ArticleRNA biology2019
miRBaseMiner, a tool for investigating miRBase content.
Article in RNA biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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.
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.
Who cites it
11 citing papers in PubMed, 29 citations in OpenAlex.
- The paradox of nuclear miRNAs: Mechanisms, therapeutic potential, and future directions.Non-coding RNA research · 2026Review
- Interplay between microRNAs and TGF-β signaling in T cells: implications for Th9 differentiation and immune pathogenesis.Frontiers in immunology · 2026Review
- Identification of Angiogenesis-Related Gene Signatures and Prediction of Potential Therapeutic Targets in Ulcerative Colitis Using Integrated Bioinformatics.Journal of inflammation research · 2024Article
- Sequential expression of miR-221-3p and miR-338-3p in Schwann cells as a therapeutic strategy to promote nerve regeneration and functional recovery.Neural regeneration research · 2023Article
- Comparison between articular chondrocytes and mesenchymal stromal cells for the production of articular cartilage implants.Frontiers in bioengineering and biotechnology · 2023Article
- The Role of MicroRNAs in Hyperlipidemia: From Pathogenesis to Therapeutical Application.Mediators of inflammation · 2022Review
- A study of transposable element-associated structural variations (TASVs) using a de novo-assembled Korean genome.Experimental & molecular medicine · 2021Article
- Article
- MicroRNA Expression Differences in Blood-Derived CD19+ B Cells of Methotrexate Treated Rheumatoid Arthritis Patients.Frontiers in immunology · 2021Article
- MirGeneDB 2.0: the metazoan microRNA complement.Nucleic acids research · 2020Article
- Jasmine: a Java pipeline for isomiR characterization in miRNA-Seq Data.Bioinformatics (Oxford, England) · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
microRNAs are small non-coding RNA molecules playing a central role in gene regulation. miRBase is the standard reference source for analysis and interpretation of experimental studies. However, the richness and complexity of the annotation is often underappreciated by users. Moreover, even for experienced users, the size of the resource can make it difficult to explore annotation to determine features such as species coverage, the impact of specific characteristics and changes between successive releases. A further consideration is that each new miRBase release contains entries that have had limited review and which may subsequently be removed in a future release to ensure the quality of annotation. To aid the miRBase user, we developed a software tool, miRBaseMiner, for investigating miRBase annotation and generating custom annotation sets. We apply the tool to characterize each release from v9.2 to v22 to examine how annotation has changed across releases and highlight some of the annotation features that users should keep in mind when using for miRBase for data analysis. These include: (1) entries with identical or very similar sequences; (2) entries with multiple annotated genome locations; (3) hairpin precursor entries with extremely low-estimated minimum free energy; (4) entries possessing reverse complementary; (5) entries with 3' poly(A) ends. As each of these factors can impact the identification of dysregulated features and subsequent clinical or biological conclusions, miRBaseMiner is a valuable resource for any user using miRBase as a reference source.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.