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Optimal path to epigenetic switching.

David Marin Roma¹, Ruadhan A O'Flanagan, Andrei E Ruckenstein

¹Department of Physics and Astronomy and BioMaPS Institute, Rutgers University, Piscataway, New Jersey 08854, USA.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics

|February 9, 2005

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Large deviation methods quantify noise-induced state transitions in genetic networks. This analysis of the toggle switch circuit validates computational models for synthetic biology applications.

Area of Science:

Systems biology
Biochemical kinetics
Synthetic biology

Background:

Multistable genetic networks exhibit dynamic state transitions influenced by intrinsic and extrinsic noise.
Understanding these transitions is crucial for designing reliable synthetic biological circuits.

Purpose of the Study:

To employ large deviation methods for calculating noise-induced transition rates in multistable genetic networks.
To analyze a synthetic biochemical circuit, the toggle switch, using these methods.

Main Methods:

Application of large deviation theory to model stochastic processes in genetic networks.
Numerical solution of the master equation for comparative analysis.

Main Results:

Related Experiment Videos

Calculated transition rates between states in the genetic toggle switch circuit.

Comparison of results from large deviation methods with numerical solutions of the master equation.

Conclusions:

Large deviation methods provide an effective analytical approach for quantifying noise-induced transitions in synthetic genetic circuits.
The findings support the validity of computational models for predicting the behavior of synthetic biological systems.