Evidence map›Paper›PMID 25610462›Full record

ArticleAdvances in bioinformatics2014

A Computational Approach for Predicting Role of Human MicroRNAs in MERS-CoV Genome.

Md Mahmudul Hasan, Rozina Akter, Md Shahin Ullah, Md Jaynul Abedin, G M Ahsan Ullah, Md Zakir Hossain

Open access · hybridAbstract read
In one paragraph

Article in Advances in bioinformatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 27% 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

32 citing papers in PubMed, 1 synthesis or guideline pooled it, 50 citations in OpenAlex.

  1. Pooled it
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  14. COVID-19: fighting the invisible enemy with microRNAs.Expert review of anti-infective therapy · 2021
    Review
  15. Saudi journal of biological sciences · 2021
    Article
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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

6 authors at 4 institutions in 2 countries.

Md Mahmudul HasanInstitute of Biomedical Studies, Baylor University, Waco, TX 76706, USA.
Rozina AkterBioMedNanoTech, Inc., 500 South University Avenue Suite 319, Little Rock, AR 72205, USA.
Md Shahin UllahBiotechnology and Genetic Engineering Discipline, Khulna University, Khulna 9208, Bangladesh.
Md Jaynul AbedinCivil Engineering Department, Bangladesh University of Engineering and Technology, Dhaka 1000, Bangladesh.
G M Ahsan UllahEnvironment Science Discipline, Khulna University, Khulna 9208, Bangladesh.
Md Zakir HossainBioMedNanoTech, Inc., 500 South University Avenue Suite 319, Little Rock, AR 72205, USA.ORCID 0000-0003-3679-612X
Khulna University · BDSouth University · USBangladesh University of Engineering and Technology · BDBaylor University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The new epidemic Middle East Respiratory Syndrome (MERS) is caused by a type of human coronavirus called MERS-CoV which has global fatality rate of about 30%. We are investigating potential antiviral therapeutics against MERS-CoV by using host microRNAs (miRNAs) which may downregulate viral gene expression to quell viral replication. We computationally predicted potential 13 cellular miRNAs from 11 potential hairpin sequences of MERS-CoV genome. Our study provided an interesting hypothesis that those miRNAs, that is, hsa-miR-628-5p, hsa-miR-6804-3p, hsa-miR-4289, hsa-miR-208a-3p, hsa-miR-510-3p, hsa-miR-18a-3p, hsa-miR-329-3p, hsa-miR-548ax, hsa-miR-3934-5p, hsa-miR-4474-5p, hsa-miR-7974, hsa-miR-6865-5p, and hsa-miR-342-3p, would be antiviral therapeutics against MERS-CoV infection.

Identifiers

PMID25610462
PMCPMC4283225
OpenAlexW2066944164

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.