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  1. 1621

    Table 8_Feature genes identification and immune infiltration assessment in abdominal aortic aneurysm using WGCNA and machine learning algorithms.xls by Ming Xie (420493)

    Published 2024
    “…By intersecting the result of 3 machine learning algorithms and WGCNA, 3 feature genes were identified, including MRAP2, PPP1R14A, and PLN genes. …”
  2. 1622

    Table 7_Feature genes identification and immune infiltration assessment in abdominal aortic aneurysm using WGCNA and machine learning algorithms.xls by Ming Xie (420493)

    Published 2024
    “…By intersecting the result of 3 machine learning algorithms and WGCNA, 3 feature genes were identified, including MRAP2, PPP1R14A, and PLN genes. …”
  3. 1623

    Table 4_Feature genes identification and immune infiltration assessment in abdominal aortic aneurysm using WGCNA and machine learning algorithms.xls by Ming Xie (420493)

    Published 2024
    “…By intersecting the result of 3 machine learning algorithms and WGCNA, 3 feature genes were identified, including MRAP2, PPP1R14A, and PLN genes. …”
  4. 1624

    Table 6_Feature genes identification and immune infiltration assessment in abdominal aortic aneurysm using WGCNA and machine learning algorithms.xls by Ming Xie (420493)

    Published 2024
    “…By intersecting the result of 3 machine learning algorithms and WGCNA, 3 feature genes were identified, including MRAP2, PPP1R14A, and PLN genes. …”
  5. 1625

    Table 3_Feature genes identification and immune infiltration assessment in abdominal aortic aneurysm using WGCNA and machine learning algorithms.xls by Ming Xie (420493)

    Published 2024
    “…By intersecting the result of 3 machine learning algorithms and WGCNA, 3 feature genes were identified, including MRAP2, PPP1R14A, and PLN genes. …”
  6. 1626

    Table 2_Feature genes identification and immune infiltration assessment in abdominal aortic aneurysm using WGCNA and machine learning algorithms.xls by Ming Xie (420493)

    Published 2024
    “…By intersecting the result of 3 machine learning algorithms and WGCNA, 3 feature genes were identified, including MRAP2, PPP1R14A, and PLN genes. …”
  7. 1627

    Table 1_Feature genes identification and immune infiltration assessment in abdominal aortic aneurysm using WGCNA and machine learning algorithms.xls by Ming Xie (420493)

    Published 2024
    “…By intersecting the result of 3 machine learning algorithms and WGCNA, 3 feature genes were identified, including MRAP2, PPP1R14A, and PLN genes. …”
  8. 1628

    Data Sheet 3_Key gene screening and diagnostic model establishment for acute type a aortic dissection.csv by Yue Pan (267516)

    Published 2025
    “…</p>Methods<p>Transcriptome datasets from the Gene Expression Omnibus (GEO) database were analyzed using differential expression analysis, weighted gene co-expression network analysis (WGCNA), and machine learning algorithms (SVM, Random Forest, LASSO regression). Functional enrichment and immunoinfiltration analyses were performed to explore biological pathways and immune cell interactions. …”
  9. 1629

    Data Sheet 2_Key gene screening and diagnostic model establishment for acute type a aortic dissection.csv by Yue Pan (267516)

    Published 2025
    “…</p>Methods<p>Transcriptome datasets from the Gene Expression Omnibus (GEO) database were analyzed using differential expression analysis, weighted gene co-expression network analysis (WGCNA), and machine learning algorithms (SVM, Random Forest, LASSO regression). Functional enrichment and immunoinfiltration analyses were performed to explore biological pathways and immune cell interactions. …”
  10. 1630

    Table 1_Key gene screening and diagnostic model establishment for acute type a aortic dissection.xlsx by Yue Pan (267516)

    Published 2025
    “…</p>Methods<p>Transcriptome datasets from the Gene Expression Omnibus (GEO) database were analyzed using differential expression analysis, weighted gene co-expression network analysis (WGCNA), and machine learning algorithms (SVM, Random Forest, LASSO regression). Functional enrichment and immunoinfiltration analyses were performed to explore biological pathways and immune cell interactions. …”
  11. 1631

    Data Sheet 4_Key gene screening and diagnostic model establishment for acute type a aortic dissection.csv by Yue Pan (267516)

    Published 2025
    “…</p>Methods<p>Transcriptome datasets from the Gene Expression Omnibus (GEO) database were analyzed using differential expression analysis, weighted gene co-expression network analysis (WGCNA), and machine learning algorithms (SVM, Random Forest, LASSO regression). Functional enrichment and immunoinfiltration analyses were performed to explore biological pathways and immune cell interactions. …”
  12. 1632

    Data Sheet 5_Key gene screening and diagnostic model establishment for acute type a aortic dissection.csv by Yue Pan (267516)

    Published 2025
    “…</p>Methods<p>Transcriptome datasets from the Gene Expression Omnibus (GEO) database were analyzed using differential expression analysis, weighted gene co-expression network analysis (WGCNA), and machine learning algorithms (SVM, Random Forest, LASSO regression). Functional enrichment and immunoinfiltration analyses were performed to explore biological pathways and immune cell interactions. …”
  13. 1633

    Data Sheet 1_Key gene screening and diagnostic model establishment for acute type a aortic dissection.csv by Yue Pan (267516)

    Published 2025
    “…</p>Methods<p>Transcriptome datasets from the Gene Expression Omnibus (GEO) database were analyzed using differential expression analysis, weighted gene co-expression network analysis (WGCNA), and machine learning algorithms (SVM, Random Forest, LASSO regression). Functional enrichment and immunoinfiltration analyses were performed to explore biological pathways and immune cell interactions. …”
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