Advances in pre-processing and model generation for mass spectrometric data analysis

Schleif, Frank Michael

doi:10.4230/DagSemProc.07131.3

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Advances in pre-processing and model generation for mass spectrometric data analysis

Author Frank Michael Schleif

Part of: Volume: Dagstuhl Seminar Proceedings, Volume 7131
Part of: Series: Dagstuhl Seminar Proceedings (DagSemProc)
License: Creative Commons Attribution 4.0 International license
Publication Date: 2007-09-12

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DagSemProc.07131.3.pdf

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Document Identifiers

DOI: 10.4230/DagSemProc.07131.3
URN: urn:nbn:de:0030-drops-11329

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Keywords

Similarity measures
functional data
proteomics
mass spectrometry
pre-processing,wavelet analysis
generalized peak list

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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.

Cite As Get BibTex

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

Author Details

Frank Michael Schleif

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