Evidence map›Paper›PMID 25704908›Full record

ReviewWiley interdisciplinary reviews. Developmental biology

Identifying transcriptional cis-regulatory modules in animal genomes.

Kushal Suryamohan, Marc S Halfon

Open access · greenAbstract readReview
In one paragraph

Review in Wiley interdisciplinary reviews. Developmental biology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed
1.9field-weighted citation impact, top 15% 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

43 citing papers in PubMed, 67 citations in OpenAlex.

  1. UnlockingNAR genomics and bioinformatics · 2026
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  9. Evolution of Microglia.Advances in neurobiology · 2024
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  19. Speciation in North AmericanSystematic entomology · 2020
    Article
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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

2 authors at 2 institutions in 1 country.

Kushal SuryamohanDepartment of Biochemistry, University at Buffalo-State University of New York, Buffalo, NY, USA; NY State Center of Excellence in Bioinformatics and Life Sciences, Buffalo, NY, USA.
Marc S Halfon
Roswell Park Comprehensive Cancer Center · USUniversity at Buffalo, State University of New York · US

Funding

High sensitivity discovery of cis-regulatory modulesR01GM085233 · NIGMS · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI HALFON, MARC S, SINHA, SAURABH · 2008 to 2012
$1.7M
NIGMS NIH HHS R01 GM085233NIGMS NIH HHS R01 GM85233
6 · The paper itself

Abstract

unlabelledGene expression is regulated through the activity of transcription factors (TFs) and chromatin-modifying proteins acting on specific DNA sequences, referred to as cis-regulatory elements. These include promoters, located at the transcription initiation sites of genes, and a variety of distal cis-regulatory modules (CRMs), the most common of which are transcriptional enhancers. Because regulated gene expression is fundamental to cell differentiation and acquisition of new cell fates, identifying, characterizing, and understanding the mechanisms of action of CRMs is critical for understanding development. CRM discovery has historically been challenging, as CRMs can be located far from the genes they regulate, have few readily identifiable sequence characteristics, and for many years were not amenable to high-throughput discovery methods. However, the recent availability of complete genome sequences and the development of next-generation sequencing methods have led to an explosion of both computational and empirical methods for CRM discovery in model and nonmodel organisms alike. Experimentally, CRMs can be identified through chromatin immunoprecipitation directed against TFs or histone post-translational modifications, identification of nucleosome-depleted 'open' chromatin regions, or sequencing-based high-throughput functional screening. Computational methods include comparative genomics, clustering of known or predicted TF-binding sites, and supervised machine-learning approaches trained on known CRMs. All of these methods have proven effective for CRM discovery, but each has its own considerations and limitations, and each is subject to a greater or lesser number of false-positive identifications. Experimental confirmation of predictions is essential, although shortcomings in current methods suggest that additional means of validation need to be developed. For further resources related to this article, please visit the WIREs website. CONFLICT OF INTEREST: The authors have declared no conflicts of interest for this article.

Indexed as

GenomeTranscription, GeneticAnimalsBinding SitesGenes, ReporterRegulatory Sequences, Nucleic AcidTranscription FactorsTranscription Factors

Identifiers

PMID25704908
PMCPMC4339228
OpenAlexW1525488578

What OpenQuestion holds

Textmetadata
LicenceTDM
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.