Novel insights into the lipidome of glioblastoma cells based on a combined PLSR and DD-HDS computational analysis

S. Lespinats, Anke Meyer-Baese, Huan He, Alan G. Marshall, Charles A. Conrad, Mark R. Emmett

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publicationEvolutionary and Bio-Inspired Computation
Subtitle of host publicationTheory and Applications III
DOIs
StatePublished - Dec 1 2009
EventEvolutionary and Bio-Inspired Computation: Theory and Applications III - Orlando, FL, United States
Duration: Apr 14 2009Apr 15 2009

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume7347
ISSN (Print)0277-786X

Other

OtherEvolutionary and Bio-Inspired Computation: Theory and Applications III
CountryUnited States
CityOrlando, FL
Period4/14/094/15/09

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Keywords

  • Data-Driven high dimensional scaling
  • Gangliosides
  • Glioblastoma
  • Partial least square regression

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Cite this

Lespinats, S., Meyer-Baese, A., He, H., Marshall, A. G., Conrad, C. A., & Emmett, M. R. (2009). Novel insights into the lipidome of glioblastoma cells based on a combined PLSR and DD-HDS computational analysis. In Evolutionary and Bio-Inspired Computation: Theory and Applications III [73470I] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 7347). https://doi.org/10.1117/12.818295