| First Authors | |
|---|---|
| Authors | Lorenzo Duso, Christoph Zechner |
| Corresponding Authors | |
| Last Authors | Christoph Zechner |
| Conference Proceedings Volume Title | 2019 IEEE 58th Conference on Decision and Control (CDC) |
| Series Title | |
| Conference Name | 58th IEEE Conference on Decision and Control, CDC 2019 |
| Conference Location | Acropolis Convention CentreNice; France |
| Conference Start Date | 2019-12-11 |
| Conference End Date | 2019-12-13 |
| Chapter Number | |
| Publisher | IEEE |
| Conference Proceedings Editors | Carlos A. Canudas de Wit |
| ISBN | 978-172811398-2 |
| First Page | 6610 |
| Last Page | 6615 |
| Open Access | false |
| Print Publication Date | 2019-12-13 |
| Online Publication Date | |
| 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. |
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| Affiliated With | Zechner, CSBD |
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| Publication Status | Published |
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| DOI | 10.1109/CDC40024.2019.9029316 |
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| Display Publisher Download Only | false |
| Visible On MPI-CBG Website | true |
| PDF Downloadable | true |
| Created By | thuem |
| Added Date | 2020-05-19 |
| Last Edited By | herbst |
| Last Edited Date | 2021-05-10 18:50:47.091 |
| Library ID | 7676 |
| Document ID | |
| Entry Complete | true |
| eDoc Compliant | true |
| Include in Edoc Report | true |
| In Pure | false |
| Ready for eDoc Export | false |
| Author Affiliations Complete | true |
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