
Proceedings Paper
Proteomic data analysis of glioma cancer stem-cell lines based on novel nonlinear dimensional data reduction techniquesFormat | Member Price | Non-Member Price |
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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
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)
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)
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)
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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