Large-scale modeling of cancer signaling: Mechanistic modeling meets Big Data

An abstract of a study by Frohlich et al on mechanistic modeling and big data for large-scale modeling of cancer signaling is presented. A system biological approach for the drug response prediction is used. A generic large-scale mechanistic dynamic model was developed covering dozens of cancer asso...

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Bibliographic Details
Published in:European journal of cancer (1990) 2016-12, Vol.69, p.S44-S44
Main Authors: Fröhlich, F, Shadrin, A, Kessler, T, Wierling, C, Heinig, M, Theis, F.J, Lange, B, Lehrach, H, Hasenauer, J
Format: Article
Language:English
Subjects:
Big Data
Cancer
Data management
Differential equations
Dynamic models
Gene expression
Hematology, Oncology and Palliative Medicine
Modelling
Ordinary differential equations
Precision medicine
Scale models
Signaling
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Summary:An abstract of a study by Frohlich et al on mechanistic modeling and big data for large-scale modeling of cancer signaling is presented. A system biological approach for the drug response prediction is used. A generic large-scale mechanistic dynamic model was developed covering dozens of cancer associate signaling pathways. The ordinary differential equation model can be individualized using exome and transcriptome sequencing data-carrying information about mutation status and expression levels. The study concludes that its results demonstrate the potential of large-scale mechanistic modeling for drug selection in personalized therapy.
ISSN:0959-8049
1879-0852
DOI:10.1016/S0959-8049(16)32716-2