Evidence map›Paper›PMID 29093506›Full record

ArticleScientific reports2017

A Method for Quantifying Molecular Interactions Using Stochastic Modelling and Super-Resolution Microscopy.

Keria Bermudez-Hernandez, Sarah Keegan, Donna R Whelan, Dylan A Reid, Jennifer Zagelbaum, Yandong Yin, Sisi Ma, Eli Rothenberg, David Fenyö

Abstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
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  8. Super-resolution mapping of cellular double-strand break resection complexes during homologous recombination.Proceedings of the National Academy of Sciences of the United States of America · 2021
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  11. Review
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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

9 authors.

Keria Bermudez-HernandezDepartment of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, NY, USA.
Sarah KeeganDepartment of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, NY, USA.
Donna R WhelanDepartment of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, NY, USA.
Dylan A ReidDepartment of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, NY, USA.
Jennifer ZagelbaumDepartment of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, NY, USA.
Yandong YinDepartment of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, NY, USA.
Sisi MaInstitute for Systems Genetics, New York University School of Medicine, New York, NY, USA.
Eli RothenbergDepartment of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, NY, USA. eli.rothenberg@nyumc.org.
David FenyöDepartment of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, NY, USA. david@fenyolab.org.ORCID 0000-0001-5049-3825

Funding

TRAINING PROGRAM IN MOLECULAR ONCOLOGY &IMMUNOLOGYT32CA009161 · NCI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI CARROLL, WILLIAM L., LEVY, DAVID E · 1985 to 2020
$13.3M
Proteogenomic Data Analysis for Cancer Systems Biology and Clinical TranslationU24CA210972 · NCI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI DING, LI, FENYO, DAVID · 2016 to 2020
$3.3M
Single-Molecule Studies of Non-Homologous DNA End JoiningR01GM108119 · NIGMS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI ROTHENBERG, ELI · 2015 to 2019
$1.7M
Single-molecule studies of BRCA1-BACH1 mechanism in genomic integrityR21CA187612 · NCI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI ROTHENBERG, ELI · 2015 to 2016
$451k
NCI NIH HHS R21 CA187612NCI NIH HHS T32 CA009161NCI NIH HHS U24 CA210972NIGMS NIH HHS R01 GM108119
6 · The paper itself

Abstract

We introduce the Interaction Factor (IF), a measure for quantifying the interaction of molecular clusters in super-resolution microscopy images. The IF is robust in the sense that it is independent of cluster density, and it only depends on the extent of the pair-wise interaction between different types of molecular clusters in the image. The IF for a single or a collection of images is estimated by first using stochastic modelling where the locations of clusters in the images are repeatedly randomized to estimate the distribution of the overlaps between the clusters in the absence of interaction (IF = 0). Second, an analytical form of the relationship between IF and the overlap (which has the random overlap as its only parameter) is used to estimate the IF for the experimentally observed overlap. The advantage of IF compared to conventional methods to quantify interaction in microscopy images is that it is insensitive to changing cluster density and is an absolute measure of interaction, making the interpretation of experiments easier. We validate the IF method by using both simulated and experimental data and provide an ImageJ plugin for determining the IF of an image.

Indexed as

Biophysical PhenomenaStochastic ProcessesCluster AnalysisMethodsMicroscopyMolecular Imaging

Identifiers

PMID29093506
PMCPMC5665986

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.