ArticleFrontiers in neuroscience2022
Identification of hub genes of Parkinson's disease through bioinformatics analysis.
Article in Frontiers in neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- Comprehensive analysis of cuproptosis-related lncRNAs in immunotherapy response and prognosis in papillary thyroid cancer.Gland surgery · 2026Article
- Genome-wide DNA methylation profiling in COVID-19 positive patients reveals alterations in pathways linked to neurological dysfunction.Clinical epigenetics · 2026Article
- Article
- Review
- Integrated bioinformatics analysis for exploring potential biomarkers related to Parkinson's disease progression.BMC medical genomics · 2024Article
- Investigation of the Mechanism ofInternational journal of general medicine · 2024Article
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Authors and funding
6 authors.
Funding
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Abstract
Parkinson's disease (PD) is a common neurodegenerative disease, and there is still a lack of effective diagnostic and treatment methods. This study aimed to search for hub genes that might serve as diagnostic or therapeutic targets for PD. All the analysis was performed in R software. The expression profile data of PD (number: GSE7621) was acquired from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) associated with PD were screened by the "Limma" package of the R software. Key genes associated with PD were screened by the "WGCNA" package of the R software. Target genes were screened by merging the results of "Limma" and "WGCNA." Enrichment analysis of target genes was performed by Gene Ontology (GO), Disease Ontology (DO), and Kyoto Enrichment of Genes and Genomes (KEGG). Machine learning algorithms were employed to screen for hub genes. Nomogram was constructed using the "rms" package. And the receiver operating characteristic curve (ROC) was plotted to detect and validate our prediction model sensitivity and specificity. Additional expression profile data of PD (number: GSE20141) was acquired from the GEO database to validate the nomogram. GSEA was used to determine the biological functions of the hub genes. Finally,
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