  Single-particle tracking (SPT) grants unprecedented insight into cellular
function at the molecular scale [1]. Throughout the cell, the movement of
single-molecules is generally heterogeneous and complex. Hence, there is an
imperative to understand the multi-scale nature of single-molecule dynamics in
biological systems. We have previously shown that with high-density SPT,
spatial maps of the parameters that dictate molecule motion can be generated to
intricately describe cellular environments [2,3,4]. To date, however, there
exist no publically available tools that reconcile trajectory data to generate
the aforementioned maps. We address this void in the SPT community with
InferenceMAP: an interactive software package that uses a powerful Bayesian
method to map the dynamic cellular space experienced by individual
biomolecules.
