ArticleVirology journal2019
Identifying novel biomarkers of the pediatric influenza infection by weighted co-expression network analysis.
Article in Virology journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.
- Genome-Wide Association Studies of Hospitalized Influenza Identify Four Risk Loci and Reveal Shared and Unique Genetic Factors Compared With COVID-19.Influenza and other respiratory viruses · 2026Pooled it
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- SP110 Could be Used as a Potential Predictive and Therapeutic Biomarker for Oral Cancer.Molecular biotechnology · 2025Article
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- DiSignAtlas: an atlas of human and mouse disease signatures based on bulk and single-cell transcriptomics.Nucleic acids research · 2024Article
- Identification of functional pathways and potential genes associated with interferon signaling during human adenovirus type 7 infection by weighted gene coexpression network analysis.Archives of virology · 2023Article
- Multi-omics personalized network analyses highlight progressive disruption of central metabolism associated with COVID-19 severity.Cell systems · 2022Article
- Recent Advances in Plasma-Engineered Polymers for Biomarker-Based Viral Detection and Highly Multiplexed Analysis.Biosensors · 2022Review
- Identification and characterization of circular RNAs in association with the feed efficiency in Hu lambs.BMC genomics · 2022Article
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- Evaluating the cytotoxicity and pathogenicity of multi-walled carbon nanotube through weighted gene co-expression network analysis: a nanotoxicogenomics study.BMC genomic data · 2022Article
- Exploration of blood-derived coding and non-coding RNA diagnostic immunological panels for COVID-19 through a co-expressed-based machine learning procedure.Frontiers in immunology · 2022Article
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- Comprehensive Transcriptomic Analysis Identifies Novel Antiviral Factors Against Influenza A Virus Infection.Frontiers in immunology · 2021Article
- Coexpression Network Analysis of lncRNA Associated with Overexpression of DNMT1 in Esophageal Epithelial Cells.BioMed research international · 2021Article
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- High-Density Blood Transcriptomics Reveals Precision Immune Signatures of SARS-CoV-2 Infection in Hospitalized Individuals.Frontiers in immunology · 2021Article
- Computational Analysis of the Global Effects ofGenes · 2020Article
- The Possible Role of MOPr-DOPr Heteromers and Its Regulatory Protein RTP4 at Sensory Neurons in Relation to Pain Perception.Frontiers in cellular neuroscience · 2020Review
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDespite the high yearly prevalence of Influenza, the pathogenesis mechanism and involved genes have not been fully known. Finding the patterns and mapping the complex interactions between different genes help us to find the possible biomarkers and treatment targets.
methodsHerein, weighted gene co-expression network analysis (WGCNA) was employed to construct a co-expression network among genes identified by microarray analysis of the pediatric influenza-infected samples.
resultsThree of the 38 modules were found as the most related modules to influenza infection. At a functional level, we found that the genes in these modules regulate the immune responses, protein targeting, and defense to virus. Moreover, the analysis of differentially expressed genes disclosed 719 DEGs between the normal and infected subjects. The comprehensive investigation of genes in the module involved in immune system and viral defense (yellow module) revealed that SP110, HERC5, SAMD9L, RTP4, C19orf66, HELZ2, EPSTI1, and PHF11 which were also identified as DEGs (except C19orf66) have the potential to be as the biomarkers and also drug targeting for the treatment of pediatric influenza.
conclusionsThe WGCN analysis revealed co-expressed genes which were involved in the innate immune system and defense to virus. The differentially expressed genes in the identified modules can be considered for designing drug targets. Moreover, modules can help to find pathogenesis routes in the future.
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