In cellular systems, Brownian forces play a dominant role in the movement of small (and not so small) particles such as vesicles, organelles, etc. However, proteins and other macromolecules bind to one another, altering the underlying Brownian dynamics. In this talk, classical approaches in the biophysical literature to time series which switch between bound and unbound states will be presented, and an alternative approach using stochastic expectation-maximization algorithm (EM) combined with particle filters will be proposed. As an example system, molecular motors, such as kinesin, switch between weakly and strongly bound states, as well as directed transport. I will discuss the analysis of such a system along with the ramifications for multi-motor-cargo complexes found in living cells.