Chemical event chain model of coupled genetic oscillators
We introduce a stochastic model of coupled genetic oscillators in which chains of chemical events involved in gene regulation and expression are represented as sequences of Poisson processes. We characterize steady states by their frequency, their quality factor, and their synchrony by the oscillato...
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2018
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| Acceso en línea: | https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_24700045_v97_n3_p_Jorg http://hdl.handle.net/20.500.12110/paper_24700045_v97_n3_p_Jorg |
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paper:paper_24700045_v97_n3_p_Jorg |
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paper:paper_24700045_v97_n3_p_Jorg2023-06-08T16:36:45Z Chemical event chain model of coupled genetic oscillators Chains Gene expression Gene expression regulation Stochastic systems Cross correlations Distributed delays Genetic oscillators Isolated regions Parameter spaces Phase oscillators Stochastic oscillations Stochastic transitions Stochastic models biological model cells cytology gene expression regulation Markov chain metabolism signal transduction Cells Gene Expression Regulation Models, Biological Signal Transduction Stochastic Processes We introduce a stochastic model of coupled genetic oscillators in which chains of chemical events involved in gene regulation and expression are represented as sequences of Poisson processes. We characterize steady states by their frequency, their quality factor, and their synchrony by the oscillator cross correlation. The steady state is determined by coupling and exhibits stochastic transitions between different modes. The interplay of stochasticity and nonlinearity leads to isolated regions in parameter space in which the coupled system works best as a biological pacemaker. Key features of the stochastic oscillations can be captured by an effective model for phase oscillators that are coupled by signals with distributed delays. © 2018 American Physical Society. 2018 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_24700045_v97_n3_p_Jorg http://hdl.handle.net/20.500.12110/paper_24700045_v97_n3_p_Jorg |
| institution |
Universidad de Buenos Aires |
| institution_str |
I-28 |
| repository_str |
R-134 |
| collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
| topic |
Chains Gene expression Gene expression regulation Stochastic systems Cross correlations Distributed delays Genetic oscillators Isolated regions Parameter spaces Phase oscillators Stochastic oscillations Stochastic transitions Stochastic models biological model cells cytology gene expression regulation Markov chain metabolism signal transduction Cells Gene Expression Regulation Models, Biological Signal Transduction Stochastic Processes |
| spellingShingle |
Chains Gene expression Gene expression regulation Stochastic systems Cross correlations Distributed delays Genetic oscillators Isolated regions Parameter spaces Phase oscillators Stochastic oscillations Stochastic transitions Stochastic models biological model cells cytology gene expression regulation Markov chain metabolism signal transduction Cells Gene Expression Regulation Models, Biological Signal Transduction Stochastic Processes Chemical event chain model of coupled genetic oscillators |
| topic_facet |
Chains Gene expression Gene expression regulation Stochastic systems Cross correlations Distributed delays Genetic oscillators Isolated regions Parameter spaces Phase oscillators Stochastic oscillations Stochastic transitions Stochastic models biological model cells cytology gene expression regulation Markov chain metabolism signal transduction Cells Gene Expression Regulation Models, Biological Signal Transduction Stochastic Processes |
| description |
We introduce a stochastic model of coupled genetic oscillators in which chains of chemical events involved in gene regulation and expression are represented as sequences of Poisson processes. We characterize steady states by their frequency, their quality factor, and their synchrony by the oscillator cross correlation. The steady state is determined by coupling and exhibits stochastic transitions between different modes. The interplay of stochasticity and nonlinearity leads to isolated regions in parameter space in which the coupled system works best as a biological pacemaker. Key features of the stochastic oscillations can be captured by an effective model for phase oscillators that are coupled by signals with distributed delays. © 2018 American Physical Society. |
| title |
Chemical event chain model of coupled genetic oscillators |
| title_short |
Chemical event chain model of coupled genetic oscillators |
| title_full |
Chemical event chain model of coupled genetic oscillators |
| title_fullStr |
Chemical event chain model of coupled genetic oscillators |
| title_full_unstemmed |
Chemical event chain model of coupled genetic oscillators |
| title_sort |
chemical event chain model of coupled genetic oscillators |
| publishDate |
2018 |
| url |
https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_24700045_v97_n3_p_Jorg http://hdl.handle.net/20.500.12110/paper_24700045_v97_n3_p_Jorg |
| _version_ |
1768544434005213184 |