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URN: urn:nbn:de:0030-drops-5427
URL: http://drops.dagstuhl.de/opus/volltexte/2006/542/

Conrad, Tim

New statistical algorithms for clinical proteomics

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Abstract

Background: Mass spectrometry based screening methods have been recently introduced into clinical proteomics. This boosts the development of a new approach for early disease detection: proteomic pattern analysis. Aim: Find, analyze and compare proteomic patterns in groups of patients having different properties such as disease status or epidemio-logical parameters (e.g. sex, age) with a new pipeline to enhance sensitivity and specificity. Problems: Mass data acquired from high-throughput platforms frequently are blurred and noisy. This extremely complicates the reliable identification of peaks in general and very small peaks below noise-level in particular. Approach: Apply sophisticated signal preprocessing steps followed by statistical analyzes to purge the raw data and enable the detection of real signals while maintaining information for tracebacks. Results: A new analysis pipeline has been developed capable of finding and analyzing peak patterns discriminating different groups of patients (e.g. male/female, cancer/healthy). First steps towards distributed computing approaches have been incorporated in the design.

BibTeX - Entry

@InProceedings{conrad:DSP:2006:542,
  author =	{Tim Conrad},
  title =	{New statistical algorithms for clinical proteomics},
  booktitle =	{Computational Proteomics},
  year =	{2006},
  editor =	{Christian G. Huber and Oliver Kohlbacher and Knut Reinert},
  number =	{05471},
  series =	{Dagstuhl Seminar Proceedings},
  ISSN =	{1862-4405},
  publisher =	{Internationales Begegnungs- und Forschungszentrum f{\"u}r Informatik (IBFI), Schloss Dagstuhl, Germany},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2006/542},
  annote =	{Keywords: MS, Mass Spectrometry, MALDI-TOF, Fingerprinting, Proteomics}
}

Keywords: MS, Mass Spectrometry, MALDI-TOF, Fingerprinting, Proteomics
Seminar: 05471 - Computational Proteomics
Issue date: 2006
Date of publication: 03.05.2006


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