Evidence map›Paper›PMID 33223819›Full record

ArticleCancer informatics2020

Bioinformatics Analysis of Differentially Expressed Genes and miRNAs in Low-Grade Gliomas.

Mohammed Amine Bendahou, Azeddine Ibrahimi, Mahjouba Boutarbouch

Open access · goldAbstract read
In one paragraph

Article in Cancer informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.3field-weighted citation impact, top 49% 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

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. Article
  3. LncRNACancer management and research · 2021
    Article
  4. Article
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

3 authors at 1 institution in 1 country.

Mohammed Amine BendahouMedical Biotechnology Laboratory (MedBiotech), BioInova Research Center, Medical and Pharmacy School, Mohammed V University in Rabat, Morocco.ORCID https://orcid.org/0000-0003-3299-6458
Azeddine IbrahimiMedical Biotechnology Laboratory (MedBiotech), BioInova Research Center, Medical and Pharmacy School, Mohammed V University in Rabat, Morocco.
Mahjouba BoutarbouchDepartment of Neurosurgery, Hospital of Specialties, CHU Ibn Sina, Rabat, Medical and Pharmacy School, Mohammed V University in Rabat, Morocco.
Mohammed V University · MA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Low-grade glioma is the most common type of primary intracranial tumor. In the last 3 years, new observations of molecular precursors in adults with gliomas have led to a modification in the histopathologic classification of these brain tumors. Among the biomarkers that have been highlighted, we have the micro RNAs (miRNAs) which play a crucial role in the regulation of gene expression and the long noncoding RNAs (lncRNAs) controlling various cellular and metabolic pathways. In our study, large-scale data on sequenced RNA and miRNAs from 516 patients were obtained from the Cancer Genome Atlas database by the TCGAbiolinks package. We identified the differential expression of miRNAs and genes using the Limma package and then we used the ClusterProfiler package for annotations of the biological pathways of the expressed genes, the survival package to estimate the survival analysis, and the GDCRNATools package to determine miRNAs-genes and miRNAs-lncRNAs interactions. We obtained a significant correlation between the miRNAs identified and the overall survival of the patients (log-rank

Indexed as

epigeneticsgene expressionlncRNALow-grade gliomamiRNAnetworkTCGAtranscriptomics

Identifiers

PMID33223819
PMCPMC7649870
OpenAlexW3096518566

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.