Flexibility in noisy cell-to-cell information dynamics

The exchange of molecules allows cells to exchange information. How robust is the information to changes in cell parameters? We use a mapping between the stochastic dynamics of two cells sharing a stimulatory molecule and parameters akin to an extension of Landau's equilibrium phase transition theory. We show that different single-cell dynamics lead to the same dynamical response—a flexibility that cells can use. The companion equilibrium Landau model behaves similarly, thereby describing the dynamics of information in a broad class of models with coupled order parameters. Published by the American Physical Society 2024

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Publication Details

Journal
Physical Review Research
Published
2024-12-10
DOI
https://doi.org/10.1103/physrevresearch.6.043252
Primary Topic
Gene Regulatory Network Analysis
Type
article
Field-Weighted Citation Impact
0.00

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article

Flexibility in noisy cell-to-cell information dynamics

Ismail Qunbar, Amir Erez, Michael Vennettilli
Physical Review Research
Gene Regulatory Network Analysis
article

Flexibility in noisy cell-to-cell information dynamics

Ismail Qunbar, Amir Erez, Michael Vennettilli
article en

Abstract

The exchange of molecules allows cells to exchange information. How robust is the information to changes in cell parameters? We use a mapping between the stochastic dynamics of two cells sharing a stimulatory molecule and parameters akin to an extension of Landau's equilibrium phase transition theory. We show that different single-cell dynamics lead to the same dynamical response—a flexibility that cells can use. The companion equilibrium Landau model behaves similarly, thereby describing the dynamics of information in a broad class of models with coupled order parameters. Published by the American Physical Society 2024

Physical Review ResearchVol. 6(4)
Hebrew University of Jerusalem (IL), Institute for Atomic and Molecular Physics (NL)
Nederlandse Organisatie voor Wetenschappelijk Onderzoek
Openalex Percentile: Top 80%
Gene Regulatory Network Analysis
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