Mathematical Tools and Statistical Techniques for Proteomic Data Mining

نویسندگان

  • Don Hong
  • Shi Yin Qin
  • Fengqing Zhang
چکیده

Proteomics is the study of and the search for information about proteins. The development of mass spectrometry (MS) such as matrix-assisted laser desorption ionization (MALDI) time-of-flight (TOF) MS and imaging mass spectrometry (IMS), greatly speeds up proteomics studies. At the same time, the MS and IMS applications in medical science give rise to many challenges in mathematics and statistics regarding to the MS and IMS data analysis including data preprocessing, classification, and biomarker discovery. In this paper, we give a review of recent development of mathematical techniques and statistical tools for MS and IMS based proteomic data mining including wavelet based MS data preprocessing and multivariate statistical methods for IMS data classification and biomarker discovery.

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تاریخ انتشار 2010