Assess the student’s ability to analyze how gene regulatory network (GRN) topology influences robustness and stochastic noise in gene expression. Scope includes common network motifs (negative/positive feedback, incoherent/coherent feedforward loops, bistable switches), quantitative metrics of robustness and noise (sensitivity analysis, Fano factor, coefficient of variation), modeling approaches (deterministic ODEs, stochastic simulations/Gillespie, Boolean approximations), interpretation of simulation and experimental single-cell data, and design of perturbation or validation experiments. Students should compare topologies, predict effects of parameter changes and perturbations on stability and noise propagation, and justify experimental strategies to test predictions.