HomeMolecular BiologyGenetic Toggle Switch: Stochastic Noise-Induced Switching (2D)

Genetic Toggle Switch: Stochastic Noise-Induced Switching (2D)

Interactive 2D stochastic simulation of the genetic toggle switch: a tau-leaping master-equation model tracks discrete repressor-protein molecule counts per cell, showing how finite population size drives spontaneous noise-induced flips between the two stable states that the deterministic Hill-function ODE alone can never produce.

Molecular Biology2DAdvanced60 FPS📱 Mobile-adapted⇄ 3D version
2d-synthetic-biology ↗ Open standalone

The genetic toggle switch — two mutually-repressing genes forming a synthetic-biology flip-flop (Gardner, Cantor & Collins, 2000) — is usually taught through its deterministic Hill-function ODE, which produces two permanently stable states. Real cells don't run on smooth concentrations, though: they run on discrete, small numbers of actual protein molecules being synthesized and degraded one at a time. This 2D simulator replaces the ODE integrator with a tau-leaping stochastic simulation of the underlying chemical master equation, tracking each cell's integer repressor-A and repressor-B molecule counts as an independent random walk. Adjust promoter strengths and cooperativity as before, but now also dial the system size Ω — the molecule-count scale — down to watch cells spontaneously hop between the two stable basins from pure molecular noise, or up to watch that noise vanish and the population freeze into the deterministic picture, with every spontaneous basin change tallied live.

⚙ Under the hood

2D stochastic simulation of the genetic toggle switch: a tau-leaping chemical master-equation model tracks discrete repressor-protein molecule counts per cell, showing how finite system size (Omega) drives spontaneous noise-induced flips between the two stable states that the deterministic Hill-function ODE alone can never produce.

synthetic biologygene circuitbistabilitystochastic simulationGillespie algorithmsystems biology2D

2D · HTML5 Canvas 2D · 60 FPS target · runs fully client-side, no install

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