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KEGG and GenomeNet, New Developments, Metagenomic Analysis

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Encyclopedia of Metagenomics

Synonyms

GenomeNet; Kyoto Encyclopedia of Genes and Genomes

Definition

KEGG (Kyoto Encyclopedia of Genes and Genomes) is a database resource representing biological systems, such as the cell, the organism, and the ecosystem, from molecular-level information, especially large-scale molecular datasets generated by genome sequencing and other high-throughput experimental technologies. GenomeNet is database and computational services for genome research and related research areas in biomedical sciences, operated by the Kyoto University Bioinformatics Center in Japan. Both services work in collaboration putting a special focus on the visualization and interpretation of large amount of data, such as metagenome sequence data, derived from high-throughput measurement techniques.

Introduction

The number of complete genomes has been increasing dramatically. From the completion of the influenza genome in 1995, it took about 13 years (1995–2008) to complete a total of 500 species. The number of...

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References

  • Fujibuchi W, Sato K, Ogata H, Goto S, Kanehisa M. KEGG and DBGET/LinkDB: integration of biological relationships in divergent molecular biology data. In: Knowledge sharing across biological and medical knowledge based systems, Technical report WS-98-04. AAAI Press; 1998. p. 35–40. http://www.aaai.org/Papers/Workshops/1998/WS-98-04/WS98-04-006.pdf

  • Kanehisa M, Goto S, Kawashima S, Nakaya A. The KEGG databases at GenomeNet. Nucl Acids Res. 2002;30(1):42–6.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Kanehisa M, Goto S, Sato Y, Furumichi M, Tanabe M. KEGG for integration and interpretation of large-scale molecular data sets. Nucleic Acids Res. 2012;40(Database issue):D109–14. Epub 2011 Nov 10.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Kotera M, Hirakawa M, Tokimatsu T, Goto S, Kanehisa M. The KEGG databases and tools facilitating omics analysis: latest developments involving human diseases and pharmaceuticals. Chapter 2 In: Wang J, Choon Tan A, Tian T, editors. Next generation microarray bioinformatics. Springer; 2012. ISBN 978-1-61779-399-8. doi:10.1007/978-1-61779-400-1_2 [PMID: 22130871]. http://link.springer.com/protocol/10.1007%2F978-1-61779-400-1_2

  • Moriya Y, Itoh M, Okuda S, Yoshizawa A, Kanehisa M. KAAS: an automatic genome annotation and pathway reconstruction server. Nucleic Acids Res. 2007;35:W182–5.

    Article  PubMed Central  PubMed  Google Scholar 

  • Tokimatsu T, Kotera M, Goto S, Kanehisa M. KEGG and GenomeNet resources for predicting protein function from omics data including KEGG PLANT resource. Chapter 14. In: Kihara D, editor. Protein function prediction for omics era. Springer; 2011. p. 271–288. http://link.springer.com/chapter/10.1007%2F978-94-007-0881-5_14

  • Wheelock CE, Wheelock AM, Kawashima S, Diez D, Kanehisa M, van Erk M, Kleemann R, Haeggstrom JZ, Goto S. Systems biology approaches and pathway tools for investigating cardiovascular disease. Mol Biosyst. 2009a;5:588–602.

    Article  CAS  PubMed  Google Scholar 

  • Wheelock CE, Goto S, Yetukuri L, D’Alexandri FL, Klukas C, Schreiber F, Oresic M. Bioinformatics strategies for the analysis of lipids. Methods Mol Biol. 2009b;580:339–68.

    CAS  PubMed  Google Scholar 

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Correspondence to Masaaki Kotera .

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Kotera, M., Moriya, Y., Tokimatsu, T., Kanehisa, M., Goto, S. (2013). KEGG and GenomeNet, New Developments, Metagenomic Analysis. In: Nelson, K. (eds) Encyclopedia of Metagenomics. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6418-1_694-6

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  • DOI: https://doi.org/10.1007/978-1-4614-6418-1_694-6

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