Evidence map›Paper›PMID 26022740›Full record

ArticleBMC bioinformatics2015

Discrimination of cell cycle phases in PCNA-immunolabeled cells.

Felix Schönenberger, Anja Deutzmann, Elisa Ferrando-May, Dorit Merhof

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.

0numbers the graph read from it
0cells of the map it votes in
58citing papers in PubMed
6.6field-weighted citation impact, top 4% 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

58 citing papers in PubMed, 97 citations in OpenAlex.

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  17. Pharmaceuticals (Basel, Switzerland) · 2024
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  20. Dynamics of Replication-Associated Protein Levels through the Cell Cycle.International journal of molecular sciences · 2024
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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

4 authors at 2 institutions in 2 countries.

Felix SchönenbergerBioimaging Center (BIC), University of Konstanz, Universitätsstraße 10, Konstanz, Germany. Felix.Schoenenberger@uni-konstanz.de.
Anja DeutzmannBioimaging Center (BIC), University of Konstanz, Universitätsstraße 10, Konstanz, Germany. Anja.Deutzmann@stanford.edu.
Elisa Ferrando-MayBioimaging Center (BIC), University of Konstanz, Universitätsstraße 10, Konstanz, Germany. Elisa.May@uni-konstanz.de.
Dorit MerhofInstitute of Imaging & Computer Vision, RWTH Aachen University, Templergraben 55, Aachen, 52074, Germany. Dorit.Merhof@lfb.rwth-aachen.de.
University of Konstanz · DERWTH Aachen University · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundProtein function in eukaryotic cells is often controlled in a cell cycle-dependent manner. Therefore, the correct assignment of cellular phenotypes to cell cycle phases is a crucial task in cell biology research. Nuclear proteins whose localization varies during the cell cycle are valuable and frequently used markers of cell cycle progression. Proliferating cell nuclear antigen (PCNA) is a protein which is involved in DNA replication and has cell cycle dependent properties. In this work, we present a tool to identify cell cycle phases and in particular, sub-stages of the DNA replication phase (S-phase) based on the characteristic patterns of PCNA distribution. Single time point images of PCNA-immunolabeled cells are acquired using confocal and widefield fluorescence microscopy. In order to discriminate different cell cycle phases, an optimized processing pipeline is proposed. For this purpose, we provide an in-depth analysis and selection of appropriate features for classification, an in-depth evaluation of different classification algorithms, as well as a comparative analysis of classification performance achieved with confocal versus widefield microscopy images.

resultsWe show that the proposed processing chain is capable of automatically classifying cell cycle phases in PCNA-immunolabeled cells from single time point images, independently of the technique of image acquisition. Comparison of confocal and widefield images showed that for the proposed approach, the overall classification accuracy is slightly higher for confocal microscopy images.

conclusionOverall, automated identification of cell cycle phases and in particular, sub-stages of the DNA replication phase (S-phase) based on the characteristic patterns of PCNA distribution, is feasible for both confocal and widefield images.

Indexed as

AlgorithmsAntibodies, MonoclonalCell ProliferationDNA ReplicationCell CycleCell NucleusHeLa CellsHumansImage Processing, Computer-AssistedMicroscopy, ConfocalMicroscopy, FluorescenceProliferating Cell Nuclear AntigenSupport Vector MachineAntibodies, MonoclonalProliferating Cell Nuclear Antigen

Identifiers

PMID26022740
PMCPMC4448323
OpenAlexW1557411065

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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.