Evidence map›Paper›PMID 40886269›Full record

ReviewAdvances in experimental medicine and biology2025

Online Databases in Circular RNAs.

Sachiko Kuwamoto-Imanishi, Hodaka Fujii

Abstract readReview
PubMed Publisher
In one paragraph

Review in Advances in experimental medicine and biology, 2025. 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

2 authors.

Sachiko Kuwamoto-ImanishiDepartment of Biochemistry and Genome Biology, Hirosaki University Graduate School of Medicine, Hirosaki, Aomori Prefecture, Japan.
Hodaka FujiiDepartment of Biochemistry and Genome Biology, Hirosaki University Graduate School of Medicine, Hirosaki, Aomori Prefecture, Japan. hodaka@hirosaki-u.ac.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Circular RNAs (circRNAs) have been attracting attention as biomarkers of various diseases, including cancer, because, as non-coding RNA (ncRNA)/protein sponges, they regulate gene expression and can be detected in various body fluids. Several comprehensive databases have been published to allow easy identification of target circRNAs.In all, 43 circRNA-related databases have been established and are listed in Database Commons since the development of the first comprehensive database of circRNAs, Circ2Traits, in 2013. Some of these databases, including Circ2Traits, provide annotation, ncRNA/protein-circRNA interactions and disease associations, and information on protein synthesis potentials and conservation among species. Additionally, databases that include analyzed RNA sequencing (RNA-seq) data or manually curated literature reporting the expression of circRNAs in specific tissues, organs, and body fluids have been established, making the exploration of target circRNAs easier. Currently, in addition to animals, plant circRNAs are being analyzed, and they cover a surprisingly large number of species.In this chapter, we summarize a selection of popular databases [circBase, CircInteractome, CircNet, CircR2Disease, the tissue-specific circular RNA database (TSCD), and the cancer-specific circRNA database (CSCD)] discussed in the previous edition and introduce some new circRNA databases listed in Database Commons. Furthermore, we discuss some reported challenges related to the nomenclature and updating of those databases.

Indexed as

Databases, GeneticDatabases, Nucleic AcidNeoplasmsRNA, CircularAnimalsComputational BiologyHumansInternetRNA, CircularBioinformaticscircRNAConservationDatabasesDisease associationFunction annotationInteractomeOntologySequence annotation

Identifiers

PMID40886269

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.