Single molecule FRET experiments are important for studying processes that happen on the molecular scale. By using pulsed illumination and collecting single photons, it is possible to use information gained from the fluorescence lifetime of the chromophores in the FRET pair to gain more accurate estimates of the underlying FRET rate which is used to determine information about the distance between the chromophores of the FRET pair. In this paper, we outline a method that utilizes Bayesian inference to learn parameter values for a model informed by the physics of a immobilized single-molecule FRET experiment. This method is unique in that it combines a rigorous look at the photophysics of the FRET pair and a nonparametric treatment of the molecular conformational statespace, allowing the method to learn not just relevant photophysical rates (such as relaxation rates and FRET rates), but also the number of molecular conformational states.
Optometry is an important field in medicine as it allows people a chance to have their vision corrected and it serves as a health screening opportunity for those who receive a dilated eye examination. One of the largest barriers to receiving a dilated eye exam is insurance coverage. Most health insurance policies have limited optometric coverage. By expanding health insurance plans to be more inclusive of optometric care, people who use these health insurance plans will have a better access of care.