Abstract: Nowadays scientists can track single-cell activity for a variety of cell-types. The dynamical fluctuations in measured single-cell trajectories contain valuable information about the underlying stochastic reaction network. We shall discuss how frequency domain analysis provides a viable approach for gleaning this information. We provide computational approaches for reliably estimating the power spectral density (PSD) for single-cell trajectories generated by stochastic reaction networks and we demonstrate how such estimates can be used in systems and synthetic biology applications.