Protein Structural Information Management Based on Spatial Concepts and Active Trigger Rules

  • Sung-Hee Park
  • Keun Ho Ryu
  • Hyeon S. Son
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2736)


A protein structure has four different levels of structures with spatial conformation and arrangement of peptide chains. Features of newly emerging protein structure data are extremely complex, large, multidimensional and incomplete. Therefore, it is necessary to develop approaches to manage protein structure data compared with management of conventional data in order to provide protein structural information for analysis applications.

We propose a new approach to manage protein structural information by using spatial object management and active database techniques. We introduce data modeling for protein structures using a geographic object model and version management of a protein sequence with trigger rules and show analysis structural information using topological and geometric operators.

Our experimental results show that applying spatial models and an active trigger to manage protein structure can efficiently support fast protein structure analysis by using spatial operations and a filter-refinement processing with a multi dimensional index.


Spatial Object Flat File Active Database Spatial Type Analyze Protein Structure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Park, S.H., Ryu, K.H., Son, H.S.: Modeling Protein Structures with Spatial Model for Structure Comparison. LNCS. Springer, Heidelberg (2003)Google Scholar
  2. 2.
    Park, S.H., Li, R.H., Ryu, K.H., Jeong, B.J., Son, H.S.: Modeling and Querying Protein Structure Based on Spatial Model. In: Proc. of Int. Conf. on Computer and information Science, Korea Information Processing, pp. 773–778 (2002)Google Scholar
  3. 3.
    Rigaus, P., School, M., Voisard, A.: Spatial Databases with application to GIS, pp. 29–61. Academic Press, San Diego (2002)Google Scholar
  4. 4.
    Oracle Spatial User’s Guide and Reference: Loading and Indexing Spatial Object Types. Release8.1.5, Oracle (2001) Google Scholar
  5. 5.
    Berman, H.M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T.N., Weissig, H., Shindyalov, I.N., Bourne, P.E.: The Protein Data bank. J. Nucleic Acids Research 28, 235–242 (2000)CrossRefGoogle Scholar
  6. 6.
    Higgins, D., Tailor, W.: Bioinfomatics: Sequence, Structure and databanks, 1st edn. Oxford University Press, New York (2000)Google Scholar
  7. 7.
    Ryu, K.H.: Genome database & EST database. J. Scientific & Technological Knowledge Infrastructure 10, 48–61 (2000)Google Scholar
  8. 8.
    Holm, L., Sander, C.: Dali/FSSP classification of three-dimensional protein folds. Nucleic Acids Research 25, 231–234 (1997)CrossRefGoogle Scholar
  9. 9.
    Levitt, M.: Competitive assessment of protein fold recognition and alignment accuracy. Int. J. Proteins Struct. Funct. Genet. 1, 92–104 (1997)CrossRefGoogle Scholar
  10. 10.
    Stultz, M., Nambudripad, R., Lathrop, H., White, V.: Predicting protein structure with probabilistic models. Int. J. Adv. Mol. Cell Biol. 22B, 447–506 (1997)CrossRefGoogle Scholar
  11. 11.
    Alexandrov, N., Nussinov, R., Zimmer, M.: Fast Protein fold recognition via sequence to structure alignment and contact capacity protentials. In: Proc. of Pac. Symp. on Biocomput., pp. 53–72 (1996)Google Scholar
  12. 12.
    Garnier, J., Gibrat, J.-F., Robson, B.: GOR method for predicting protein secondary structure from amino acid sequence. J. Method Enzymol. 266, 540–553 (1996)CrossRefGoogle Scholar
  13. 13.
    Widom, J., Ceri, S.: Introduction to Active Database Systems. In: Active Database Systems: Triggers and Rules For Advanced Database Processing, pp. 1–41. Morgan Kaufmann, San Francisco (1996)Google Scholar
  14. 14.
    Clementini, E., Felice, P., van Oostrom, P.: A small set of formal topological relationships suitable for end-user interaction. In: Proc. of Spatial Databases Symp., Singapore, pp. 277–295 (1993)Google Scholar
  15. 15.
    Altschul, S.F., Carrol, R.J., Lipman, D.J.: Basic local alignment search tool. J. Mol. Biol. 215, 403–410 (1990)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Sung-Hee Park
    • 1
  • Keun Ho Ryu
    • 1
  • Hyeon S. Son
    • 2
  1. 1.Database LaboratoryChungbuk National UniversityHungduck-ku, CheongjuKorea
  2. 2.Center for Computational Biology & BioinformaticsKorea Institute of Science and Technology InformationDaejeon cityKorea

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