Computational techniques to the topology and dynamics of lipidomic networks found in glioblastoma cells

Anke Meyer-Bäse, Robert Görke, Huan He, Mark Emmett, Alan G. Marshall, Charles A. Conrad

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

Abstract

Newly emerging advances in both measurement as well as bio-inspired computation techniques have facilitated the development of so-called lipidomics technologies and offer an excellent opportunity to understand regulation at the molecular level in many diseases such as cancer. The analysis and the understanding of the global interactional behavior of lipidomic networks remains a challenging task and can not be accomplished solely based on intuitive reasoning. The present contribution aims at developing novel computational approaches to assess the topological and functional aspects of lipidomic networks and discusses their benefits compared to recently proposed techniques. Graph-clustering methods are introduced as powerful correlation networks which enable a simultaneous exploration and visualization of co-regulation in glioblastoma data. The dynamic description of the lipidomic network is given through multi-mode nonlinear autonomous stochastic systems to model the interactions at the molecular level and to study the success of novel gene therapies for eradicating the aggressive glioblastoma. These new paradigms are providing unique "fingerprints" by revealing how the intricate interactions at the lipidome level can be employed to induce apoptosis (cell death) and are thus opening a new window to biomedical frontiers.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
Volume7704
DOIs
StatePublished - 2010
Externally publishedYes
EventEvolutionary and Bio-Inspired Computation: Theory and Applications IV - Orlando, FL, United States
Duration: Apr 7 2010Apr 8 2010

Other

OtherEvolutionary and Bio-Inspired Computation: Theory and Applications IV
CountryUnited States
CityOrlando, FL
Period4/7/104/8/10

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Keywords

  • Correlations
  • Glioblastoma
  • Graph clustering network
  • Langevin-type equation
  • Lipidomics
  • Stochastic simulations

ASJC Scopus subject areas

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

Cite this

Meyer-Bäse, A., Görke, R., He, H., Emmett, M., Marshall, A. G., & Conrad, C. A. (2010). Computational techniques to the topology and dynamics of lipidomic networks found in glioblastoma cells. In Proceedings of SPIE - The International Society for Optical Engineering (Vol. 7704). [770406] https://doi.org/10.1117/12.849903