High throughput single molecule tracking methods were developed to perform quantitative analyses of rare molecular populations. An optimization strategy for single molecule tracking at interfaces is described that allowed tracking of ~10(6) unique trajectories. These large statistical datasets were analyzed in order to identify and characterize distinct molecular populations based on their characteristic dynamic behavior (residence time or surface diffusion) and/or their spatial distribution. Cumulative (i.e. integrated) probability distributions were found to be several orders of magnitude more sensitive to rare populations than were raw probability distributions. Mapping using Accumulated Probe Trajectories (MAPT) was used to characterize molecular populations associated with rare surface heterogeneities. Importantly, large sample sizes were found to result in a dramatic enhancement in the ability to identify rare populations and to resolve their dynamic and spatial parameters.
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