Dynamical complex network theory applied to the therapeutics of brain malignancies

Anke Meyer-Bäse; Daniel Fratte; Adrian Barbu; Katja Pinker-Domenig

doi:10.1117/12.2181816

20 May 2015 Dynamical complex network theory applied to the therapeutics of brain malignancies

Anke Meyer-Bäse, Daniel Fratte, Adrian Barbu, Katja Pinker-Domenig

Proceedings Volume 9496, Independent Component Analyses, Compressive Sampling, Large Data Analyses (LDA), Neural Networks, Biosystems, and Nanoengineering XIII; 949608 (2015) https://doi.org/10.1117/12.2181816
Event: SPIE Sensing Technology + Applications, 2015, Baltimore, MD, United States

Abstract

An important problem in modern therapeutics at the metabolomic, transcriptomic or phosphoproteomic level remains to identify therapeutic targets in a plentitude of high-throughput data from experiments relevant to a variety of diseases. This paper presents the application of 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 frameworks provides us with the minimal number of ”driver nodes” necessary to determine the full control over the obtained graph network in order to provide a change in the network’s dynamics from an initial state (disease) to a desired state (non-disease). The achieved results will provide biochemists with techniques to identify more metabolic regions and biological pathways for complex diseases, and design and test novel therapeutic solutions.

Citation Download Citation

Anke Meyer-Bäse, Daniel Fratte, Adrian Barbu, and Katja Pinker-Domenig "Dynamical complex network theory applied to the therapeutics of brain malignancies", Proc. SPIE 9496, Independent Component Analyses, Compressive Sampling, Large Data Analyses (LDA), Neural Networks, Biosystems, and Nanoengineering XIII, 949608 (20 May 2015); https://doi.org/10.1117/12.2181816

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available