ArticleFrontiers in immunology2025
Integrating machine learning and multi-omics analysis to reveal nucleotide metabolism-related immune genes and their functional validation in ischemic stroke.
Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- TMC6 Protects Against Ischemic Neuronal Injury by Activating Rap1/Rac1 Signaling to Restore Mitochondrial Dynamics and Mitophagy.Molecular neurobiology · 2026Article
- Mechanisms and integrative machine learning approaches to blood-brain barrier biomarker profiling for personalized ischemic stroke management.Physiological reports · 2026Review
- Multi-omics and artificial intelligence for precision drug discovery and potential clinical applications.Signal transduction and targeted therapy · 2026Review
- Integrated machine learning and transcriptomics reveal immune infiltration-related orthologous transcription genes in cerebral ischemic injury.Frontiers in immunology · 2026Article
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Authors and funding
8 authors.
Funding
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Abstract
Background: Ischemic stroke (IS) is a major global cause of death and disability, linked to nucleotide metabolism imbalances. This study aimed to identify nucleotide metabolism-related genes associated with IS and explore their roles in disease mechanisms for new diagnostic and therapeutic strategies. Methods: IS gene expression data were sourced from the GEO database. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were conducted in R, intersecting results with nucleotide metabolism-related genes. Functional enrichment and connectivity map (cMAP) analyses identified key genes and potential therapeutic agents. Core immune-related genes were determined using LASSO regression, SVM-RFE, and Random Forest algorithms. Immune cell infiltration levels and correlations were analyzed via CIBERSORT. Single-cell RNA sequencing (scRNA-seq) data and molecular docking assessed gene expression, localization, and gene-drug binding. Results: Thirty-three candidate genes were identified, mainly involved in immune and inflammatory responses. Conclusion: This study underscores the role of nucleotide metabolism in IS, identifying
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