Evidence map›Paper›PMID 42681326›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2026

Construction and Analysis of circRNA-miRNA-mRNA Regulatory Networks.

Simone Avesani, Luciano Cascione, Rosalba Giugno

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Simone AvesaniDepartment of Computer Science, University of Verona, Verona, Italy. simone.avesani@univr.it.
Luciano CascioneInstitute of Oncology Research, Faculty of Biomedical Sciences, Università della Svizzera italiana (USI), Bellinzona, Switzerland.
Rosalba GiugnoDepartment of Computer Science, University of Verona, Verona, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Circular RNAs (circRNAs) represent an emerging class of noncoding RNAs characterized by their covalently closed-loop structure and generated through the back-splicing event. This structural configuration provides circRNAs with enhanced stability and unique functional properties. Functionally, circRNAs act as protein scaffolds, enhance protein activity, can be translated, and frequently serve as competing endogenous RNAs (ceRNAs), particularly by sponging microRNAs (miRNAs) and modulating downstream gene expression. Since these regulatory capacities have significant implications in cancer, neurodegenerative, and cardiovascular diseases, in response, numerous computational approaches have been developed to reconstruct circRNA-miRNA-mRNA networks, ranging from specific circRNA-oriented applications to sequencing-based tools, each with distinct strengths and limitations. This chapter provides an overview of these strategies, highlighting their application in bioinformatics research and their potential to explore novel regulatory mechanisms mediated by circRNAs.

Indexed as

Computational BiologyGene Regulatory NetworksMicroRNAsRNA, CircularRNA, MessengerAnimalsGene Expression RegulationHumansRNA, Competitive EndogenousMicroRNAsRNA, CircularRNA, Competitive EndogenousRNA, MessengercircRNAcircRNA–miRNA–mRNA networksNetwork reconstructionRegulative analysis

Identifiers

PMID42681326

What OpenQuestion holds

Textmetadata
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.