Evidence map›Paper›PMID 32256005›Full record

ArticleBioinformation2019

Genomic profiling of Nipah virus using NGS driven RNA-Seq expression data.

Md Zakiul Hassan, Md Shakil Ahmed, Md Marufuzzaman Khan, Mohammad Ahsan Uddin, Fahmida Chowdhury, Md Kamruzzaman

Abstract read
In one paragraph

Article in Bioinformation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Md Zakiul HassanInfectious Diseases Division, International Centre for Diarrheal Disease Research, Bangladesh, Dhaka, Bangladesh.
Md Shakil AhmedInfectious Diseases Division, International Centre for Diarrheal Disease Research, Bangladesh, Dhaka, Bangladesh.
Md Marufuzzaman KhanDepartment of Public Health, The University of Tennessee, Knoxville, Tennessee, USA.
Mohammad Ahsan UddinDepartment of Statistics, University of Dhaka, Dhaka, Bangladesh.
Fahmida ChowdhuryInfectious Diseases Division, International Centre for Diarrheal Disease Research, Bangladesh, Dhaka, Bangladesh.
Md KamruzzamanInstitute of Bangladesh Studies, University of Rajshahi, Rajshahi, Bangladesh.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nipah virus (NiV) is an ssRNA, enveloped paramyxovirus in the genus Henipaveridae with a case fatality rate >70%. We analyzed the NGS RNA-Seq gene expression data of NiV to detect differentially expressed genes (DEGs) using the statistical R package limma. We used the Cytoscape, Ensembl, and STRING tools to construct the gene-gene interaction tree, phylogenetic gene tree and protein-protein interaction networks towards functional annotation. We identified 2707 DEGs (p-value <0.05) among 54359 NiV genes. The top-up and down-regulated DEGs were EPST1, MX1, IFIT3, RSAD2, OAS1, OASL, CMPK2 and SLFN13, SPAC977.17 using log2FC criteria with optimum threshold 1.0. The top 20 up-regulated gene-gene interaction trees showed no significant association between Nipah and Tularemia virus. Similarly, the top 20 down-regulated genes of neither Ebola nor Tularemia virus showed an association with the Nipah virus. Hence, we document the top-up and down-regulated DEGs for further consideration as biomarkers and candidates for vaccine or drug design against Nipah virus to combat infection.

Indexed as

limmaNGS RNA-SeqNipah virusPhylogenetic gene treeProtein-protein interaction network

Identifiers

PMID32256005
PMCPMC7088422

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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.