Evidence map›Paper›PMID 26578605›Full record

ReviewNucleic acids research2016

Bioinformatic tools for microRNA dissection.

Most Mauluda Akhtar, Luigina Micolucci, Md Soriful Islam, Fabiola Olivieri, Antonio Domenico Procopio

Open access · goldAbstract readReview
In one paragraph

Review in Nucleic acids research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 103 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
103citing papers in PubMed, 2 pooled it
9.3field-weighted citation impact, top 1% 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

103 citing papers in PubMed, 2 syntheses or guidelines pooled it, 218 citations in OpenAlex.

  1. Pooled it
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  11. An Overview of miRNA and miRNA Target Analysis Tools.Methods in molecular biology (Clifton, N.J.) · 2025
    Review
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43 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

5 authors at 1 institution in 1 country.

Most Mauluda AkhtarLaboratory of Experimental Pathology, Department of Clinical and Molecular Sciences, Università Politecnica delle Marche, Ancona 60100, Italy Computational Pathology Unit, Department of Clinical and Molecular Sciences, Università Politecnica delle Marche, Ancona 60100, Italy mauluda82@gmail.com.
Luigina MicolucciLaboratory of Experimental Pathology, Department of Clinical and Molecular Sciences, Università Politecnica delle Marche, Ancona 60100, Italy Computational Pathology Unit, Department of Clinical and Molecular Sciences, Università Politecnica delle Marche, Ancona 60100, Italy.
Md Soriful IslamDepartment of Experimental and Clinical Medicine, Faculty of Medicine, Università Politecnica delle Marche, Ancona 60100, Italy.
Fabiola OlivieriLaboratory of Experimental Pathology, Department of Clinical and Molecular Sciences, Università Politecnica delle Marche, Ancona 60100, Italy Center of Clinical Pathology and Innovative Therapies, Italian National Research Center on Aging (INRCA-IRCCS), Ancona 60121, Italy.
Antonio Domenico ProcopioLaboratory of Experimental Pathology, Department of Clinical and Molecular Sciences, Università Politecnica delle Marche, Ancona 60100, Italy Center of Clinical Pathology and Innovative Therapies, Italian National Research Center on Aging (INRCA-IRCCS), Ancona 60121, Italy.
Marche Polytechnic University · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently, microRNAs (miRNAs) have emerged as important elements of gene regulatory networks. MiRNAs are endogenous single-stranded non-coding RNAs (~22-nt long) that regulate gene expression at the post-transcriptional level. Through pairing with mRNA, miRNAs can down-regulate gene expression by inhibiting translation or stimulating mRNA degradation. In some cases they can also up-regulate the expression of a target gene. MiRNAs influence a variety of cellular pathways that range from development to carcinogenesis. The involvement of miRNAs in several human diseases, particularly cancer, makes them potential diagnostic and prognostic biomarkers. Recent technological advances, especially high-throughput sequencing, have led to an exponential growth in the generation of miRNA-related data. A number of bioinformatic tools and databases have been devised to manage this growing body of data. We analyze 129 miRNA tools that are being used in diverse areas of miRNA research, to assist investigators in choosing the most appropriate tools for their needs.

Indexed as

AnimalsComputational BiologyGene-Environment InteractionGene Expression RegulationGene Regulatory NetworksGenetic Predisposition to DiseaseHumansMicroRNAsResearchRNA, MessengerMicroRNAsRNA, Messenger

Identifiers

PMID26578605
PMCPMC4705652
OpenAlexW2180078914

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.