Evidence map›Paper›PMID 35106564›Full record

ArticleBriefings in bioinformatics2022

CRAFT: a bioinformatics software for custom prediction of circular RNA functions.

Anna Dal Molin, Enrico Gaffo, Valeria Difilippo, Alessia Buratin, Caterina Tretti Parenzan, Silvia Bresolin, Stefania Bortoluzzi

Erratum issuedAbstract read
In one paragraph

Article in Briefings in bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Article
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  4. Coding circular RNA in human cancer.Genes & diseases · 2025
    Review
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  9. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Anna Dal MolinDepartment of Molecular Medicine, University of Padova, Padova, Italy.
Enrico GaffoDepartment of Molecular Medicine, University of Padova, Padova, Italy.ORCID 0000-0001-6338-7677
Valeria DifilippoDepartment of Biology, University of Padova, Padova, Italy.
Alessia BuratinDepartment of Molecular Medicine, University of Padova, Padova, Italy.
Caterina Tretti ParenzanOnco-hematology, stem cell transplant and gene therapy laboratory, IRP-Istituto di Ricerca Pediatrica, Padova, Italy.
Silvia BresolinOnco-hematology, stem cell transplant and gene therapy laboratory, IRP-Istituto di Ricerca Pediatrica, Padova, Italy.
Stefania BortoluzziDepartment of Molecular Medicine, University of Padova, Padova, Italy.ORCID 0000-0001-8240-3070

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Circular RNAs (circRNAs), transcripts generated by backsplicing, are particularly stable and pleiotropic molecules, whose dysregulation drives human diseases and cancer by modulating gene expression and signaling pathways. CircRNAs can regulate cellular processes by different mechanisms, including interaction with microRNAs (miRNAs) and RNA-binding proteins (RBP), and encoding specific peptides. The prediction of circRNA functions is instrumental to interpret their impact in diseases, and to prioritize circRNAs for functional investigation. Currently, circRNA functional predictions are provided by web databases that do not allow custom analyses, while self-standing circRNA prediction tools are mostly limited to predict only one type of function, mainly focusing on the miRNA sponge activity of circRNAs. To solve these issues, we developed CRAFT (CircRNA Function prediction Tool), a freely available computational pipeline that predicts circRNA sequence and molecular interactions with miRNAs and RBP, along with their coding potential. Analysis of a set of circRNAs with known functions has been used to appraise CRAFT predictions and to optimize its setting. CRAFT provides a comprehensive graphical visualization of the results, links to several knowledge databases, and extensive functional enrichment analysis. Moreover, it originally combines the predictions for different circRNAs. CRAFT is a useful tool to help the user explore the potential regulatory networks involving the circRNAs of interest and generate hypotheses about the cooperation of circRNAs into the modulation of biological processes.

Indexed as

MicroRNAsRNA, CircularComputational BiologyGene Regulatory NetworksHumansRNARNA-Binding ProteinsRNA, MessengerSoftwareMicroRNAsRNARNA-Binding ProteinsRNA, CircularRNA, MessengerbioinformaticsCircRNAcomputational pipelinefunctional predictionregulatory network

Identifiers

PMID35106564
PMCPMC8921651

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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.