Correlation functions quantify super-resolution images and estimate apparent clustering due to over-counting.

ABSTRACT: We present an analytical method using correlation functions to quantify clustering in super-resolution fluorescence localization images and electron microscopy images of static surfaces in two dimensions. We use this method to quantify how over-counting of labeled molecules contributes to apparent self-clustering and to calculate the effective lateral resolution of an image. This treatment applies to distributions of proteins and lipids in cell membranes, where there is significant interest in using electron microscopy and super-resolution fluorescence localization techniques to probe membrane heterogeneity. When images are quantified using pair auto-correlation functions, the magnitude of apparent clustering arising from over-counting varies inversely with the surface density of labeled m

SUBMITTER: Veatch SL 

PROVIDER: S-EPMC3288038 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature