Mathematical models of signaling networks and their application to disease
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If you have a question about this talk, please contact Danielle Stretch.
Cells are equipped with complex molecular networks that process
external information, allowing cells to react to their environment.
Deregulation of this signal transduction system is involved in the
development of a variety of diseases such as diabetes and cancer. In
my talk I will discuss how to study these molecular networks using a
combination of high-throughput proteomics and mathematical modelling.
As a case study, I will show an application to hepatocellular
carcinoma, the most frequent form of liver cancer. Mathematical
models specific for healthy liver cells and hepatocellular carcinoma
cell lines were generated and compared, revealing three key
differences in the wiring of their signalling pathways. These
differences are potential targets for new therapies.
This talk is part of the Computational and Systems Biology series.
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