Advertisement

A Grid Service Based on Suffix Trees for Pattern Extraction from Mass Spectrometry Proteomics Data

  • M. Cannataro
  • P. Veltri
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4331)

Abstract

The paper presents a Grid Service allowing to detect and extract the longest common sub-spectrum among a set of mass spectrometry spectra data. The system uses a novel pattern extraction algorithm named LCSS (Longest Common Spectra SubString) that adapts a very popular string matching technique based on Suffix Trees to spectra data. The basic LCSS algorithm made available as a Grid Service is used to implement a pattern extraction workflow on mass spectrometry dataset. First experimental results are presented.

Keywords

Pattern Extraction Mass Spectrometry Suffix Tree Grid Services 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Aebersold, R., Mann, M.: Mass spectrometry-based proteomics. Nature 422, 198–207 (2003)CrossRefGoogle Scholar
  2. 2.
    Cannataro, M., Guzzi, P., Mazza, T., Tradigo, G., Veltri, P.: Preprocessing of mass spectrometry proteomics data on the grid. In: CBMS 2005, pp. 549–554. IEEE Press, Los Alamitos (2005)Google Scholar
  3. 3.
    Cannataro, M., Guzzi, P., Mazza, T., Tradigo, G., Veltri, P.: Using ontologies for preprocessing and mining spectra data on the grid. Future Generation Comp. Syst. 23(1), 55–60 (2007)CrossRefGoogle Scholar
  4. 4.
    Alliance Globus. The globus project, http://www.globus.org/
  5. 5.
    Gopalakrishnan, V., William, E., Ranganathan, S., Bowser, R., Cudkowic, M.E., Novelli, M., Lattazi, W., Gambotto, A., Day, B.W.: Proteomic data mining challenges in identification of disease-specific biomarkers from variable resolution mass spectra. In: Proceedings of SIAM Bioinformatics Workshop 2004, Buena Vista, FL, April 2004, pp. 1–10 (2004)Google Scholar
  6. 6.
    Gusfield, D.: Algorithms on Strings, Trees, and Sequences: Computer Science and Computational Biology. Cambridge University Press, Cambridge (1997)zbMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • M. Cannataro
    • 1
  • P. Veltri
    • 1
  1. 1.University Magna Græcia of CatanzaroItaly

Personalised recommendations