ArticleNeural regeneration research2019
Challenges in microRNAs' targetome prediction and validation.
Article in Neural regeneration research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
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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.
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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.
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Who cites it
18 citing papers in PubMed, 28 citations in OpenAlex.
- Flunarizine changes microRNA expression in cell cultures and in a mouse model of spinal muscular atrophy.Scientific reports · 2026Article
- MicroRNA‑microbiome cross‑kingdom networks drive inflammatory bowel disease through dynamic regulatory ecosystems (Review).International journal of molecular medicine · 2026Review
- microRNA-497-5p-based screening identifies a novel synthetic lethal-type interaction via PKMYT1 and WEE1 in pleural mesothelioma.Molecular therapy. Nucleic acids · 2025Article
- MicroRNA gatekeepers: Orchestrating rhizospheric dynamics.Journal of integrative plant biology · 2025Review
- Recent advances in investigation of circRNA/lncRNA-miRNA-mRNA networks through RNA sequencing data analysis.Briefings in functional genomics · 2025Review
- Identification and characterization of host miRNAs that target the mouse mammary tumour virus (MMTV) genome.Open biology · 2024Article
- Gra-CRC-miRTar: The pre-trained nucleotide-to-graph neural networks to identify potential miRNA targets in colorectal cancer.Computational and structural biotechnology journal · 2024Article
- Gra-CRC-miRTar: The pre-trained nucleotide-to-graph neural networks to identify potential miRNA targets in colorectal cancer.bioRxiv : the preprint server for biology · 2024Article
- MicroRNAs and long non-coding RNAs during transcriptional regulation and latency of HIV and HTLV.Retrovirology · 2024Review
- Impact of MICA 3'UTR allelic variability on miRNA binding prediction, a bioinformatic approach.Frontiers in genetics · 2023Article
- Decoding microRNA drivers in atherosclerosis.Bioscience reports · 2022Review
- Comprehensive transcriptomic analysis of two RIL parents with contrasting salt responsiveness identifies polyadenylated and non-polyadenylated flower lncRNAs in chickpea.Plant biotechnology journal · 2022Article
- Machine Learning Based Methods and Best Practices of microRNA-Target Prediction and Validation.Advances in experimental medicine and biology · 2022Article
- Transcriptomic analysis reveals essential microRNAs after peripheral nerve injury.Neural regeneration research · 2021Article
- Integrative approaches for analysis of mRNA and microRNA high-throughput data.Computational and structural biotechnology journal · 2021Review
- Integrated miRNA/mRNA Counter-Expression Analysis Highlights Oxidative Stress-Related GenesInternational journal of molecular sciences · 2020Article
- MiRNA Regulatory Functions in Photoreceptors.Frontiers in cell and developmental biology · 2020Review
- Precision Medicine in Neurodegenerative Diseases: Some Promising Tips Coming from the microRNAs' World.Cells · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
MicroRNAs (miRNAs) are small RNA molecules with important roles in post-transcriptional regulation of gene expression. In recent years, the predicted number of miRNAs has skyrocketed, largely as a consequence of high-throughput sequencing technologies becoming ubiquitous. This dramatic increase in miRNA candidates poses multiple challenges in terms of data deposition, curation, and validation. Although multiple databases containing miRNA annotations and targets have been developed, ensuring data quality by validating miRNA-target interactions requires the efforts of the research community. In order to generate databases containing biologically active miRNAs, it is imperative to overcome a multitude of hurdles, including restricted miRNA expression patterns, distinct miRNA biogenesis machineries, and divergent miRNA-mRNA interaction dynamics. In the present review, we discuss recent advances and limitations in miRNA prediction, identification, and validation. Lastly, we focus on the most enriched neuronal miRNA, miR-124, and its gene regulatory network in human neurons, which has been revealed using a combined computational and experimental approach.
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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.