1. Buffering variability in cell regulation motifs close to criticality
- Author
-
Daniele Proverbio, Arthur N. Montanari, Alexander Skupin, Jorge Gonçalves, Proverbio, D [0000-0002-0122-479X], Montanari, AN [0000-0002-4866-3888], Gonçalves, J [0000-0002-5228-6165], Apollo - University of Cambridge Repository, Fonds National de la Recherche - FnR [sponsor], and Luxembourg Centre for Systems Biomedicine (LCSB): Systems Control (Goncalves Group) [research center]
- Subjects
FOS: Physical sciences ,Critical transitions ,Quantitative Biology - Quantitative Methods ,Nonlinear Sciences - Adaptation and Self-Organizing Systems ,FOS: Biological sciences ,Multidisciplinary, general & others [G99] [Physical, chemical, mathematical & earth Sciences] ,49 Mathematical Sciences ,Cell development ,Fokker-Planck ,Adaptation and Self-Organizing Systems (nlin.AO) ,51 Physical Sciences ,Multidisciplinaire, général & autres [G99] [Physique, chimie, mathématiques & sciences de la terre] ,Quantitative Methods (q-bio.QM) ,40 Engineering - Abstract
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. 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.
- Published
- 2022