Evidence map›Paper›PMID 29300163›Full record

ArticleeLife2018

Robust model-based analysis of single-particle tracking experiments with Spot-On.

Anders S Hansen, Maxime Woringer, Jonathan B Grimm, Luke D Lavis, Robert Tjian, Xavier Darzacq

Abstract read
In one paragraph

Article in eLife, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 190 papers.

0numbers the graph read from it
0cells of the map it votes in
190citing 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

190 citing papers in PubMed.

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130 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

6 authors.

Anders S Hansen *Department of Molecular and Cell Biology, Li Ka Shing Center for Biomedical and Health Sciences, CIRM Center of Excellence, University of California, Berkeley, Berkeley, United States.ORCID 0000-0001-7540-7858
Maxime Woringer *Department of Molecular and Cell Biology, Li Ka Shing Center for Biomedical and Health Sciences, CIRM Center of Excellence, University of California, Berkeley, Berkeley, United States.ORCID 0000-0003-2581-9808
Jonathan B GrimmJanelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States.
Luke D LavisJanelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States.
Robert TjianDepartment of Molecular and Cell Biology, Li Ka Shing Center for Biomedical and Health Sciences, CIRM Center of Excellence, University of California, Berkeley, Berkeley, United States.ORCID 0000-0003-0539-8217
Xavier DarzacqDepartment of Molecular and Cell Biology, Li Ka Shing Center for Biomedical and Health Sciences, CIRM Center of Excellence, University of California, Berkeley, Berkeley, United States.ORCID 0000-0003-2537-8395

Funding

KOMP2-Phase3 Production and Phenotyping by the DTCC Consortium TCP Transfer to UC DavisUM1OD023221 · OD · UNIVERSITY OF CALIFORNIA AT DAVIS · PI KC KENT LLOYD · 2016 to 2026
$45.7M
Center for 3D Structure and Physics of the GenomeU54DK107980 · NIDDK · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI SONTHEIMER, ERIK J. · 2015 to 2019
$14.9M
Tools For Imaging the Functional Genome in Living Cells and TissuesU01EB021236 · NIBIB · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI DARZACQ, XAVIER, SINGER, ROBERT H · 2015 to 2017
$2.5M
Howard Hughes Medical Institute 003061NIBIB NIH HHS U01 EB021236NIBIB NIH HHS UO1-EB021236NIDDK NIH HHS U54 DK107980NIDDK NIH HHS U54-DK107980NIH HHS UM1 OD023221
6 · The paper itself

Abstract

Single-particle tracking (SPT) has become an important method to bridge biochemistry and cell biology since it allows direct observation of protein binding and diffusion dynamics in live cells. However, accurately inferring information from SPT studies is challenging due to biases in both data analysis and experimental design. To address analysis bias, we introduce 'Spot-On', an intuitive web-interface. Spot-On implements a kinetic modeling framework that accounts for known biases, including molecules moving out-of-focus, and robustly infers diffusion constants and subpopulations from pooled single-molecule trajectories. To minimize inherent experimental biases, we implement and validate stroboscopic photo-activation SPT (spaSPT), which minimizes motion-blur bias and tracking errors. We validate Spot-On using experimentally realistic simulations and show that Spot-On outperforms other methods. We then apply Spot-On to spaSPT data from live mammalian cells spanning a wide range of nuclear dynamics and demonstrate that Spot-On consistently and robustly infers subpopulation fractions and diffusion constants.

Indexed as

Cytological TechniquesImage Processing, Computer-AssistedInternetIntravital MicroscopySingle Molecule Imagingbiophysicscomputational biologydynamicshumankinetic modelingmousesingle moleculesingle particle trackingstructural biologysuper-resolutionsystems biologytranscription factor

Identifiers

PMID29300163
PMCPMC5809147

What OpenQuestion holds

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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.