RT Journal Article SR Electronic T1 Increasing the time resolution of single-molecule experiments with Bayesian inference JF bioRxiv FD Cold Spring Harbor Laboratory SP 099648 DO 10.1101/099648 A1 Colin D. Kinz-Thompson A1 Ruben L. Gonzalez, Jr. YR 2017 UL http://biorxiv.org/content/early/2017/05/26/099648.abstract AB Many time-resolved, single-molecule biophysics experiments seek to characterize the kinetics of biomolecular systems exhibiting dynamics that challenge the time resolution of the given technique. Here we present a general, computational approach to this problem that employs Bayesian inference to learn the underlying dynamics of such systems, even when they are much faster than the time resolution of the experimental technique being used. By accurately and precisely inferring rate constants, our Bayesian Inference for the Analysis of Sub-temporal-resolution Data (BIASD) approach effectively enables the experimenter to super-resolve the poorly resolved dynamics that are present in their data.