Evidence map›Paper›PMID 34432289›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2022

44 Current Challenges in miRNomics.

Bünyamin Akgül, Peter F Stadler, Liam J Hawkins, Hanane Hadj-Moussa, Kenneth B Storey, Kemal Ergin, Rahmi Çetinkaya, Alexandre R Paschoal, Pedro G Nachtigall, Yusuf Tutar and 2 more

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Review
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

12 authors.

Bünyamin AkgülMolecular Biology and Genetics, Izmir Institute of Technology, Urla, Izmir, Turkey.
Peter F StadlerBioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, University of Leipzig, Leipzig, Germany.
Liam J HawkinsDepartment of Biology, Carleton University, Ottawa, ON, Canada.
Hanane Hadj-MoussaDepartment of Biology, Carleton University, Ottawa, ON, Canada.
Kenneth B StoreyDepartment of Biology, Carleton University, Ottawa, ON, Canada.
Kemal ErginDepartment of Histology and Embryology, Medical Faculty, Aydın Adnan Menderes University, Aydın, Turkey.
Rahmi ÇetinkayaDepartment of Basic Oncology and Cancer Biology, Institute of Health Sciences, Aydın Adnan Menderes University, Aydın, Turkey.
Alexandre R PaschoalDepartment of Computer Science and Bioinformatics and Pattern Recognition Group, Universidade Tecnológica Federal do Paraná (UTFPR), Cornélio Procópio, Brazil.
Pedro G NachtigallLaboratório Especial de Toxinologia Aplicada, CeTICS, Instituto Butantan, São Paulo, SP, Brazil.
Yusuf TutarDivision of Biochemistry, Department of Basic Pharmaceutical Sciences, Hamidiye Faculty of Pharmacy & Division of Molecular Medicine, Hamidiye Institute of Health Sciences, University of Health Sciences, Istanbul, Turkey.
Malik YousefDepartment of Information System, Galilee Digital Health Research Center (GDH), Zefat Academic College, Zefat, Israel.
Jens AllmerMedical Informatics and Bioinformatics, Institute for Measurement Engineering and Sensor Technology, Hochschule Ruhr West, University of Applied Sciences, Mülheim adR, Germany. jens@allmer.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mature microRNAs (miRNAs) are short RNA sequences about 18-24 nucleotide long, which provide the recognition key within RISC for the posttranscriptional regulation of target RNAs. Considering the canonical pathway, mature miRNAs are produced via a multistep process. Their transcription (pri-miRNAs) and first processing step via the microprocessor complex (pre-miRNAs) occur in the nucleus. Then they are exported into the cytosol, processed again by Dicer (dsRNA) and finally a single strand (mature miRNA) is incorporated into RISC (miRISC). The sequence of the incorporated miRNA provides the function of RNA target recognition via hybridization. Following binding of the target, the mRNA is either degraded or translation is inhibited, which ultimately leads to less protein production. Conversely, it has been shown that binding within the 5' UTR of the mRNA can lead to an increase in protein product. Regulation of homeostasis is very important for a cell; therefore, all steps in the miRNA-based regulation pathway, from transcription to the incorporation of the mature miRNA into RISC, are under tight control. While much research effort has been exerted in this area, the knowledgebase is not sufficient for accurately modelling miRNA regulation computationally. The computational prediction of miRNAs is, however, necessary because it is not feasible to investigate all possible pairs of a miRNA and its target, let alone miRNAs and their targets. We here point out open challenges important for computational modelling or for our general understanding of miRNA-based regulation and show how their investigation is beneficial. It is our hope that this collection of challenges will lead to their resolution in the near future.

Indexed as

Gene Expression RegulationGenomicsMicroRNAsRNA, MessengerMicroRNAsRNA, MessengerChallengesMature miRNAmiRNA predictionmiRNA targetingmiRNomicsRISC

Identifiers

What OpenQuestion holds

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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.