Evidence map›Paper›PMID 37819683›Full record

ArticleDatabase : the journal of biological databases and curation2023

The landscape of microRNA interaction annotation: analysis of three rare disorders as a case study.

Panni Simona, Kalpana Panneerselvam, Pablo Porras, Margaret Duesbury, Livia Perfetto, Luana Licata, Henning Hermjakob, Sandra Orchard

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article 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. An erratum has been issued. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.0field-weighted citation impact, top 21% 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

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 5 institutions in 4 countries.

Panni SimonaDipartimento di Biologia Ecologia e Scienze della Terra, Università della Calabria, Rende 87036, Italy.
Kalpana PanneerselvamEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus Hinxton, Cambridge CB10 1SD, UK.
Pablo PorrasEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus Hinxton, Cambridge CB10 1SD, UK.
Margaret DuesburyEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus Hinxton, Cambridge CB10 1SD, UK.
Livia PerfettoDepartment of Biology and Biotechnologies "Charles Darwin", La Sapienza University, Rome, Italy.
Luana LicataDepartment of Biology, University of Tor Vergata, Rome, Italy.ORCID 0000-0001-5084-9000
Henning HermjakobEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus Hinxton, Cambridge CB10 1SD, UK.ORCID 0000-0001-8479-0262
Sandra OrchardEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus Hinxton, Cambridge CB10 1SD, UK.ORCID 0000-0002-8878-3972
European Bioinformatics Institute · GBAstraZeneca (United Kingdom) · GBCharles Darwin University · AUUniversity of Calabria · ITUniversity of Rome Tor Vergata · IT

Funding

UniProt - Text Mining and Large Language models to Enhance Functional Annotation in UniProt of Protein Variants Associated with Alzheimer's DiseaseU24HG007822 · NHGRI · GEORGETOWN UNIVERSITY · PI Alex Bateman, Alan James Bridge · 2018 to 2026
$53.0M
NHGRI NIH HHS U24 HG007822
6 · The paper itself

Abstract

In recent years, a huge amount of data on ncRNA interactions has been described in scientific papers and databases. Although considerable effort has been made to annotate the available knowledge in public repositories, there are still significant discrepancies in how different resources capture and interpret data on ncRNA functional and physical associations. In the present paper, we present a collection of microRNA-mRNA interactions annotated from the scientific literature following recognized standard criteria and focused on microRNAs, which regulate genes associated with rare diseases as a case study. The list of protein-coding genes with a known role in specific rare diseases was retrieved from the Genome England PanelApp, and associated microRNA-mRNA interactions were annotated in the IntAct database and compared with other datasets. RNAcentral identifiers were used for unambiguous, stable identification of ncRNAs. The information about the interaction was enhanced by a detailed description of the cell types and experimental conditions, providing a computer-interpretable summary of the published data, integrated with the huge amount of protein interactions already gathered in the database. Furthermore, for each interaction, the binding sites of the microRNA are precisely mapped on a well-defined mRNA transcript of the target gene. This information is crucial to conceive and design optimal microRNA mimics or inhibitors to interfere in vivo with a deregulated process. As these approaches become more feasible, high-quality, reliable networks of microRNA interactions are needed to help, for instance, in the selection of the best target to be inhibited and to predict potential secondary off-target effects. Database URL https://www.ebi.ac.uk/intact.

Indexed as

MicroRNAsDatabases, FactualHumansRare DiseasesRNA, MessengerRNA, UntranslatedMicroRNAsRNA, MessengerRNA, Untranslated

Identifiers

PMID37819683
PMCPMC10566539
OpenAlexW4387547299

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.