Evidence map›Paper›PMID 34160817›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2021

Bioinformatic Analysis of Circular RNA Expression.

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

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Enrico GaffoDepartment of Molecular Medicine, University of Padova, Padova, Italy.
Alessia BuratinDepartment of Molecular Medicine, University of Padova, Padova, Italy.
Anna Dal MolinDepartment of Molecular Medicine, University of Padova, Padova, Italy.
Stefania BortoluzziDepartment of Molecular Medicine, University of Padova, Padova, Italy. stefania.bortoluzzi@unipd.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Circular RNAs (circRNAs) are stable RNA molecules generated by backsplicing that play regulatory functions through interaction with other RNA and proteins, as well as by encoding peptides. Dysregulation of circRNA expression can drive cancer development and progression with different mechanisms. CircRNAs are currently regarded as extremely attractive molecules in cancer research for the identification of new and possibly targetable disease regulatory networks and for the development of biomarkers for cancer diagnosis, prognosis definition, and monitoring. Using specific experimental and computational protocols, circRNAs can be identified through RNA-seq by spotting the reads spanning backsplice junctions, which are specific to circular molecules. In this chapter, we report a state-of-the-art computational protocol for a genome-wide analysis of circRNAs from RNA-seq data, which considers circRNA detection, quantification, and differential expression testing. Finally, we indicate how to determine circular transcript sequences and the resources for an in silico functional characterization of circRNAs.

Indexed as

Gene Expression ProfilingGene Expression RegulationRNA, CircularTranscriptomeAlgorithmsComputational BiologyDatabases, GeneticGenome-Wide Association StudySequence Analysis, RNASoftwareRNA, CircularBioinformaticsCircular RNAComputational pipelineRNA-seq

Identifiers

PMID34160817

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.