Evidence map›Paper›PMID 36303761›Full record

ArticleFrontiers in bioinformatics2021

Raw Data to Results: A Hands-On Introduction and Overview of Computational Analysis for Single-Molecule Localization Microscopy.

Koen J A Martens, Bartosz Turkowyd, Ulrike Endesfelder

Open access · goldAbstract read
In one paragraph

Article in Frontiers in bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
4.8field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
  2. Article
  3. Nanoscale architecture and dynamics of CaJournal of molecular and cellular cardiology plus · 2025
    Article
  4. Perspective: An outlook on fluorescence tracking.The Journal of chemical physics · 2025
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Triggered cagedSTORM microscopy.Biomedical optics express · 2024
    Article
  10. Article
  11. Recent Advances in Single-Molecule Tracking and Imaging Techniques.Annual review of analytical chemistry (Palo Alto, Calif.) · 2023
    Review
  12. Review
  13. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 2 countries.

Koen J A MartensDepartment of Physics, Carnegie Mellon University, Pittsburgh, PA, United States.
Bartosz TurkowydDepartment of Physics, Carnegie Mellon University, Pittsburgh, PA, United States.
Ulrike EndesfelderDepartment of Physics, Carnegie Mellon University, Pittsburgh, PA, United States.
University of Bonn · DELoewe Center for Synthetic Microbiology · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single-molecule localization microscopy (SMLM) is an advanced microscopy method that uses the blinking of fluorescent molecules to determine the position of these molecules with a resolution below the diffraction limit (∼5-40 nm). While SMLM imaging itself is becoming more popular, the computational analysis surrounding the technique is still a specialized area and often remains a "black box" for experimental researchers. Here, we provide an introduction to the required computational analysis of SMLM imaging, post-processing and typical data analysis. Importantly, user-friendly, ready-to-use and well-documented code in Python and MATLAB with exemplary data is provided as an interactive experience for the reader, as well as a starting point for further analysis. Our code is supplemented by descriptions of the computational problems and their implementation. We discuss the state of the art in computational methods and software suites used in SMLM imaging and data analysis. Finally, we give an outlook into further computational challenges in the field.

Indexed as

drift and chromatic aberration correctionsingle-particle trackingSMLM clusteringSMLM image formationSMLM localization and localization mergingSMLM localization precision and structural image resolutionSMLM Python and MATLAB codetemporal median filtering

Identifiers

PMID36303761
PMCPMC9580916
OpenAlexW4210409543

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.