ArticleNano letters2021
Nanoscale Pattern Extraction from Relative Positions of Sparse 3D Localizations.
Article in Nano letters, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
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Who cites it
15 citing papers in PubMed, 32 citations in OpenAlex.
- Using iPALM to determine protein organisation in cardiac muscle Z-discs.PLoS computational biology · 2026Article
- Biological properties of α-actinin-2 and its role and mechanisms in disease development.Frontiers in physiology · 2026Review
- Spatial and stoichiometric in situ analysis of biomolecular oligomerization at single-protein resolution.Nature communications · 2025Article
- Temporal analysis of relative distances (TARDIS) is a robust, parameter-free alternative to single-particle tracking.Nature methods · 2024Article
- Insights into protein structure using cryogenic light microscopy.Biochemical Society transactions · 2023Review
- Simulating structurally variable nuclear pore complexes for microscopy.Bioinformatics (Oxford, England) · 2023Article
- Particle fusion of super-resolution data reveals the unit structure of Nup96 in Nuclear Pore Complex.Scientific reports · 2023Article
- PIEZO1 and PECAM1 interact at cell-cell junctions and partner in endothelial force sensing.Communications biology · 2023Article
- Maximum-likelihood model fitting for quantitative analysis of SMLM data.Nature methods · 2023Article
- Affimers targeting proteins in the cardiomyocyte Z-disc: Novel tools that improve imaging of heart tissue.Frontiers in cardiovascular medicine · 2023Article
- Bayesian inference of multi-point macromolecular architecture mixtures at nanometre resolution.PLoS computational biology · 2022Article
- Affimers and nanobodies as molecular probes and their applications in imaging.Journal of cell science · 2022Article
- Mapping molecular complexes with super-resolution microscopy and single-particle analysis.Open biology · 2022Review
- Article
- Raw Data to Results: A Hands-On Introduction and Overview of Computational Analysis for Single-Molecule Localization Microscopy.Frontiers in bioinformatics · 2021Article
Corrections and comments
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Authors and funding
16 authors at 5 institutions in 4 countries.
Funding
Abstract
Inferring the organization of fluorescently labeled nanosized structures from single molecule localization microscopy (SMLM) data, typically obscured by stochastic noise and background, remains challenging. To overcome this, we developed a method to extract high-resolution ordered features from SMLM data that requires only a low fraction of targets to be localized with high precision. First, experimentally measured localizations are analyzed to produce relative position distributions (RPDs). Next, model RPDs are constructed using hypotheses of how the molecule is organized. Finally, a statistical comparison is used to select the most likely model. This approach allows pattern recognition at sub-1% detection efficiencies for target molecules, in large and heterogeneous samples and in 2D and 3D data sets. As a proof-of-concept, we infer ultrastructure of Nup107 within the nuclear pore, DNA origami structures, and α-actinin-2 within the cardiomyocyte Z-disc and assess the quality of images of centrioles to improve the averaged single-particle reconstruction.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.