Evidence map›Paper›PMID 37021559›Full record

ArticleNucleic acids research2023

Esearch3D: propagating gene expression in chromatin networks to illuminate active enhancers.

Maninder Heer, Luca Giudice, Claudia Mengoni, Rosalba Giugno, Daniel Rico

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2023. 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
2.2field-weighted citation impact, top 13% 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

4 citing papers in PubMed, 10 citations in OpenAlex.

  1. Machine and Deep Learning Methods for Predicting 3D Genome Organization.Methods in molecular biology (Clifton, N.J.) · 2025
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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

5 authors at 2 institutions in 3 countries.

Maninder HeerBiosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK.
Luca GiudiceDepartment of Computer Science, University of Verona, Strada le Grazie 15, 37134, Verona, Italy.
Claudia MengoniDepartment of Computer Science, University of Verona, Strada le Grazie 15, 37134, Verona, Italy.
Rosalba GiugnoDepartment of Computer Science, University of Verona, Strada le Grazie 15, 37134, Verona, Italy.ORCID 0000-0001-9843-7638
Daniel RicoBiosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK.ORCID 0000-0002-6561-2310
University of Verona · ITNewcastle University · GB

Funding

Wellcome Trust
6 · The paper itself

Abstract

Most cell type-specific genes are regulated by the interaction of enhancers with their promoters. The identification of enhancers is not trivial as enhancers are diverse in their characteristics and dynamic in their interaction partners. We present Esearch3D, a new method that exploits network theory approaches to identify active enhancers. Our work is based on the fact that enhancers act as a source of regulatory information to increase the rate of transcription of their target genes and that the flow of this information is mediated by the folding of chromatin in the three-dimensional (3D) nuclear space between the enhancer and the target gene promoter. Esearch3D reverse engineers this flow of information to calculate the likelihood of enhancer activity in intergenic regions by propagating the transcription levels of genes across 3D genome networks. Regions predicted to have high enhancer activity are shown to be enriched in annotations indicative of enhancer activity. These include: enhancer-associated histone marks, bidirectional CAGE-seq, STARR-seq, P300, RNA polymerase II and expression quantitative trait loci (eQTLs). Esearch3D leverages the relationship between chromatin architecture and transcription, allowing the prediction of active enhancers and an understanding of the complex underpinnings of regulatory networks. The method is available at: https://github.com/InfOmics/Esearch3D and https://doi.org/10.5281/zenodo.7737123.

Indexed as

ChromatinEnhancer Elements, GeneticSoftwareGene ExpressionPromoter Regions, GeneticRNA Polymerase IIChromatinRNA Polymerase II

Identifiers

PMID37021559
PMCPMC10250221
OpenAlexW4362657526

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.