Evidence map›Paper›PMID 29733395›Full record

ArticleNucleic acids research2018

Towards a map of cis-regulatory sequences in the human genome.

Meng Niu, Ehsan Tabari, Pengyu Ni, Zhengchang Su

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.0field-weighted citation impact, top 24% 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

12 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. 44 Current Challenges in miRNomics.Methods in molecular biology (Clifton, N.J.) · 2022
    Article
  7. regCNN: identifyingComputational and structural biotechnology journal · 2022
    Article
  8. Review
  9. Accurate prediction ofNAR genomics and bioinformatics · 2021
    Article
  10. Profiling Chromatin Accessibility at Single-cell Resolution.Genomics, proteomics & bioinformatics · 2021
    Review
  11. Article
  12. 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

4 authors at 1 institution in 1 country.

Meng NiuDepartment of Bioinformatics and Genomics, College of Computing and Informatics, The University of North Carolina at Charlotte, 9201 University City Blvd., Charlotte, NC 28223, USA.
Ehsan TabariDepartment of Bioinformatics and Genomics, College of Computing and Informatics, The University of North Carolina at Charlotte, 9201 University City Blvd., Charlotte, NC 28223, USA.
Pengyu NiDepartment of Bioinformatics and Genomics, College of Computing and Informatics, The University of North Carolina at Charlotte, 9201 University City Blvd., Charlotte, NC 28223, USA.
Zhengchang SuDepartment of Bioinformatics and Genomics, College of Computing and Informatics, The University of North Carolina at Charlotte, 9201 University City Blvd., Charlotte, NC 28223, USA.
University of North Carolina at Charlotte · US

Funding

Understanding the complexity of the transcriptomes in E. coli K12R01GM106013 · NIGMS · UNIVERSITY OF NORTH CAROLINA CHARLOTTE · PI SU, ZHENGCHANG · 2014 to 2017
$1.1M
NIGMS NIH HHS R01 GM106013
6 · The paper itself

Abstract

Accumulating evidence indicates that transcription factor (TF) binding sites, or cis-regulatory elements (CREs), and their clusters termed cis-regulatory modules (CRMs) play a more important role than do gene-coding sequences in specifying complex traits in humans, including the susceptibility to common complex diseases. To fully characterize their roles in deriving the complex traits/diseases, it is necessary to annotate all CREs and CRMs encoded in the human genome. However, the current annotations of CREs and CRMs in the human genome are still very limited and mostly coarse-grained, as they often lack the detailed information of CREs in CRMs. Here, we integrated 620 TF ChIP-seq datasets produced by the ENCODE project for 168 TFs in 79 different cell/tissue types and predicted an unprecedentedly completely map of CREs in CRMs in the human genome at single nucleotide resolution. The map includes 305 912 CRMs containing a total of 1 178 913 CREs belonging to 736 unique TF binding motifs. The predicted CREs and CRMs tend to be subject to either purifying selection or positive selection, thus are likely to be functional. Based on the results, we also examined the status of available ChIP-seq datasets for predicting the entire regulatory genome of humans.

Indexed as

AlgorithmsBase SequenceBinding SitesCell Line, TumorGenetic Predisposition to DiseaseGenome, HumanHeLa CellsHumansRegulatory Elements, TranscriptionalRegulatory Sequences, Nucleic Acid

Identifiers

PMID29733395
PMCPMC6009671
OpenAlexW2799761182

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.