Evidence map›Paper›PMID 42447868›Full record

ArticleCell reports methods2026

Benchmarking dynamic analysis methods in diffusion-based single-molecule FRET.

Joel A Crossley

Abstract read
In one paragraph

Article in Cell reports methods, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

1 author.

Joel A CrossleyAstbury Centre for Structural Molecular Biology, School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds LS2 9JT, UK. Electronic address: j.a.crossley@leeds.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single-molecule Förster resonance energy transfer (smFRET) provides nanometer-scale snapshots of biomolecular conformational dynamics, but extracting reliable dynamic information from diffusion-based measurements requires a careful choice of analysis method. This study benchmarks the widely used approaches, including qualitative indicators of dynamics and quantitative rate extraction via hidden Markov modeling, using simulated datasets spanning common experimental conditions and focusing on a two-state system. The assessment clarifies the timescales each method reports on, determines the number of bursts required for reliable inference, examines the differences in FRET efficiencies needed by each approach, and evaluates the accuracy of kinetic rate recovery. Together, these results provide practical guidelines for selecting analysis strategies and accurately interpreting conformational dynamics in diffusion-based smFRET. The accompanying datasets offer a resource for optimizing experimental design and developing new analytical methods.

Indexed as

BenchmarkingFluorescence Resonance Energy TransferSingle Molecule ImagingDiffusionHidden Markov ModelsKineticsMarkov Chainsbenchmarkingbiophysicsconformational dynamicsCP: computational biologyCP: imagingfluorescenceFREThidden Markov modelkineticssingle-moleculesmFRETstructural biology

Identifiers

PMID42447868
PMCPMC13615502

What OpenQuestion holds

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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.