Evidence map›Paper›PMID 29291020›Full record

ArticleOncotarget2017

About miRNAs, miRNA seeds, target genes and target pathways.

Tim Kehl, Christina Backes, Fabian Kern, Tobias Fehlmann, Nicole Ludwig, Eckart Meese, Hans-Peter Lenhof, Andreas Keller

Open access · diamondAbstract read
In one paragraph

Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 90 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
90citing papers in PubMed, 1 pooled it
3.2field-weighted citation impact, top 7% 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

90 citing papers in PubMed, 1 synthesis or guideline pooled it, 159 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Unlocking Parkinson's disease: the role of microRNAs in regulation, diagnosis, and therapy.Apoptosis : an international journal on programmed cell death · 2025
    Review
  17. Article
  18. Review
  19. Article
  20. Review

30 more citing papers are in PubMed but not listed here.

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 1 institution in 1 country.

Tim KehlCenter for Bioinformatics, Saarland University, Saarland Informatics Campus, Saarbrücken, Germany.
Christina BackesChair for Clinical Bioinformatics, Saarland University, Saarland Informatics Campus, Saarbrücken, Germany.
Fabian KernChair for Clinical Bioinformatics, Saarland University, Saarland Informatics Campus, Saarbrücken, Germany.
Tobias FehlmannChair for Clinical Bioinformatics, Saarland University, Saarland Informatics Campus, Saarbrücken, Germany.
Nicole LudwigDepartment of Human Genetics, Saarland University, Homburg, Germany.
Eckart MeeseDepartment of Human Genetics, Saarland University, Homburg, Germany.
Hans-Peter LenhofCenter for Bioinformatics, Saarland University, Saarland Informatics Campus, Saarbrücken, Germany.
Andreas KellerChair for Clinical Bioinformatics, Saarland University, Saarland Informatics Campus, Saarbrücken, Germany.
Saarland University · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

miRNAs are typically repressing gene expression by binding to the 3' UTR, leading to degradation of the mRNA. This process is dominated by the eight-base seed region of the miRNA. Further, miRNAs are known not only to target genes but also to target significant parts of pathways. A logical line of thoughts is: miRNAs with similar (seed) sequence target similar sets of genes and thus similar sets of pathways. By calculating similarity scores for all 3.25 million pairs of 2,550 human miRNAs, we found that this pattern frequently holds, while we also observed exceptions. Respective results were obtained for both, predicted target genes as well as experimentally validated targets. We note that miRNAs target gene set similarity follows a bimodal distribution, pointing at a set of 282 miRNAs that seems to target genes with very high specificity. Further, we discuss miRNAs with different (seed) sequences that nonetheless regulate similar gene sets or pathways. Most intriguingly, we found miRNA pairs that regulate different gene sets but similar pathways such as miR-6886-5p and miR-3529-5p. These are jointly targeting different parts of the MAPK signaling cascade. The main goal of this study is to provide a general overview on the results, to highlight a selection of relevant results on miRNAs, miRNA seeds, target genes and target pathways and to raise awareness for artifacts in respective comparisons. The full set of information that allows to infer detailed results on each miRNA has been included in miRPathDB, the miRNA target pathway database (https://mpd.bioinf.uni-sb.de).

Indexed as

microRNAnon-coding RNAsystems biologytarget gene

Identifiers

PMID29291020
PMCPMC5739805
OpenAlexW2767385021

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.