title: Optimal diffusion coefficient estimation in single-particle tracking.
abstract: Single-particle tracking is increasingly used to extract quantitative parameters on single molecules and their environment, while advances in spatial and temporal resolution of tracking techniques inspire new questions and avenues of investigation. Correspondingly, sophisticated analytical methods are constantly developed to obtain more refined information from measured trajectories. Here we point out some fundamental limitations of these approaches due to the finite length of trajectories, the presence of localization error, and motion blur, focusing on the simplest motion regime of free diffusion in an isotropic medium (Brownian motion). We show that two recently proposed algorithms approach the theoretical limit of diffusion coefficient uncertainty. We discuss the practical performance of the algorithms as well as some important implications of these results for single-particle tracking.
authors.affiliation: Department of Chemistry and Biochemistry, University of California at Los Angeles, Los Angeles, California 90095, USA. michalet@chem.ucla.edu
authors.forename: Xavier
authors.initials: X
authors.lastname: Michalet
authors.forename: Andrew J
authors.initials: AJ
authors.lastname: Berglund
mesh_terms: D000465:Algorithms; D001704:Biopolymers / Q000032:analysis*; D057054:Molecular Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*
chemical_list: D001704:Biopolymers