Evidence map›Paper›PMID 36066004›Full record

ArticleeLife2022

Recovering mixtures of fast-diffusing states from short single-particle trajectories.

Alec Heckert, Liza Dahal, Robert Tjian, Xavier Darzacq

Open access · goldAbstract read
In one paragraph

Article in eLife, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers.

0numbers the graph read from it
0cells of the map it votes in
67citing papers in PubMed
22.7field-weighted citation impact, top 1% 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

67 citing papers in PubMed, 97 citations in OpenAlex.

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  3. Elevated MyoD1 levels expand genome-wide binding and the repertoire of regulated genes.Proceedings of the National Academy of Sciences of the United States of America · 2026
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7 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

4 authors at 2 institutions in 1 country.

Alec HeckertDepartment of Molecular and Cell Biology, Li Ka Shing Center for Biomedical and Health Sciences, University of California, Berkeley, Berkeley, United States.ORCID https://orcid.org/0000-0001-8748-6645
Liza DahalDepartment of Molecular and Cell Biology, Li Ka Shing Center for Biomedical and Health Sciences, University of California, Berkeley, Berkeley, United States.
Robert TjianCIRM Center of Excellence, University of California, Berkeley, Berkeley, United States.
Xavier DarzacqDepartment of Molecular and Cell Biology, Li Ka Shing Center for Biomedical and Health Sciences, University of California, Berkeley, Berkeley, United States.ORCID https://orcid.org/0000-0003-2537-8395
University of California, Berkeley · USHoward Hughes Medical Institute · US

Funding

Project 2: Evaluating the dynamic protein-protein interactions mediated by LCDs within EWS/FLI and its partners in living cells via single molecule imagingU54CA231641 · NCI · RESEARCH INST NATIONWIDE CHILDREN'S HOSP · PI LESSNICK, STEPHEN L. · 2018 to 2018
$6.2M
Stem Cell Engineering Training ProgramT32GM098218 · NIGMS · UNIVERSITY OF CALIFORNIA BERKELEY · PI HEALY, KEVIN EDWARD, SCHAFFER, DAVID V · 2011 to 2020
$1.8M
Howard Hughes Medical Institute CC34430NCI NIH HHS U54 CA231641NIGMS NIH HHS T32 GM098218
6 · The paper itself

Abstract

Single-particle tracking (SPT) directly measures the dynamics of proteins in living cells and is a powerful tool to dissect molecular mechanisms of cellular regulation. Interpretation of SPT with fast-diffusing proteins in mammalian cells, however, is complicated by technical limitations imposed by fast image acquisition. These limitations include short trajectory length due to photobleaching and shallow depth of field, high localization error due to the low photon budget imposed by short integration times, and cell-to-cell variability. To address these issues, we investigated methods inspired by Bayesian nonparametrics to infer distributions of state parameters from SPT data with short trajectories, variable localization precision, and absence of prior knowledge about the number of underlying states. We discuss the advantages and disadvantages of these approaches relative to other frameworks for SPT analysis.

Indexed as

MammalsSingle Molecule ImagingAnimalsBayes TheoremDiffusionbiochemistrychemical biologyhumanmammalian cell culturephysics of living systemssingle-particle trackingU2OS osteosarcoma

Identifiers

PMID36066004
PMCPMC9451534
OpenAlexW4293576390

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.