Evidence map›Paper›PMID 31450634›Full record

ReviewGenes2019

Integration of Bioinformatic Predictions and Experimental Data to Identify circRNA-miRNA Associations.

Martina Dori, Silvio Bicciato

Abstract readReview
In one paragraph

Review in Genes, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.

0numbers the graph read from it
0cells of the map it votes in
58citing papers in PubMed
–field-weighted citation impact
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

58 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. Review
  7. Article
  8. Role of Circular RNAs in Prostate Cancer.Current medicinal chemistry · 2024
    Review
  9. Article
  10. Article
  11. Circular RNA regulation and function in drug seeking phenotypes.Molecular and cellular neurosciences · 2023
    Review
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Age-related ceRNA networks in adultFrontiers in genetics · 2023
    Article
  19. Article
  20. 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

2 authors.

Martina DoriCenter for Genome Research, Department of Life Sciences, University of Modena and Reggio Emilia, Via G. Campi, 287, 41100 Modena, Italy. martina.dori@unimore.it.
Silvio BicciatoCenter for Genome Research, Department of Life Sciences, University of Modena and Reggio Emilia, Via G. Campi, 287, 41100 Modena, Italy. silvio.bicciato@unimore.it.ORCID 0000-0002-1944-7078

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Circular RNAs (circRNAs) have recently emerged as a novel class of transcripts, characterized by covalently linked 3'-5' ends that result in the so-called backsplice junction. During the last few years, thousands of circRNAs have been identified in different organisms. Yet, despite their role as disease biomarker started to emerge, depicting their function remains challenging. Different studies have shown that certain circRNAs act as miRNA sponges, but any attempt to generalize from the single case to the "circ-ome" has failed so far. In this review, we explore the potential to define miRNA "sponging" as a more general function of circRNAs and describe the different approaches to predict miRNA response elements (MREs) in known or novel circRNA sequences. Moreover, we discuss how experiments based on Ago2-IP and experimentally validated miRNA:target duplexes can be used to either prioritize or validate putative miRNA-circRNA associations.

Indexed as

AnimalsComputational BiologyGene Regulatory NetworksHumansMicroRNAsRNA, CircularRNA, MessengerRNA Processing, Post-TranscriptionalMicroRNAsRNA, CircularRNA, MessengercircRNAmiRNAmiRNA spongetarget prediction

Identifiers

PMID31450634
PMCPMC6769881

What OpenQuestion holds

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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.