Detecting structural heterogeneity in single-molecule localization microscopy data.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 34145284.
- Also identified by DOI 10.1038/s41467-021-24106-8 and PMC identifier 8213809.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
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.
Medical subject headings
- DNA
- Nuclear Pore
- Nucleic Acid Conformation
- Single Molecule Imaging