Evidence map›Paper›PMID 34540355›Full record

ArticlePhysical review. X

Pitching single-focus confocal data analysis one photon at a time with Bayesian nonparametrics.

Meysam Tavakoli, Sina Jazani, Ioannis Sgouralis, Omer M Shafraz, Sanjeevi Sivasankar, Bryan Donaphon, Marcia Levitus, Steve Pressé

Abstract read
In one paragraph

Article in Physical review. X. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

29 citing papers in PubMed.

  1. Article
  2. Perspective: An outlook on fluorescence tracking.The Journal of chemical physics · 2025
    Article
  3. Review
  4. Review
  5. Physics-Inspired Single-Particle Tracking Accelerated with Parallelism.bioRxiv : the preprint server for biology · 2025
    Article
  6. Single-molecule reaction-diffusion.Biophysical journal · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. An accurate probabilistic step finder for time-series analysis.bioRxiv : the preprint server for biology · 2023
    Article
  12. Single-Molecule Reaction-Diffusion.bioRxiv : the preprint server for biology · 2023
    Article
  13. Article
  14. Article
  15. Review
  16. 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

8 authors.

Meysam TavakoliDepartment of Physics, Indiana University-Purdue University Indianapolis, IN 46202.
Sina JazaniCenter for Biological Physics, Department of Physics, Arizona State University, Tempe, AZ 85287.
Ioannis SgouralisCenter for Biological Physics, Department of Physics, Arizona State University, Tempe, AZ 85287.
Omer M ShafrazDepartment of Biomedical Engineering, University of California, Davis, CA 95616.
Sanjeevi SivasankarDepartment of Biomedical Engineering, University of California, Davis, CA 95616.
Bryan DonaphonBiodesign Institute, Arizona State University, Tempe, AZ 85287.
Marcia LevitusCenter for Biological Physics, Department of Physics, Arizona State University, Tempe, AZ 85287.
Steve PresséCenter for Biological Physics, Department of Physics, Arizona State University, Tempe, AZ 85287 and School of Molecular Sciences, Arizona State University, Tempe, AZ 85287.

Funding

Microscope for ultrasensitive measurement of single-molecule interaction and conformationR01GM121885 · NIGMS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI SIVASANKAR, SANJEEVI · 2017 to 2024
$2.5M
A Bayesian nonparametric approach to superresolved tracking of multiple molecules inside living cellsR01GM130745 · NIGMS · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI PRESSE, STEVE · 2019 to 2023
$1.5M
Theoretical Models of Single Molecule Dynamics from Minimal Photon NumbersR01GM134426 · NIGMS · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI PRESSE, STEVE · 2019 to 2022
$1.2M
Trekking with the Ribognome: Single Molecule Microscopy of Intracellular miRNPsR01GM081025 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI WALTER, NILS G · 2007 to 2010
$998k
NIGMS NIH HHS R01 GM081025NIGMS NIH HHS R01 GM121885NIGMS NIH HHS R01 GM130745NIGMS NIH HHS R01 GM134426
6 · The paper itself

Abstract

Fluorescence time traces are used to report on dynamical properties of molecules. The basic unit of information in these traces is the arrival time of individual photons, which carry instantaneous information from the molecule, from which they are emitted, to the detector on timescales as fast as microseconds. Thus, it is theoretically possible to monitor molecular dynamics at such timescales from traces containing only a sufficient number of photon arrivals. In practice, however, traces are stochastic and in order to deduce dynamical information through traditional means-such as fluorescence correlation spectroscopy (FCS) and related techniques-they are collected and temporally autocorrelated over several minutes. So far, it has been impossible to analyze dynamical properties of molecules on timescales approaching data acquisition without collecting long traces under the strong assumption of stationarity of the process under observation or assumptions required for the analytic derivation of a correlation function. To avoid these assumptions, we would otherwise need to estimate the instantaneous number of molecules emitting photons and their positions within the confocal volume. As the number of molecules in a typical experiment is unknown, this problem demands that we abandon the conventional analysis paradigm. Here, we exploit Bayesian nonparametrics that allow us to obtain, in a principled fashion, estimates of the same quantities as FCS but from the direct analysis of traces of photon arrivals that are significantly smaller in size, or total duration, than those required by FCS.

Indexed as

Bayesian nonparametricsConfocal microscopyFCSSingle photon detectionSpectroscopy

Identifiers

PMID34540355
PMCPMC8445401

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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.