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Proceedings Paper

Proteomic data analysis of glioma cancer stem-cell lines based on novel nonlinear dimensional data reduction techniques
Author(s): Sylvain Lespinats; Katja Pinker-Domenig; Georg Wengert; Ivo Houben; Marc Lobbes; Andreas Stadlbauer; Anke Meyer-Bäse
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Paper Abstract

Glioma-derived cancer stem cells (GSCs) are tumor-initiating cells and may be refractory to radiation and chemotherapy and thus have important implications for tumor biology and therapeutics. The analysis and interpretation of large proteomic data sets requires the development of new data mining and visualization approaches. Traditional techniques are insufficient to interpret and visualize these resulting experimental data. The emphasis of this paper lies in the application of novel approaches for the visualization, clustering and projection representation to unveil hidden data structures relevant for the accurate interpretation of biological experiments. These qualitative and quantitative methods are applied to the proteomic analysis of data sets derived from the GSCs. The achieved clustering and visualization results provide a more detailed insight into the protein-level fold changes and putative upstream regulators for the GSCs. However the extracted molecular information is insufficient in classifying GSCs and paving the pathway to an improved therapeutics of the heterogeneous glioma.

Paper Details

Date Published: 12 July 2016
PDF: 8 pages
Proc. SPIE 9871, Sensing and Analysis Technologies for Biomedical and Cognitive Applications 2016, 98710T (12 July 2016); doi: 10.1117/12.2229133
Show Author Affiliations
Sylvain Lespinats, Institut National de l'Energie Solaire (France)
Katja Pinker-Domenig, Medical Univ. of Vienna (Austria)
Memorial Sloan-Kettering Cancer Ctr. (United States)
Georg Wengert, Medical Univ. of Vienna (Austria)
Ivo Houben, Maastricht Univ. Medical Ctr. (Netherlands)
Marc Lobbes, Maastricht Univ. Medical Ctr. (Netherlands)
Andreas Stadlbauer, Friedrich-Alexander-Univ. of Erlangen-Nürnberg (Germany)
Anke Meyer-Bäse, Maastricht Univ. Medical Ctr. (Netherlands)
Florida State Univ. (United States)

Published in SPIE Proceedings Vol. 9871:
Sensing and Analysis Technologies for Biomedical and Cognitive Applications 2016
Liyi Dai; Yufeng Zheng; Henry Chu; Anke D. Meyer-Bäse, Editor(s)

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