Precise measurement of nanoscopic septin ring structures with deep learning-assisted quantitative superresolution microscopy.

ABSTRACT: The combination of image analysis and superresolution microscopy methods allows for unprecedented insight into the organization of macromolecular assemblies in cells. Advances in deep learning (DL)-based object recognition enable the automated processing of large amounts of data, resulting in high accuracy through averaging. However, while the analysis of highly symmetric structures of constant size allows for a resolution approaching the dimensions of structural biology, DL-based image recognition may introduce bias. This prohibits the development of readouts for processes that involve significant changes in size or shape of amorphous macromolecular complexes. Here we address this problem by using changes of septin ring structures in single molecule localization-based superresolution micr

SUBMITTER: Zehtabian A 

PROVIDER: S-EPMC9635280 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature