Evidence map›Paper›PMID 35475220›Full record

ArticleCell reports methods2022

A comprehensive approach for genome-wide efficiency profiling of DNA modifying enzymes.

Charalampos Kyriakopoulos, Karl Nordström, Paula Linh Kramer, Judith Yumiko Gottfreund, Abdulrahman Salhab, Julia Arand, Fabian Müller, Ferdinand von Meyenn, Gabriella Ficz, Wolf Reik and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell reports methods, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
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

13 authors.

Charalampos KyriakopoulosComputer Science Department, Saarland University, Campus E1.3, 66123 Saarbrücken, Germany.
Karl NordströmDepartment of Genetics and Epigenetics, Saarland University, Campus A2.4, 66123 Saarbrücken, Germany.
Paula Linh KramerComputer Science Department, Saarland University, Campus E1.3, 66123 Saarbrücken, Germany.
Judith Yumiko GottfreundDepartment of Genetics and Epigenetics, Saarland University, Campus A2.4, 66123 Saarbrücken, Germany.
Abdulrahman SalhabDepartment of Genetics and Epigenetics, Saarland University, Campus A2.4, 66123 Saarbrücken, Germany.
Julia ArandDivision of Cell and Developmental Biology, Medical University of Vienna, 1090 Vienna, Austria.
Fabian MüllerDepartment of Integrative Cellular Biology and Bioinformatics, Campus A2.4, 66123 Saarbrücken, Germany.
Ferdinand von MeyennDepartment of Health Sciences and Technology, ETH Zürich, Schorenstrasse 16, Schwerzenbach, 8603 Zürich, Switzerland.
Gabriella FiczHaemato-Oncology, Queen Mary University of London, London EC1M 6BQ, UK.
Wolf ReikEpigenetics Department, Babraham Institute, Cambridge CB22 3AT, UK.
Verena WolfComputer Science Department, Saarland University, Campus E1.3, 66123 Saarbrücken, Germany.
Jörn WalterDepartment of Genetics and Epigenetics, Saarland University, Campus A2.4, 66123 Saarbrücken, Germany.
Pascal GiehrDepartment of Genetics and Epigenetics, Saarland University, Campus A2.4, 66123 Saarbrücken, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A precise understanding of DNA methylation dynamics is of great importance for a variety of biological processes including cellular reprogramming and differentiation. To date, complex integration of multiple and distinct genome-wide datasets is required to realize this task. We present GwEEP (genome-wide epigenetic efficiency profiling) a versatile approach to infer dynamic efficiencies of DNA modifying enzymes. GwEEP relies on genome-wide hairpin datasets, which are translated by a hidden Markov model into quantitative enzyme efficiencies with reported confidence around the estimates. GwEEP predicts

Indexed as

DNA-Binding ProteinsEpigenesis, GeneticCell DifferentiationDNADNA MethylationDNADNA-Binding Proteins5hmC5mCDNA demethylationDNA methylationDnmtsepigeneticshairpin sequencinghidden Markov modelTets

Identifiers

PMID35475220
PMCPMC9017147

What OpenQuestion holds

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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.