SABIO-RK: Integration and Curation of Reaction Kinetics Data

  • Ulrike Wittig
  • Martin Golebiewski
  • Renate Kania
  • Olga Krebs
  • Saqib Mir
  • Andreas Weidemann
  • Stefanie Anstein
  • Jasmin Saric
  • Isabel Rojas
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4075)

Abstract

Simulating networks of biochemical reactions require reliable kinetic data. In order to facilitate the access to such kinetic data we have developed SABIO-RK, a curated database with information about biochemical reactions and their kinetic properties. The data are manually extracted from literature and verified by curators, concerning standards, formats and controlled vocabularies. This process is supported by tools in a semi-automatic manner. SABIO-RK contains and merges information about reactions such as reactants and modifiers, organism, tissue and cellular location, as well as the kinetic properties of the reactions. The type of the kinetic mechanism, modes of inhibition or activation, and corresponding rate equations are presented together with their parameters and measured values, specifying the experimental conditions under which these were determined. Links to other databases enable the user to gather further information and to refer to the original publication. Information about reactions and their kinetic data can be exported to an SBML file, allowing users to employ the information as the basis for their simulation models.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Schomburg, I., Chang, A., Ebeling, C., Gremse, M., Heldt, C., Huhn, G., Schomburg, D.: BRENDA, the enzyme database: updates and major new developments. Nucleic Acids Res. 32, 431–433 (2004)CrossRefGoogle Scholar
  2. 2.
    Bairoch, A., Apweiler, R., Wu, C.H., Barker, W.C., Boeckmann, B., Ferro, S., Gasteiger, E., Huang, H., Lopez, R., Magrane, M., Martin, M.J., Natale, D.A., O’Donovan, C., Redaschi, N., Yeh, L.S.: The Universal Protein Resource (UniProt). Nucleic Acids Res. 33, 154–159 (2005)CrossRefGoogle Scholar
  3. 3.
    Le Novere, N., Bornstein, B., Broicher, A., Courtot, M., Donizelli, M., Dharuri, H., Li, L., Sauro, H., Schilstra, M., Shapiro, B., Snoep, J.L., Hucka, M.: BioModels Database: a free, centralized database of curated, published, quantitative kinetic models of biochemical and cellular systems. Nucleic Acids Res. 34, 689–691 (2006)CrossRefGoogle Scholar
  4. 4.
    Hucka, M., Finney, A., Sauro, H.M., Bolouri, H., Doyle, J.C., Kitano, H., Arkin, A.P., Bornstein, B.J., Bray, D., Cornish-Bowden, A., Cuellar, A.A., Dronov, S., Gilles, E.D., Ginkel, M., Gor, V., Goryanin, I.I., Hedley, W.J., Hodgman, T.C., Hofmeyr, J.H., Hunter, P.J., Juty, N.S., Kasberger, J.L., Kremling, A., Kummer, U., Le Novere, N., Loew, L.M., Lucio, D., Mendes, P., Minch, E., Mjolsness, E.D., Nakayama, Y., Nelson, M.R., Nielsen, P.F., Sakurada, T., Schaff, J.C., Shapiro, B.E., Shimizu, T.S., Spence, H.D., Stelling, J., Takahashi, K., Tomita, M., Wagner, J., Wang, J.: The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. Bioinformatics 19, 524–531 (2003)CrossRefGoogle Scholar
  5. 5.
    Rojas, I., Bernardi, L., Ratsch, E., Kania, R., Wittig, U., Saric, J.: A database system for the analysis of biochemical pathways. In Silico Biol. 2, p. 7 (2002)Google Scholar
  6. 6.
  7. 7.
    Kanehisa, M., Goto, S., Hattori, M., Aoki-Kinoshita, K.F., Itoh, M., Kawashima, S., Katayama, T., Araki, M., Hirakawa, M.: From genomics to chemical genomics: new developments in KEGG. Nucleic Acids Res. 7, 354–357 (2006)CrossRefGoogle Scholar
  8. 8.
  9. 9.
  10. 10.
    Anstein, S., Kremer, G., Reyle, U.: Identifying and Classifying Terms in the Life Sciences: The Case of Chemical Terminology. In: Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC) (to appear, 2006)Google Scholar
  11. 11.
  12. 12.
    Weininger, D.: SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules. J. Chem. Inf. Comput. Sci. 28, 31–36 (1988)Google Scholar
  13. 13.
    International System of Units (SI), http://www.bipm.fr/en/si/
  14. 14.
    Wittig, U., Weidemann, A., Kania, R., Peiss, C., Rojas, I.: Classification of chemical compounds to support complex queries in a pathway database. Comp. Funct. Genom. 5, 156–162 (2004)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Ulrike Wittig
    • 1
  • Martin Golebiewski
    • 1
  • Renate Kania
    • 1
  • Olga Krebs
    • 1
  • Saqib Mir
    • 1
  • Andreas Weidemann
    • 1
  • Stefanie Anstein
    • 1
  • Jasmin Saric
    • 1
  • Isabel Rojas
    • 1
  1. 1.Scientific Databases and Visualization GroupEML Research gGmbHHeidelbergGermany

Personalised recommendations