| First Authors | David Thomas Gonzales |
|---|---|
| Authors | David Thomas Gonzales, T-Y Dora Tang, Christoph Zechner |
| Corresponding Authors | Christoph Zechner |
| 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 |
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| Publisher | IEEE |
| Conference Proceedings Editors | Carlos A. Canudas de Wit |
| ISBN | 978-172811398-2 |
| First Page | 939 |
| Last Page | 944 |
| Open Access | false |
| Print Publication Date | 2019-12-13 |
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| Abstract | Cells can utilize chemical communication to exchange information and coordinate their behavior in the presence of noise. Communication can reduce noise to shape a collective response, or amplify noise to generate distinct phenotypic subpopulations. Here we discuss a moment-based approach to study how cell-cell communication affects noise in biochemical networks that arises from both intrinsic and extrinsic sources. We derive a system of approximate differential equations that captures lower-order moments of a population of cells, which communicate by secreting and sensing a diffusing molecule. Since the number of obtained equations grows combinatorially with number of considered cells, we employ a previously proposed model reduction technique, which exploits symmetries in the underlying moment dynamics. Importantly, the number of equations obtained in this way is independent of the number of considered cells such that the method scales to arbitrary population sizes. Based on this approach, we study how cell-cell communication affects population variability in several biochemical networks. Moreover, we analyze the accuracy and computational efficiency of the moment-based approximation by comparing it with moments obtained from stochastic simulations. |
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| Affiliated With | Tang, Zechner, CSBD |
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| Publication Status | Published |
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| DOI | 10.1109/CDC40024.2019.9029457 |
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| Created By | thuem |
| Added Date | 2020-05-19 |
| Last Edited By | herbst |
| Last Edited Date | 2021-05-10 18:49:56.616 |
| Library ID | 7675 |
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| Entry Complete | true |
| eDoc Compliant | true |
| Include in Edoc Report | true |
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| Ready for eDoc Export | false |
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