Evidence map›Paper›PMID 32887511›Full record

ReviewNon-coding RNA2020

Non-Coding RNA Databases in Cardiovascular Research.

Deepak Balamurali, Monika Stoll

Open access · goldAbstract readReview
In one paragraph

Review in Non-coding RNA, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 2 pooled it
0.8field-weighted citation impact, top 33% 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

9 citing papers in PubMed, 2 syntheses or guidelines pooled it, 15 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Review
  5. Non-coding RNA research · 2024
    Review
  6. RNA-Chrom: a manually curated analytical database of RNA-chromatin interactome.Database : the journal of biological databases and curation · 2023
    Article
  7. Article
  8. Review
  9. 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

2 authors at 1 institution in 1 country.

Deepak BalamuraliGenetic Epidemiology and Statistical Genetics, Department of Biochemistry, CARIM School for Cardiovascular Diseases, Maastricht University, 6229 ER Maastricht, The Netherlands.ORCID 0000-0001-8669-0150
Monika StollGenetic Epidemiology and Statistical Genetics, Department of Biochemistry, CARIM School for Cardiovascular Diseases, Maastricht University, 6229 ER Maastricht, The Netherlands.ORCID 0000-0002-2711-4281
Maastricht University · NL

Funding

H2020 Marie Skłodowska-Curie Actions 813716
6 · The paper itself

Abstract

Cardiovascular diseases (CVDs) are of multifactorial origin and can be attributed to several genetic and environmental components. CVDs are the leading cause of mortality worldwide and they primarily damage the heart and the vascular system. Non-coding RNA (ncRNA) refers to functional RNA molecules, which have been transcribed into DNA but do not further get translated into proteins. Recent transcriptomic studies have identified the presence of thousands of ncRNA molecules across species. In humans, less than 2% of the total genome represents the protein-coding genes. While the role of many ncRNAs is yet to be ascertained, some long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) have been associated with disease progression, serving as useful diagnostic and prognostic biomarkers. A plethora of data repositories specialized in ncRNAs have been developed over the years using publicly available high-throughput data from next-generation sequencing and other approaches, that cover various facets of ncRNA research like basic and functional annotation, expressional profile, structural and molecular changes, and interaction with other biomolecules. Here, we provide a compendium of the current ncRNA databases relevant to cardiovascular research.

Indexed as

cardiovascular diseasesdatabasencRNAnon-coding

Identifiers

PMID32887511
PMCPMC7549374
OpenAlexW3082248099

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.