Noise structure shapes transitions in cell-type switching processes
Cells are dynamic systems that can transition between distinct phenotypic states through the coordinated activation and repression of genes. Because gene expression is intrinsically stochastic, these dynamics are typically modeled using stochastic frameworks. A central aspect of such descriptions is the noise structure (e.g., additive, demographic or environmental), which specifies how fluctuations depend on the cellular state.
In this work, we investigate how the noise structure influences cell-type switching in a minimal gene regulatory circuit. We find that, while differentiation paths are robust across different noise models, dedifferentiation and transdifferentiation paths are highly sensitive to the type of noise considered. These findings highlight the importance of an appropriate stochastic description when modeling biological systems.
This Annual PhD student seminar will be broadcasted in the following zoom link: https://us06web.zoom.us/j/89027654460?pwd=Wg9TYMPqqP2ipfj2JVvEagmzaTw29c.1
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