Evidence map›Paper›PMID 27703238›Full record

ArticleScientific reports2016

Extracting quantitative information from single-molecule super-resolution imaging data with LAMA - LocAlization Microscopy Analyzer.

Sebastian Malkusch, Mike Heilemann

Abstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers.

0numbers the graph read from it
0cells of the map it votes in
55citing papers in PubMed
–field-weighted citation impact
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

55 citing papers in PubMed.

  1. Article
  2. Nanoscale Mapping of the Subcellular Glycosylation Landscape.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Super-Resolved Protein Imaging Using Bifunctional Light-Up Aptamers.Angewandte Chemie (International ed. in English) · 2024
    Article
  7. Article
  8. Anisotropic DBSCAN for 3D SMLM Data Clustering.The journal of physical chemistry. B · 2024
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Single-Molecule Localization Microscopy of Presynaptic Active Zones inInternational journal of molecular sciences · 2023
    Article
  17. Article
  18. Article
  19. Article
  20. Article
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

2 authors.

Sebastian MalkuschSingle Molecule Biophysics, Institute of Physical and Theoretical Chemistry, Goethe-University Frankfurt, Germany.
Mike HeilemannSingle Molecule Biophysics, Institute of Physical and Theoretical Chemistry, Goethe-University Frankfurt, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Super-resolution fluorescence microscopy revolutionizes cell biology research and provides novel insights on how proteins are organized at the nanoscale and in the cellular context. In order to extract a maximum of information, specialized tools for image analysis are necessary. Here, we introduce the LocAlization Microscopy Analyzer (LAMA), a comprehensive software tool that extracts quantitative information from single-molecule super-resolution imaging data. LAMA allows characterizing cellular structures by their size, shape, intensity, distribution, as well as the degree of colocalization with other structures. LAMA is freely available, platform-independent and designed to provide direct access to individual analysis of super-resolution data.

Identifiers

PMID27703238
PMCPMC5050494

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Registered trials

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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.