Evidence map›Paper›PMID 33673400›Full record

ArticleGenes2021

miRNAture-Computational Detection of microRNA Candidates.

Cristian A Velandia-Huerto, Jörg Fallmann, Peter F Stadler

Open access · goldAbstract read
In one paragraph

Article in Genes, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 51% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. The Draft Genome of Chinese Endemic SpeciesFrontiers in genetics · 2022
    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

3 authors at 2 institutions in 4 countries.

Cristian A Velandia-HuertoBioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, Leipzig University, D-04107 Leipzig, Germany.ORCID 0000-0002-1370-3560
Jörg FallmannBioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, Leipzig University, D-04107 Leipzig, Germany.ORCID 0000-0002-4573-9939
Peter F StadlerBioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, Leipzig University, D-04107 Leipzig, Germany.ORCID 0000-0002-5016-5191
Leipzig University · DEUniversity of Vienna · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Homology-based annotation of short RNAs, including microRNAs, is a difficult problem because their inherently small size limits the available information. Highly sensitive methods, including parameter optimized blast, nhmmer, or cmsearch runs designed to increase sensitivity inevitable lead to large numbers of false positives, which can be detected only by detailed analysis of specific features typical for a RNA family and/or the analysis of conservation patterns in structure-annotated multiple sequence alignments. The miRNAture pipeline implements a workflow specific to animal microRNAs that automatizes homology search and validation steps. The miRNAture pipeline yields very good results for a large number of "typical" miRBase families. However, it also highlights difficulties with atypical cases, in particular microRNAs deriving from repetitive elements and microRNAs with unusual, branched precursor structures and atypical locations of the mature product, which require specific curation by domain experts.

Indexed as

Computational BiologySequence AlignmentSequence Analysis, RNASoftwareMicroRNAsMicroRNAsconsensus structurehomology searchMicroRNAmultiple sequence alignmentrepetitive elementRNA secondary structure

Identifiers

PMID33673400
PMCPMC7996739
OpenAlexW3134971841

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.