Evidence map›Paper›PMID 41277400›Full record

ArticleJournal of cell science2026

Redefining colocalization analysis with a novel phasor mixing coefficient.

Owen F Puls, Jesse S Aaron, Ellen K Quarles, Satya Khuon, Leanna R Eisenman, Andrés Kamaid, Leonel Malacrida, Teng-Leong Chew

Abstract read
In one paragraph

Article in Journal of cell science, 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
–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

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

8 authors.

Owen F PulsAdvanced Imaging Center and Integrative Imaging , Howard Hughes Medical Institute Janelia Research Campus, Ashburn, VA 20147, USA.ORCID 0000-0002-5097-3420
Jesse S AaronAdvanced Imaging Center and Integrative Imaging , Howard Hughes Medical Institute Janelia Research Campus, Ashburn, VA 20147, USA.ORCID 0000-0002-7543-9590
Ellen K QuarlesAdvanced Imaging Center and Integrative Imaging , Howard Hughes Medical Institute Janelia Research Campus, Ashburn, VA 20147, USA.ORCID 0000-0002-7160-3939
Satya KhuonAdvanced Imaging Center and Integrative Imaging , Howard Hughes Medical Institute Janelia Research Campus, Ashburn, VA 20147, USA.
Leanna R EisenmanAdvanced Imaging Center and Integrative Imaging , Howard Hughes Medical Institute Janelia Research Campus, Ashburn, VA 20147, USA.
Andrés KamaidAdvanced Bioimaging Unit, Institut Pasteur de Montevideo and Universidad de la República, Montevideo, 11400Uruguay.ORCID 0000-0003-3686-1315
Leonel MalacridaAdvanced Bioimaging Unit, Institut Pasteur de Montevideo and Universidad de la República, Montevideo, 11400Uruguay.ORCID 0000-0001-6253-9229
Teng-Leong ChewAdvanced Imaging Center and Integrative Imaging , Howard Hughes Medical Institute Janelia Research Campus, Ashburn, VA 20147, USA.ORCID 0000-0002-3139-7560

Funding

Agencia Nacional de Investigacion e Innovacion FMV_1_2023_1_176623Agencia Nacional de Investigación e Innovación FMV_1_2023_1_176623Chan Zuckerberg InitiativeChan Zuckerberg Initiative 2020-225439Chan Zuckerberg Initiative 2021-240122Chan Zuckerberg Initiative 2022-252604Howard Hughes Medical InstitutePrograma de Desarrollo de las Ciencias BasicasPrograma de Desarrollo de las Ciencias Básicas 2020-225439Programa de Desarrollo de las Ciencias Básicas 2021-240122Programa de Desarrollo de las Ciencias Básicas 2022-252604Silicon Valley Community Foundation
6 · The paper itself

Abstract

The first step to probing any potential interaction between two biomolecules is to determine their spatial association. In other words, if two biomolecules localize similarly within a cell, then it is plausible they could interact. Traditionally, this is quantified through various colocalization metrics. These measures infer this association by estimating the degree to which fluorescent signals from each biomolecule overlap or correlate. However, these metrics are, at best, proxies, and they depend strongly on various experimental choices. Here, we define a new strategy that leverages multispectral imaging and phasor analysis, termed the phasor mixing coefficient (PMC). The PMC measures the precise mixing of fluorescent signals in each pixel. We demonstrate how the PMC captures complex biological subtlety by offering two distinct values, a global measure of overall color mixing and the homogeneity thereof. We additionally show that the PMC exhibits less sensitivity to signal-to-noise ratio, intensity threshold and background signal compared to canonical methods. Moreover, this method provides a means to visualize color mixing at each pixel. We show that the PMC offers users a nuanced and robust metric to quantify biological association.

Indexed as

Image Processing, Computer-AssistedHumansMicroscopy, FluorescenceSignal-To-Noise RatioColocalizationMultispectral imagingPhasor analysisQuantitative microscopy

Identifiers

PMID41277400
PMCPMC12863294

What OpenQuestion holds

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LicenceCC BY
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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.