How to find structurally different molecules before they disappear in the average?

News - 18 June 2021 - Communication ImPhys

Published today in Nature Communications a study about finding heterogeneity in SMLM data. Particle fusion for single molecule localization microscopy improves signal-to-noise ratio and overcomes underlabeling, but ignores structural heterogeneity or conformational variability. This study presents a-priori knowledge-free unsupervised classification of structurally different particles employing the Bhattacharya cost function as dissimilarity metric.

Title: Detecting structural heterogeneity in single-molecule localization microscopy data

Authors: Teun A.P.M. Huijben, Hamidreza Heydarian, Alexander Auer, Florian Schueder, Ralf Jungmann, Sjoerd Stallinga & Bernd Rieger 

Link: Article

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