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Stochastic simulation can make the molecular processes of cellular controlmore vivid than the traditional differential-equation approach by generatingtypical system histories instead of just statistical measures such as the meanand variance of a population. Simple simulations are now easy for students toconstruct from scratch, that is, without recourse to black-box packages. Insome cases, their results can also be compared directly to single-moleculeexperimental data. After introducing the stochastic simulation algorithm, thisarticle gives two case studies, involving gene expression and error correction,respectively. Code samples and resulting animations showing results are givenin the online supplements.

Stochastic Simulation to Visualize Gene Expression and Error Correction in Living Cells