Evidence map›Paper›PMID 31844073›Full record

ArticleScientific reports2019

MeinteR: A framework to prioritize DNA methylation aberrations based on conformational and cis-regulatory element enrichment.

Andigoni Malousi, Sofia Kouidou, Maria Tsagiopoulou, Nikos Papakonstantinou, Emmanouil Bouras, Elisavet Georgiou, Georgios Tzimagiorgis, Kostas Stamatopoulos

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 46% 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

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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

2 citing papers in PubMed, 5 citations in OpenAlex.

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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

8 authors at 2 institutions in 1 country.

Andigoni MalousiLab. of Biological Chemistry, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece. andigoni@auth.gr.
Sofia KouidouLab. of Biological Chemistry, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece.
Maria TsagiopoulouInstitute of Applied Biosciences, Centre for Research and Technology Hellas, Thessaloniki, Greece.
Nikos PapakonstantinouInstitute of Applied Biosciences, Centre for Research and Technology Hellas, Thessaloniki, Greece.
Emmanouil BourasLab. of Hygiene, Social-Preventive Medicine & Medical Statistics, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece.
Elisavet GeorgiouLab. of Biological Chemistry, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece.
Georgios TzimagiorgisLab. of Biological Chemistry, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece.
Kostas StamatopoulosInstitute of Applied Biosciences, Centre for Research and Technology Hellas, Thessaloniki, Greece.
Aristotle University of Thessaloniki · GRCentre for Research and Technology Hellas · GR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

DNA methylation studies have been reformed with the advent of single-base resolution arrays and bisulfite sequencing methods, enabling deeper investigation of methylation-mediated mechanisms. In addition to these advancements, numerous bioinformatics tools address important computational challenges, covering DNA methylation calling up to multi-modal interpretative analyses. However, contrary to the analytical frameworks that detect driver mutational signatures, the identification of putatively actionable epigenetic events remains an unmet need. The present work describes a novel computational framework, called MeinteR, that prioritizes critical DNA methylation events based on the following hypothesis: critical aberrations of DNA methylation more likely occur on a genomic substrate that is enriched in cis-acting regulatory elements with distinct structural characteristics, rather than in genomic "deserts". In this context, the framework incorporates functional cis-elements, e.g. transcription factor binding sites, tentative splice sites, as well as conformational features, such as G-quadruplexes and palindromes, to identify critical epigenetic aberrations with potential implications on transcriptional regulation. The evaluation on multiple, public cancer datasets revealed significant associations between the highest-ranking loci with gene expression and known driver genes, enabling for the first time the computational identification of high impact epigenetic changes based on high-throughput DNA methylation data.

Indexed as

Nucleic Acid ConformationSoftwareAnimalsBreast NeoplasmsCarcinoma, HepatocellularDatabases, GeneticDNA MethylationEpigenesis, GeneticFemaleGene Expression Regulation, NeoplasticGenome, HumanGenome-Wide Association StudyG-QuadruplexesHumansLiver NeoplasmsMice

Identifiers

PMID31844073
PMCPMC6915744
OpenAlexW2994614550

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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.