title: Analysis and Interpretation of Superresolution Single-Particle Trajectories.
abstract: A large number (tens of thousands) of single molecular trajectories on a cell membrane can now be collected by superresolution methods. The data contains information about the diffusive motion of molecule, proteins, or receptors and here we review methods for its recovery by statistical analysis of the data. The information includes the forces, organization of the membrane, the diffusion tensor, the long-time behavior of the trajectories, and more. To recover the long-time behavior and statistics of long trajectories, a stochastic model of their nonequilibrium motion is required. Modeling and data analysis serve extracting novel biophysical features at an unprecedented spatiotemporal resolution. The review presents data analysis, modeling, and stochastic simulations applied in particular on surface receptors evolving in neuronal cells.
authors.affiliation: Applied Mathematics and Computational Biology, IBENS Ecole Normale Supérieure, Paris, France; Churchill College, Cambridge University, Cambridge, United Kingdom. Electronic address: david.holcman@ens.fr.
authors.forename: D
authors.initials: D
authors.lastname: Holcman
authors.affiliation: ETH Zürich, Institute of Integrative Biology, ETH-Zentrum CHN, Universitätsstrasse 16, Zürich, Switzerland.
authors.forename: N
authors.initials: N
authors.lastname: Hoze
authors.affiliation: Department of Applied Mathematics, Tel-Aviv University, Tel-Aviv, Israel.
authors.forename: Z
authors.initials: Z
authors.lastname: Schuss
mesh_terms: D003627:Data Interpretation, Statistical; D004058:Diffusion; D008958:Models, Molecular; D009038:Motion; D009474:Neurons / Q000378:metabolism; D013269:Stochastic Processes