DagSemProc.07131.3.pdf
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Advances in pre-processing and model generation for mass spectrometric data analysis
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Dagstuhl Seminar Proceedings, Volume 7131
Series: Dagstuhl Seminar Proceedings (DagSemProc) - License:
Creative Commons Attribution 4.0 International license
- Publication Date: 2007-09-12
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Frank Michael Schleif. Advances in pre-processing and model generation for mass spectrometric data analysis. In Similarity-based Clustering and its Application to Medicine and Biology. Dagstuhl Seminar Proceedings, Volume 7131, pp. 1-24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2007)
https://doi.org/10.4230/DagSemProc.07131.3
https://doi.org/10.4230/DagSemProc.07131.3
Abstract
The analysis of complex signals as obtained by mass spectrometric measurements
is complicated and needs an appropriate representation of the data. Thereby
the kind of preprocessing, feature extraction as well as the used similarity measure
are of particular importance. Focusing on biomarker analysis and taking the
functional nature of the data into account this task is even more complicated.
A new mass spectrometry tailored data preprocessing is shown, discussed and analyzed in
a clinical proteom study compared to a standard setting.
Keywords
- Similarity measures
- functional data
- proteomics
- mass spectrometry
- pre-processing,wavelet analysis
- generalized peak list
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