Evidence map›Paper›PMID 32143373›Full record

ArticleInternational journal of molecular sciences2020

MiR&moRe2: A Bioinformatics Tool to Characterize microRNAs and microRNA-Offset RNAs from Small RNA-Seq Data.

Enrico Gaffo, Michele Bortolomeazzi, Andrea Bisognin, Piero Di Battista, Federica Lovisa, Lara Mussolin, Stefania Bortoluzzi

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.8field-weighted citation impact, top 34% 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

9 citing papers in PubMed, 13 citations in OpenAlex.

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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

7 authors at 1 institution in 1 country.

Enrico GaffoDepartment of Molecular Medicine, University of Padova, 35121 Padova, Italy.ORCID 0000-0001-6338-7677
Michele BortolomeazziDepartment of Molecular Medicine, University of Padova, 35121 Padova, Italy.
Andrea BisogninDepartment of Molecular Medicine, University of Padova, 35121 Padova, Italy.
Piero Di BattistaDivision of Pediatric Hematology, Department of Women's and Children's Health, University of Padova, 35128 Padova, Italy.
Federica LovisaDivision of Pediatric Hematology, Department of Women's and Children's Health, University of Padova, 35128 Padova, Italy.
Lara MussolinDivision of Pediatric Hematology, Department of Women's and Children's Health, University of Padova, 35128 Padova, Italy.
Stefania BortoluzziDepartment of Molecular Medicine, University of Padova, 35121 Padova, Italy.ORCID 0000-0001-8240-3070
University of Padua · IT

Funding

Associazione Italiana per la Ricerca sul Cancro Investigator Grant - IG 2017 #20052Associazione Italiana per la Ricerca sul Cancro Investigator Grant - IG 2018 #21385Fondazione Cassa di Risparmio di Padova e Rovigo Grant 17/03Fondazione Umberto Veronesi Fellowships 2019Ministero dell'Istruzione, dell'Università e della Ricerca PRIN 2017 #2017PPS2X4_003Roche Roche per la Ricerca 2018
6 · The paper itself

Abstract

MicroRNA-offset RNAs (moRNAs) are microRNA-like small RNAs generated by microRNA precursors. To date, little is known about moRNAs and bioinformatics tools to inspect their expression are still missing. We developed miR&moRe2, the first bioinformatics method to consistently characterize microRNAs, moRNAs, and their isoforms from small RNA sequencing data. To illustrate miR&moRe2 discovery power, we applied it to several published datasets. MoRNAs identified by miR&moRe2 were in agreement with previous research findings. Moreover, we observed that moRNAs and new microRNAs predicted by miR&moRe2 were downregulated upon the silencing of the microRNA-biogenesis pathway. Further, in a sizeable dataset of human blood cell populations, tens of novel miRNAs and moRNAs were discovered, some of them with significantly varied expression levels among the cell types. Results demonstrate that miR&moRe2 is a valid tool for a comprehensive study of small RNAs generated from microRNA precursors and could help to investigate their biogenesis and function.

Indexed as

AlgorithmsComputational BiologyGene Expression ProfilingGene Expression RegulationGene SilencingGenome, HumanHumansMicroRNAsRNA-SeqRNA, Small InterferingSoftwareMicroRNAsRNA, Small InterferingbioinformaticsisomiRsisomoRsmiRNAsmoRNAsnon-coding RNAssmall RNA prediction

Identifiers

PMID32143373
PMCPMC7084216
OpenAlexW3009983268

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.