Detecting structural heterogeneity in single-molecule localization microscopy data

T.A.P.M. Huijben, H. Heydarian, Alexander Auer, Florian Schueder, Ralf Jungmann, S. Stallinga, B. Rieger

Research output: Contribution to journalArticleScientificpeer-review

2 Downloads (Pure)

Abstract

Particle fusion for single molecule localization microscopy improves signal-to-noise ratio and overcomes underlabeling, but ignores structural heterogeneity or conformational variability. We present a-priori knowledge-free unsupervised classification of structurally different particles employing the Bhattacharya cost function as dissimilarity metric. We achieve 96% classification accuracy on mixtures of up to four different DNA-origami structures, detect rare classes of origami occuring at 2% rate, and capture variation in ellipticity of nuclear pore complexes.
Original languageEnglish
Article number3791
Number of pages8
JournalNature Communications
Volume12
Issue number1
DOIs
Publication statusPublished - 2021

Keywords

  • OA-Fund TU Delft

Fingerprint

Dive into the research topics of 'Detecting structural heterogeneity in single-molecule localization microscopy data'. Together they form a unique fingerprint.

Cite this