Evidence map›Paper›PMID 29036653›Full record

ArticleNucleic acids research2018

miRCarta: a central repository for collecting miRNA candidates.

Christina Backes, Tobias Fehlmann, Fabian Kern, Tim Kehl, Hans-Peter Lenhof, Eckart Meese, Andreas Keller

Abstract read
In one paragraph

Article in Nucleic acids research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers.

0numbers the graph read from it
0cells of the map it votes in
64citing 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

64 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. IsomiR Utility in Amyotrophic Lateral Sclerosis Prognostication.medRxiv : the preprint server for health sciences · 2025
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Review
  12. Review
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  14. Review
  15. Generation of de novo miRNAs from template switching during DNA replication.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  16. Review
  17. Review
  18. Article
  19. Article
  20. Article

4 more citing papers are in PubMed but not listed here.

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

7 authors.

Christina BackesChair for Clinical Bioinformatics, Saarland Informatics Campus, Saarland University, Germany.
Tobias FehlmannChair for Clinical Bioinformatics, Saarland Informatics Campus, Saarland University, Germany.
Fabian KernChair for Clinical Bioinformatics, Saarland Informatics Campus, Saarland University, Germany.
Tim KehlCenter for Bioinformatics, Saarland Informatics Campus, Saarland University, Germany.
Hans-Peter LenhofCenter for Bioinformatics, Saarland Informatics Campus, Saarland University, Germany.
Eckart MeeseInstitute for Human Genetics, Medical School, Saarland University, Germany.
Andreas KellerChair for Clinical Bioinformatics, Saarland Informatics Campus, Saarland University, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The continuous increase of available biological data as consequence of modern high-throughput technologies poses new challenges for analysis techniques and database applications. Especially for miRNAs, one class of small non-coding RNAs, many algorithms have been developed to predict new candidates from next-generation sequencing data. While the amount of publications describing novel miRNA candidates keeps steadily increasing, the current gold standard database for miRNAs - miRBase - has not been updated since June 2014. As a result, publications describing new miRNA candidates in the last three to five years might have a substantial overlap of candidates without noticing. With miRCarta we implemented a database to collect novel miRNA candidates and augment the information provided by miRBase. In the first stage, miRCarta is thought to be a highly sensitive collection of potential miRNA candidates with a high degree of analysis functionality, annotations and details on each miRNA. We added-besides the full content of the miRBase-12,857 human miRNA precursors to miRCarta. Users can match their own predictions to the entries of miRCarta to reduce potential redundancies in their studies. miRCarta provides the most comprehensive collection of human miRNAs and miRNA candidates to form a basis for further refinement and validation studies. The database is freely accessible at https://mircarta.cs.uni-saarland.de/.

Indexed as

Databases, Nucleic AcidAnimalsHigh-Throughput Nucleotide SequencingHumansMicroRNAsMolecular Sequence AnnotationNucleic Acid ConformationRNA PrecursorsSequence Analysis, RNAMicroRNAsRNA Precursors

Identifiers

PMID29036653
PMCPMC5753177

What OpenQuestion holds

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LicenceCC BY-NC
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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.