Bayesian inference of multi-point macromolecular architecture mixtures at nanometre resolution.

ABSTRACT: Gaussian spot fitting methods have significantly extended the spatial range where fluorescent microscopy can be used, with recent techniques approaching nanometre (nm) resolutions. However, small inter-fluorophore distances are systematically over-estimated for typical molecular scales. This bias can be corrected computationally, but current algorithms are limited to correcting distances between pairs of fluorophores. Here we present a flexible Bayesian computational approach that infers the distances and angles between multiple fluorophores and has several advantages over these previous methods. Specifically it improves confidence intervals for small lengths, estimates measurement errors of each fluorophore individually and infers the correlations between polygon lengths. The latter is es

SUBMITTER: Embacher PA 

PROVIDER: S-EPMC9829179 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature