Buffering variability in cell regulation motifs close to criticality
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arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2022
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| _version_ | 1866909714404605952 |
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| author | Proverbio, Daniele Montanari, Arthur N. Skupin, Alexander Gonçalves, Jorge |
| author_facet | Proverbio, Daniele Montanari, Arthur N. Skupin, Alexander Gonçalves, Jorge |
| contents | Bistable biological regulatory systems need to cope with stochastic noise to fine-tune their function close to bifurcation points. Here, we study stability properties of this regime in generic systems to demonstrate that cooperative interactions buffer system variability, hampering noise-induced regime shifts. Our analysis also shows that, in the considered cooperativity range, impending regime shifts can be generically detected by statistical early warning signals from distributional data. Our generic framework, based on minimal models, can be used to extract robustness and variability properties of more complex models and empirical data close to criticality. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2212_08600 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Buffering variability in cell regulation motifs close to criticality Proverbio, Daniele Montanari, Arthur N. Skupin, Alexander Gonçalves, Jorge Adaptation and Self-Organizing Systems Quantitative Methods Bistable biological regulatory systems need to cope with stochastic noise to fine-tune their function close to bifurcation points. Here, we study stability properties of this regime in generic systems to demonstrate that cooperative interactions buffer system variability, hampering noise-induced regime shifts. Our analysis also shows that, in the considered cooperativity range, impending regime shifts can be generically detected by statistical early warning signals from distributional data. Our generic framework, based on minimal models, can be used to extract robustness and variability properties of more complex models and empirical data close to criticality. |
| title | Buffering variability in cell regulation motifs close to criticality |
| topic | Adaptation and Self-Organizing Systems Quantitative Methods |
| url | https://arxiv.org/abs/2212.08600 |