGG pathway map for chronic myeloid leukemia (hsa05220) containing the target molecule and the KEGG drug structure map for antineoplastics–protein kinase inhibitors (map07045). View Image -
Figure 1.12.7 KEGG disease entry for chronic myeloid leukemia (H0004) with links to its KEGG pathway map (hsa05220) and the BRITE hierarchy for human diseases (br08402). View Image -
Figure 1.12.8 The disease/drug mapping of the KEGG pathway map for Alzheimer's disease (hsadd05210), which reveals common genes with other neurodegenerative diseases shown in the BRITE hierarchy (br08402). View Image -
Figure 1.12.9 The BRITE hierarchy for G protein–coupled receptors (ko04030) and its human‐specific version (hsa04030). View Image -
Figure 1.12.10 The BRITE hierarchy for the Anatomical Therapeutic Chemical (ATC) Classification (br08303). View Image -
Figure 1.12.11 The KEGG GENES entry for cystic fibrosis transmembrane conductance regulator (CFTR) in human (hsa:1080). View Image -
Figure 1.12.12 The KEGG SSDB gene cluster search result for nitrate transport protein NrtC in Synechocystis sp. PCC 6803 (syn:sll1452). View Image -
Figure 1.12.13 The KEGG ORTHOLOGY (KO) entry for cystic fibrosis transmembrane conductance regulator (K05031) and its taxonomy mapping. View Image -
Figure 1.12.14 The KEGG GENOME entry for Escherichia coli O157:H7 EDL933 (EHEC) and its related strains shown in the KEGG BRITE hierarchy for KEGG organisms (br08601). View Image -
Figure 1.12.15 The KEGG COMPOUND entry for L ‐lysine (C0047) and the KEGG GLYCAN entry for CD65 (G00197). View Image -
Figure 1.12.16 The KEGG REACTION entry for EC 2.3.1.1 (R00259), the KEGG RPAIR entry for the main reactant pair (RP04458), and the KEGG RCLASS entry for the corresponding reaction class (RC0064). View Image -
Figure 1.12.17 The KEGG MODULE entry for the first carbon oxidation in the citrate cycle (M0010) with its location shown in the pathway map (map0020). View Image -
Figure 1.12.18 An example of the Color Pathway tool in KEGG Mapper. The stage‐dependent pathways for chronic myeloid leukemia (CML) are shown as snapshots on the cancer overview map (hsa05200). Here all pathways involved in CML are marked. View Image -
Figure 1.12.19 An example of the Join Brite tool in KEGG Mapper. The receptor‐ligand relation data is mapped on the BRITE hierarchy for G protein–coupled receptors (ko04030), where the result is shown in an additional hierarchy level. View Image -
Figure 1.12.20 The 3D viewer tool in KEGG Atlas. The somatic mutation frequency data for colorectal cancer is shown on top of the cancer overview map (hsa05200). View Image
Videos
Literature Cited
| Literature Cited | |
| Aoki, K.F., Yamaguchi, A., Ueda, N., Akutsu, T., Mamitsuka, H., Goto, S., and Kanehisa, M. 2004. KCaM (KEGG Carbohydrate Matcher): A software tool for analyzing the structures of carbohydrate sugar chains. Nucleic Acids Res. 32:W267‐W272. | |
| Goto, S., Okuno, Y., Hattori, M., Nishioka, T., and Kanehisa, M. 2002. LIGAND: Database of chemical compounds and reactions in biological pathways. Nucleic Acids Res. 30:402‐404. | |
| Hattori, M., Okuno, Y., Goto, S., and Kanehisa, M. 2003. Development of a chemical structure comparison method for integrated analysis of chemical and genomic information in the metabolic pathways. J. Am. Chem. Soc. 125:11853‐11865. | |
| Hattori, M., Tanaka, N., Kanehisa, M., and Goto, S. 2010. SIMCOMP/SUBCOMP: Chemical structure search servers for network analyses. Nucleic Acids Res. 38:W652‐W656. | |
| Kanehisa, M. 1997. A database for post‐genome analysis. Trends Genet. 13:375‐376. | |
| Kanehisa, M. and Goto, S. 2000. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 28:27‐30. | |
| Kanehisa, M., Goto, S., Kawashima, S., and Nakaya, A. 2002. The KEGG databases at GenomeNet. Nucleic Acids Res. 30:42‐46. | |
| Kanehisa, M., Goto, S., Kawashima, S., Okuno, Y., and Hattori, M. 2004. The KEGG resource for deciphering the genome. Nucleic Acids Res. 32:D277‐D280. | |
| Kanehisa,M., Goto, S., Hattori, M., Aoki‐Kinoshita, K.F., Itoh, M., Kawashima, S., Katayama, T., Araki, M., and Hirakawa, M. 2006. From genomics to chemical genomics: New developments in KEGG. Nucleic Acids Res. 34:D354‐D357. | |
| Kanehisa, M., Araki, M., Goto, S., Hattori, M., Hirakawa, M., Itoh, M., Katayama, T., Kawashima, S., Okuda, S., Tokimatsu, T., and Yamanishi, Y. 2008. KEGG for linking genomes to life and the environment. Nucleic Acids Res. 36:D480‐D484. | |
| Kanehisa, M., Goto, S., Furumichi, M., Tanabe, M., and Hirakawa, M. 2010. KEGG for representation and analysis of molecular networks involving diseases and drugs. Nucleic Acids Res. 38:D355‐D360. | |
| Kanehisa, M., Goto, S., Sato, Y., Furumichi, M., and Tanabe, M. 2012. KEGG for integration and interpretation of large‐scale molecular data sets. Nucleic Acids Res. 40:D109‐D114. | |
| Kotera, M., Okuno, Y., Hattori, M., Goto, S., and Kanehisa, M. 2004. Computational assignment of the EC numbers for genomic‐scale analysis of enzymatic reactions. J. Am. Chem. Soc. 126:16487‐16498. | |
| McDonald, A.G., Boyce, S., and Tipton, K.F. 2009. ExplorEnz: The primary source of the IUBMB enzyme list. Nucleic Acids Res. 37:D593‐D597. | |
| Moriya, Y., Itoh, M., Okuda, S., Yoshizawa, A., and Kanehisa, M. 2007. KAAS: An automatic genome annotation and pathway reconstruction server. Nucleic Acids Res. 35:W182‐W185. | |
| Moriya, Y., Shigemizu, D., Hattori, M., Tokimatsu, T., Kotera, M., Goto, S., and Kanehisa, M. 2010. PathPred: An enzyme‐catalyzed metabolic pathway prediction server. Nucleic Acids Res. 38:W138‐W143. | |
| Pruitt, K.D., Tatusova, T., Brown, G.R., and Maglott, D.R. 2012. NCBI Reference Sequences (RefSeq): Current status, new features and genome annotation policy. Nucleic Acids Res. 40:D130‐D135. | |
| Takarabe, M., Shigemizu, D., Kotera, M., Goto, S., and Kanehisa, M. 2011. Network‐based analysis and characterization of adverse drug‐drug interactions. J. Chem. Inf. Model. 51:2977‐2985. |
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