Evidence map›Paper›PMID 34356060›Full record

ArticleGenes2021

CircIMPACT: An R Package to Explore Circular RNA Impact on Gene Expression and Pathways.

Alessia Buratin, Enrico Gaffo, Anna Dal Molin, Stefania Bortoluzzi

Abstract read
In one paragraph

Article in Genes, 2021. 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
–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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. 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.

Alessia BuratinDepartment of Biology, University of Padova, 35131 Padova, Italy.ORCID 0000-0003-2461-750X
Enrico GaffoDepartment of Molecular Medicine, University of Padova, 35131 Padova, Italy.ORCID 0000-0001-6338-7677
Anna Dal MolinDepartment of Molecular Medicine, University of Padova, 35131 Padova, Italy.
Stefania BortoluzziDepartment of Molecular Medicine, University of Padova, 35131 Padova, Italy.ORCID 0000-0001-8240-3070

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Circular RNAs (circRNAs) are transcripts generated by back-splicing. CircRNAs might regulate cellular processes by different mechanisms, including interaction with miRNAs and RNA-binding proteins. CircRNAs are pleiotropic molecules whose dysregulation has been linked to human diseases and can drive cancer by impacting gene expression and signaling pathways. The detection of circRNAs aberrantly expressed in disease conditions calls for the investigation of their functions. Here, we propose CircIMPACT, a bioinformatics tool for the integrative analysis of circRNA and gene expression data to facilitate the identification and visualization of the genes whose expression varies according to circRNA expression changes. This tool can highlight regulatory axes potentially governed by circRNAs, which can be prioritized for further experimental study. The usefulness of CircIMPACT is exemplified by a case study analysis of bladder cancer RNA-seq data. The link between circHIPK3 and heparanase (HPSE) expression, due to the circHIPK3-miR558-HPSE regulatory axis previously determined by experimental studies on cell lines, was successfully detected. CircIMPACT is freely available at GitHub.

Indexed as

Gene ExpressionComputational BiologyGlucuronidaseHeparanaseHumansIntracellular Signaling Peptides and ProteinsMicroRNAsProtein Serine-Threonine KinasesRNA, CircularRNA SplicingUrinary Bladder NeoplasmsGlucuronidaseHeparanaseHIPK3 protein, humanIntracellular Signaling Peptides and ProteinsMicroRNAsProtein Serine-Threonine KinasesRNA, Circularcircular RNAgene expressionpathwaysregulatory axes

Identifiers

PMID34356060
PMCPMC8308052

What OpenQuestion holds

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Registered trials

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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.