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  Moment-based analysis of biochemical networks in a heterogeneous population of communicating cells.

Gonzales, D. T., Tang, T.-Y.-D., & Zechner, C. (2019). Moment-based analysis of biochemical networks in a heterogeneous population of communicating cells. In C. A. Canudas de Wit (Ed.), 2019 IEEE 58th Conference on Decision and Control (CDC) (pp. 939-944). Piscataway, N.J.: IEEE.

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Datensatz-Permalink: https://hdl.handle.net/21.11116/0000-0006-7CFC-4 Versions-Permalink: https://hdl.handle.net/21.11116/0000-0006-7CFD-3
Genre: Konferenzbeitrag

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 Urheber:
Gonzales, David Thomas1, Autor           
Tang, T-Y Dora1, Autor           
Zechner, Christoph1, Autor           
Affiliations:
1Max Planck Institute for Molecular Cell Biology and Genetics, Max Planck Society, ou_2340692              

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Schlagwörter: -
 Zusammenfassung: 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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 Datum: 2019-12-13
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: DOI: 10.1109/CDC40024.2019.9029457
Anderer: cbg-7675
 Art des Abschluß: -

Veranstaltung

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Titel: 58th IEEE Conference on Decision and Control, CDC 2019
Veranstaltungsort: Acropolis Convention CentreNice; France
Start-/Enddatum: 2019-12-11 - 2019-12-13

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Titel: 2019 IEEE 58th Conference on Decision and Control (CDC)
Genre der Quelle: Konferenzband
 Urheber:
Canudas de Wit, Carlos A., Herausgeber
Affiliations:
-
Ort, Verlag, Ausgabe: Piscataway, N.J. : IEEE
Seiten: - Band / Heft: 2019 IEEE 58th Conference on Decision and Control (CDC) Artikelnummer: - Start- / Endseite: 939 - 944 Identifikator: ISBN: 978-172811398-2