Evidence map›Paper›PMID 37098414›Full record

ReviewDatabase : the journal of biological databases and curation2023

Review of databases for experimentally validated human microRNA-mRNA interactions.

Dorian Kariuki, Kesava Asam, Bradley E Aouizerat, Kimberly A Lewis, Jose C Florez, Elena Flowers

Open access · goldAbstract readReview
In one paragraph

Review in Database : the journal of biological databases and curation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
9.1field-weighted citation impact, top 2% of its field
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

22 citing papers in PubMed, 38 citations in OpenAlex.

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  18. Temporal Expression Analysis to Unravel Gene Regulatory Dynamics by microRNAs.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  19. Review
  20. 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

6 authors at 3 institutions in 1 country.

Dorian KariukiDepartment of Physiological Nursing, University of California, San Francisco, CA 94143, USA.ORCID 0000-0001-8607-6185
Kesava AsamBluestone Center for Clinical Research, New York University, New York, CA 10010, USA.
Bradley E AouizeratBluestone Center for Clinical Research, New York University, New York, CA 10010, USA.
Kimberly A LewisDepartment of Physiological Nursing, University of California, San Francisco, CA 94143, USA.
Jose C FlorezDepartment of Medicine, Center for Genomic Medicine and Diabetes Unit, Massachusetts General Hospital, Boston, MA 02114, USA.
Elena FlowersDepartment of Physiological Nursing, University of California, San Francisco, CA 94143, USA.ORCID 0000-0002-7054-7533
University of California, San Francisco · USCenter for Clinical Research (United States) · USBroad Institute · US

Funding

The Impact of Interventions to Treat Incident Diabetes on Circulating microRNAs in the Diabetes Prevention ProgramR01DK124228 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI FLOWERS, ELENA · 2020 to 2023
$2.3M
NIDDK NIH HHS R01 DK124228
6 · The paper itself

Abstract

MicroRNAs (miRs) may contribute to disease etiology by influencing gene expression. Numerous databases are available for miR target prediction and validation, but their functionality is varied, and outputs are not standardized. The purpose of this review is to identify and describe databases for cataloging validated miR targets. Using Tools4miRs and PubMed, we identified databases with experimentally validated targets, human data, and a focus on miR-messenger RNA (mRNA) interactions. Data were extracted about the number of times each database was cited, the number of miRs, the target genes, the interactions per database, experimental methodology and key features of each database. The search yielded 10 databases, which in order of most cited to least were: miRTarBase, starBase/The Encyclopedia of RNA Interactomes, DIANA-TarBase, miRWalk, miRecords, miRGator, miRSystem, miRGate, miRSel and targetHub. Findings from this review suggest that the information presented within miR target validation databases can be enhanced by adding features such as flexibility in performing queries in multiple ways, downloadable data, ongoing updates and integrating tools for further miR-mRNA target interaction analysis. This review is designed to aid researchers, especially those new to miR bioinformatics tools, in database selection and to offer considerations for future development and upkeep of validation tools. Database URL http://mirtarbase.cuhk.edu.cn/.

Indexed as

MicroRNAsComputational BiologyDatabases, Nucleic AcidHumansPubMedRNA, MessengerMicroRNAsRNA, Messenger

Identifiers

PMID37098414
PMCPMC10129384
OpenAlexW4367016957

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.