  Memory effects in time-series of experimental observables are ubiquitous,
have important consequences for the interpretation of kinetic data, and may
even affect the function of biomolecular nanomachines such as enzymes. Here we
propose a set of complementary methods for quantifying conclusively the
magnitude and duration of memory in a time series of a reaction coordinate. The
toolbox is general, robust, easy to use, and does not rely on any underlying
microscopic model. As a proof of concept we apply it to the analysis of memory
in the dynamics of the end-to-end distance of the analytically solvable
Rouse-polymer model and an experimental time-series of extensions of a single
DNA hairpin measured in an optical tweezers experiment.
