Signal flow control of complex signaling networks

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Complex disease such as cancer is often caused by genetic mutations that eventually alter the signal flow in the intra-cellular signaling network and result in different cell fate. Therefore, it is crucial to identify control targets that can most effectively block such unwanted signal flow. For this purpose, systems biological analysis provides a useful framework, but mathematical modeling of complicated signaling networks requires massive time-series measurements of signaling protein activity levels for accurate estimation of kinetic parameter values or regulatory logics. Here, we present a novel method, called SFC (Signal Flow Control), for identifying control targets without the information of kinetic parameter values or regulatory logics. Our method requires only the structural information of a signaling network and is based on the topological estimation of signal flow through the network. SFC will be particularly useful for a large-scale signaling network to which parameter estimation or inference of regulatory logics is no longer applicable in practice. The identified control targets have significant implication in drug development as they can be putative drug targets.
Publisher
NATURE PUBLISHING GROUP
Issue Date
2019-10
Language
English
Article Type
Article
Citation

SCIENTIFIC REPORTS, v.9

ISSN
2045-2322
DOI
10.1038/s41598-019-50790-0
URI
http://hdl.handle.net/10203/268037
Appears in Collection
BiS-Journal Papers(저널논문)
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