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Proceedings Paper

Visual analysis and dynamical control of phosphoproteomic networks
Author(s): Anke Meyer-Bäse; Robert Görke; Marc Lobbes; Mark R. Emmett; Carol L. Nilsson
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Paper Abstract

This paper presents novel graph algorithms and modern control solutions applied to the graph networks resulting from specific experiments to discover disease-related pathways and drug targets in glioma cancer stem cells (GSCs). The theoretical framework applies to many other high-throughput data from experiments relevant to a variety of diseases. In addition to developing novel graph and control networks to predict therapeutic targets, these algorithms will provide biochemists with techniques to identify more metabolic regions and biological pathways for complex diseases, and design and test novel therapeutic solutions.

Paper Details

Date Published: 29 May 2013
PDF: 8 pages
Proc. SPIE 8750, Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XI, 87500X (29 May 2013); doi: 10.1117/12.2019381
Show Author Affiliations
Anke Meyer-Bäse, The Florida State Univ. (United States)
Robert Görke, The Florida State Univ. (United States)
Marc Lobbes, Maastricht Univ. Medical Ctr. (Netherlands)
Mark R. Emmett, The Univ. of Texas Medical Branch (United States)
Carol L. Nilsson, The Univ. of Texas Medical Branch (United States)


Published in SPIE Proceedings Vol. 8750:
Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XI
Harold H. Szu, Editor(s)

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