Evidence map›Paper›PMID 23005136›Full record

ArticlePhysical review. E, Statistical, nonlinear, and soft matter physics2012

Optimal diffusion coefficient estimation in single-particle tracking.

Xavier Michalet, Andrew J Berglund

Abstract read
In one paragraph

Article in Physical review. E, Statistical, nonlinear, and soft matter physics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 120 papers.

0numbers the graph read from it
0cells of the map it votes in
120citing 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

120 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. High-Speed Interferometric Scattering Tracking Microscopy of Compartmentalized Lipid Diffusion in Living Cells.Chemphyschem : a European journal of chemical physics and physical chemistry · 2025
    Article
  9. Article
  10. Clustering within a single-component biomolecular condensate.bioRxiv : the preprint server for biology · 2025
    Article
  11. Entropy (Basel, Switzerland) · 2025
    Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

60 more citing papers are in PubMed but not listed here.

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.

Xavier MichaletDepartment of Chemistry and Biochemistry, University of California at Los Angeles, Los Angeles, California 90095, USA. michalet@chem.ucla.edu
Andrew J Berglund

Funding

High-Resolution, High Speed, High-Throughput 3-Dimensional Detector for BiologyR01EB006353 · NIBIB · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI WEISS, SHIMON · 2007 to 2010
$1.6M
Multipixel Hybrid Photon-Counting Detector for High-Throughput Single-Molecule AsR01GM084327 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI WEISS, SHIMON · 2008 to 2010
$667k
NIBIB NIH HHS EB006353NIBIB NIH HHS R01 EB006353NIGMS NIH HHS GM084327NIGMS NIH HHS R01 GM084327
6 · The paper itself

Abstract

Single-particle tracking is increasingly used to extract quantitative parameters on single molecules and their environment, while advances in spatial and temporal resolution of tracking techniques inspire new questions and avenues of investigation. Correspondingly, sophisticated analytical methods are constantly developed to obtain more refined information from measured trajectories. Here we point out some fundamental limitations of these approaches due to the finite length of trajectories, the presence of localization error, and motion blur, focusing on the simplest motion regime of free diffusion in an isotropic medium (Brownian motion). We show that two recently proposed algorithms approach the theoretical limit of diffusion coefficient uncertainty. We discuss the practical performance of the algorithms as well as some important implications of these results for single-particle tracking.

Indexed as

AlgorithmsBiopolymersMolecular ImagingPattern Recognition, AutomatedBiopolymers

Identifiers

PMID23005136
PMCPMC4917385

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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.