  Formation, maintenance and physiology of high-density protein-enriched
organized nanodomains, first observed in electron microscopy images, remains
challenging to investigate due to their small sizes. However, these regions
regulate molecular trafficking, assembly and sorting required for higher cell
functions, such as communication or plastic changes. Over the past ten years,
super-resolution single-particle trajectories (SPTs) have been used to sample
these sub-cellular environments at a nanometer resolution for both membrane and
soluble proteins. We present here data analysis developments and algorithms
that convert high-throughput molecular trajectories into maps of molecular
density, diffusion and local drift organization. These approaches transform
intrinsic trajectory properties into statistics of the underlying cellular
organization. The automatic identification of large numbers of high-density
regions allows quantifying their boundary location and organization, their
stability over time and their ability to transiently retain molecules. To
conclude recent automated algorithms can now be used to extract biophysical
parameters of sub-cellular nanodomains over a large amount of trajectories.
