Classification of Proteomic Signals by Block Kriging Error Matching

  • Tuan D. Pham
  • Dominik Beck
  • Miriam Brandl
  • Xiaobo Zhou
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5099)

Abstract

One of recent advances in biotechnology offers high-throughput mass-spectrometry data for disease detection, prevention, and biomarker discovery. In fact proteomics has recently become an attractive topic of research in biomedicine. Signal processing and pattern classification techniques are inherently essential for analyzing proteomic data. In this paper the estimation method of block kriging is utilized to derive an error matching strategy for classifying proteomic signals with a particular application to the prediction of cardiovascular events using clinical mass spectrometry data. The proposed block kriging based classification technique has been found to be superior to other recently developed methods.

Keywords

Proteomics mass spectral data block kriging signal processing classification distortion measures 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Tuan D. Pham
    • 1
  • Dominik Beck
    • 1
  • Miriam Brandl
    • 1
  • Xiaobo Zhou
    • 2
  1. 1.Bioinformatics Applications Research CenterJames Cook UniversityTownsvilleAustralia
  2. 2.HCNR Center for Bioinformatics, Harvard Medical School BostonUSA

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