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Proceedings Paper

Novel insights into the lipidome of glioblastoma cells based on a combined PLSR and DD-HDS computational analysis
Author(s): S. Lespinats; Anke Meyer-Bäse; Huan He; Alan G. Marshall; Charles A. Conrad; Mark R. Emmett
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Paper Abstract

Partial Least Square Regression (PLSR) and Data-Driven High Dimensional Scaling (DD-HDS) are employed for the prediction and the visualization of changes in polar lipid expression induced by different combinations of wild-type (wt) p53 gene therapy and SN38 chemotherapy of U87 MG glioblastoma cells. A very detailed analysis of the gangliosides reveals that certain gangliosides of GM3 or GD1-type have unique properties not shared by the others. In summary, this preliminary work shows that data mining techniques are able to determine the modulation of gangliosides by different treatment combinations.

Paper Details

Date Published: 29 April 2009
PDF: 13 pages
Proc. SPIE 7347, Evolutionary and Bio-Inspired Computation: Theory and Applications III, 73470I (29 April 2009); doi: 10.1117/12.818295
Show Author Affiliations
S. Lespinats, UMR INSERM (France)
Univ. Paris Diderot (France)
Anke Meyer-Bäse, Florida State Univ. (United States)
Huan He, Florida State Univ. (United States)
National High Magnetic Field Lab. (United States)
Alan G. Marshall, Florida State Univ. (United States)
National High Magnetic Field Lab. (United States)
Charles A. Conrad, M.D. Anderson Cancer Ctr., Univ. of Texas, Houston (United States)
Mark R. Emmett, National High Magnetic Field Lab. (United States)


Published in SPIE Proceedings Vol. 7347:
Evolutionary and Bio-Inspired Computation: Theory and Applications III
Teresa H. O'Donnell; Misty Blowers; Kevin L. Priddy, Editor(s)

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