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Advances in pre-processing and model generation for mass spectrometric data analysis Schleif, Frank Michael Similarity measures functional data proteomics mass spectrometry pre-processing,wavelet analysis generalized peak list 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. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Frank Michael Schleif 2007 Is Part Of Dagstuhl Seminar Proceedings, Volume 7131, Similarity-based Clustering and its Application to Medicine and Biology (2007) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/DagSemProc.07131.3 urn:nbn:de:0030-drops-11329 https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.07131.3 eng https://creativecommons.org/licenses/by/4.0/legalcode