ArticleJournal of thoracic disease2023
Prediction of target genes in community-acquired pneumonia based on the bioinformatics method.
Article in Journal of thoracic disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
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Who cites it
2 citing papers in PubMed, 4 citations in OpenAlex.
- Interleukins in community-acquired pneumonia: from biomarkers to precision medicine.Frontiers in immunology · 2026Review
- Epidemiological characteristics of severe community-acquired pneumonia in children admitted to two tertiary hospitals in Shihezi, Xinjiang Region, China in 2023: a cross-sectional analysis.Journal of thoracic disease · 2024Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: To screen the related genes of community-acquired pneumonia (CAP) by bioinformatics technology, and to analyze the clinical value of key genes. Methods: Gene chip data sets containing CAP patients and normal controls were screened from the Gene Expression Omnibus (GEO) database. The downregulated differentially expressed genes (DEGs) were screened using a gene expression analysis tool (GEO2R). Simultaneously, gene set enrichment analysis (GSEA) was used to explore the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and core genes related to CAP. The candidate genes were then intersected with the genes reported in Online Mendelian Inheritance in Man (OMIM), and the clinical value of these candidate genes was examined based on a literature search. Finally, the clinical data of the CAP patients were retrospectively analyzed. Detect the type of pathogenic bacteria in bronchial-alveolar lavage fluid (BALF) using metagenomics next-generation sequencing (mNGS) high throughput sequencing technology, and detect the expression of key genes through liquid based cell immunohistochemistry to analyze the correlation between pathogenic bacteria and key genes. Results: Through the intersection of Venn diagrams, 175 co-expressed downregulated DEGs related to CAP were identified. A total of 4 candidate genes, including Conclusions: The identification of the key gene
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Registered trials
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