ArticleFrontiers in genetics2025
Bioinformatics-based identification of differentially expressed genes in endometrial carcinoma: implications for early diagnosis and prognostic stratification.
Article in Frontiers in genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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
1 citing paper in PubMed.
- Investigating the association of NBN gene polymorphisms with multiple cancers through statistical meta-analysis and bioinformatics insights.Biology methods & protocols · 2026Review
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4 authors.
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Abstract
Introduction: This study aims to identify differentially expressed genes (DEGs) in endometrial carcinoma (EC) through bioinformatics analysis and investigate their roles in early diagnosis and prognosis. Methods: EC-related gene datasets were retrieved from the NCBI and analyzed using R packages to screen for DEGs. Primers were designed for selected DEGs, and their expression levels were validated via qPCR. Logistic regression, survival analysis, Cox proportional hazards models, and random forest models were employed to evaluate associations between DEGs and clinical outcomes. Results: Bioinformatics analysis identified significantly upregulated genes ( Conclusion: The identified DEGs and clinical indicators hold significant potential for improving early diagnosis and prognostic evaluation in EC. These findings provide novel biomarkers and theoretical foundations for precision medicine, guiding risk stratification and personalized therapeutic strategies.
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