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Path mutual information for a class of biochemical reaction networks

Duso, L
•
Zechner, C
2019
  • conference object

Abstract
Living cells encode and transmit information in the temporal dynamics of signaling molecules. Gaining a quantitative understanding of how intracellular networks process dynamic signals requires measures that capture the interdependence between complete time trajectories of network components. Mutual information provides such a measure but its calculation in the context of stochastic reaction networks is associated with computational challenges. Here we propose a method to calculate the mutual information between complete time-continuous paths of two molecular species that interact with each other through chemical reactions. We demonstrate our approach using three simple case studies.
DOI
10.1109/CDC40024.2019.9029316
WOS
WOS:000560779006011
Archivio
https://hdl.handle.net/20.500.11767/145867
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85082441307
https://arxiv.org/abs/1904.01988
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