Evidence map›Paper›PMID 30631072›Full record

ArticleNature communications2019

Ultrafast data mining of molecular assemblies in multiplexed high-density super-resolution images.

Yandong Yin, Wei Ting Chelsea Lee, Eli Rothenberg

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
5.6field-weighted citation impact, top 5% of its field
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

22 citing papers in PubMed, 32 citations in OpenAlex.

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  16. 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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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

3 authors at 1 institution in 1 country.

Yandong YinDepartment of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, NY, 10016, USA. Yandong.Yin@nyumc.org.ORCID http://orcid.org/0000-0003-2499-871X
Wei Ting Chelsea LeeDepartment of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, NY, 10016, USA.ORCID http://orcid.org/0000-0002-8842-6510
Eli RothenbergDepartment of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, NY, 10016, USA. Eli.Rothenberg@nyumc.org.
New York University · US

Funding

Single-Molecule Studies of Non-Homologous DNA End JoiningR01GM108119 · NIGMS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI ROTHENBERG, ELI · 2015 to 2019
$1.7M
NIGMS NIH HHS R01 GM108119
6 · The paper itself

Abstract

Multicolor single-molecule localization super-resolution microscopy has enabled visualization of ultrafine spatial organizations of molecular assemblies within cells. Despite many efforts, current approaches for distinguishing and quantifying such organizations remain limited, especially when these are contained within densely distributed super-resolution data. In theory, higher-order correlation such as the Triple-Correlation function is capable of obtaining the spatial configuration of individual molecular assemblies masked within seemingly discorded dense distributions. However, due to their enormous computational cost such analyses are impractical, even for high-end computers. Here, we developed a fast algorithm for Triple-Correlation analyses of high-content multiplexed super-resolution data. This algorithm computes the probability density of all geometric configurations formed by every triple-wise single-molecule localization from three different channels, circumventing impractical 4D Fourier Transforms of the entire megapixel image. This algorithm achieves 10

Indexed as

AlgorithmsCell Line, TumorComputer SimulationFourier AnalysisHumansImage Processing, Computer-AssistedMicroscopy, FluorescenceReproducibility of ResultsSingle Molecule Imaging

Identifiers

PMID30631072
PMCPMC6328550
OpenAlexW2911001534

What OpenQuestion holds

Textmetadata
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.