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Showing 4,401 - 4,419 results of 4,419 for search '(((( data code algorithm ) OR ( data processing algorithm ))) OR ( element network algorithm ))', query time: 0.27s Refine Results
  1. 4401
    The overall framework of this study.

    The overall framework of this study. by Tianbao Feng (21722233)

    Published 2025
    “…Additionally, a protein-protein interaction (PPI) network was established to identify hub genes, and 8 machine learning algorithms were used to narrowed down hub genes. <i>BMX</i> and <i>CASP5</i> were consistently identified across all algorithms. …”
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  2. 4402
    PANoptosis related genes.

    PANoptosis related genes. by Tianbao Feng (21722233)

    Published 2025
    “…Additionally, a protein-protein interaction (PPI) network was established to identify hub genes, and 8 machine learning algorithms were used to narrowed down hub genes. <i>BMX</i> and <i>CASP5</i> were consistently identified across all algorithms. …”
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  3. 4403
    Table 3_Athero-oncology perspective: identifying hub genes for atherosclerosis diagnosis using machine learning.csv

    Table 3_Athero-oncology perspective: identifying hub genes for atherosclerosis diagnosis using machine learning.csv by Liyan Zhao (340225)

    Published 2025
    “…UMAP plots from single-cell RNA sequencing data were used to analyze the expression patterns of hub genes, particularly focusing on macrophage-like SMCs in SMC lineage-traced mouse models. …”
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  4. 4404
    Image 1_Athero-oncology perspective: identifying hub genes for atherosclerosis diagnosis using machine learning.tif

    Image 1_Athero-oncology perspective: identifying hub genes for atherosclerosis diagnosis using machine learning.tif by Liyan Zhao (340225)

    Published 2025
    “…UMAP plots from single-cell RNA sequencing data were used to analyze the expression patterns of hub genes, particularly focusing on macrophage-like SMCs in SMC lineage-traced mouse models. …”
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  5. 4405
    Table 5_Athero-oncology perspective: identifying hub genes for atherosclerosis diagnosis using machine learning.csv

    Table 5_Athero-oncology perspective: identifying hub genes for atherosclerosis diagnosis using machine learning.csv by Liyan Zhao (340225)

    Published 2025
    “…UMAP plots from single-cell RNA sequencing data were used to analyze the expression patterns of hub genes, particularly focusing on macrophage-like SMCs in SMC lineage-traced mouse models. …”
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  6. 4406
    Image 4_Athero-oncology perspective: identifying hub genes for atherosclerosis diagnosis using machine learning.tif

    Image 4_Athero-oncology perspective: identifying hub genes for atherosclerosis diagnosis using machine learning.tif by Liyan Zhao (340225)

    Published 2025
    “…UMAP plots from single-cell RNA sequencing data were used to analyze the expression patterns of hub genes, particularly focusing on macrophage-like SMCs in SMC lineage-traced mouse models. …”
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  7. 4407
    Table 2_Athero-oncology perspective: identifying hub genes for atherosclerosis diagnosis using machine learning.xls

    Table 2_Athero-oncology perspective: identifying hub genes for atherosclerosis diagnosis using machine learning.xls by Liyan Zhao (340225)

    Published 2025
    “…UMAP plots from single-cell RNA sequencing data were used to analyze the expression patterns of hub genes, particularly focusing on macrophage-like SMCs in SMC lineage-traced mouse models. …”
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  8. 4408
    Image 3_Athero-oncology perspective: identifying hub genes for atherosclerosis diagnosis using machine learning.tif

    Image 3_Athero-oncology perspective: identifying hub genes for atherosclerosis diagnosis using machine learning.tif by Liyan Zhao (340225)

    Published 2025
    “…UMAP plots from single-cell RNA sequencing data were used to analyze the expression patterns of hub genes, particularly focusing on macrophage-like SMCs in SMC lineage-traced mouse models. …”
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  9. 4409
    Table 1_Associations between metabolic-inflammatory biomarkers and Helicobacter pylori infection: an interpretable machine learning prediction approach.docx

    Table 1_Associations between metabolic-inflammatory biomarkers and Helicobacter pylori infection: an interpretable machine learning prediction approach.docx by Yue Zhang (30585)

    Published 2025
    “…In the external Chinese cohort, the TyG association attenuated (P = 0.057), but higher TyG/HDL-C quartiles remained significant. Among 11 algorithms, Random Forest (RF) and Gaussian Process (GP) achieved the highest AUCs on the training set (both 0.97) but dropped markedly on the validation set (both 0.75), indicating overfitting. …”
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  10. 4410
    Table 6_Athero-oncology perspective: identifying hub genes for atherosclerosis diagnosis using machine learning.csv

    Table 6_Athero-oncology perspective: identifying hub genes for atherosclerosis diagnosis using machine learning.csv by Liyan Zhao (340225)

    Published 2025
    “…UMAP plots from single-cell RNA sequencing data were used to analyze the expression patterns of hub genes, particularly focusing on macrophage-like SMCs in SMC lineage-traced mouse models. …”
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  11. 4411
    Table 1_Athero-oncology perspective: identifying hub genes for atherosclerosis diagnosis using machine learning.csv

    Table 1_Athero-oncology perspective: identifying hub genes for atherosclerosis diagnosis using machine learning.csv by Liyan Zhao (340225)

    Published 2025
    “…UMAP plots from single-cell RNA sequencing data were used to analyze the expression patterns of hub genes, particularly focusing on macrophage-like SMCs in SMC lineage-traced mouse models. …”
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  12. 4412
    Image 5_Athero-oncology perspective: identifying hub genes for atherosclerosis diagnosis using machine learning.tif

    Image 5_Athero-oncology perspective: identifying hub genes for atherosclerosis diagnosis using machine learning.tif by Liyan Zhao (340225)

    Published 2025
    “…UMAP plots from single-cell RNA sequencing data were used to analyze the expression patterns of hub genes, particularly focusing on macrophage-like SMCs in SMC lineage-traced mouse models. …”
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  13. 4413
    Table 7_Athero-oncology perspective: identifying hub genes for atherosclerosis diagnosis using machine learning.csv

    Table 7_Athero-oncology perspective: identifying hub genes for atherosclerosis diagnosis using machine learning.csv by Liyan Zhao (340225)

    Published 2025
    “…UMAP plots from single-cell RNA sequencing data were used to analyze the expression patterns of hub genes, particularly focusing on macrophage-like SMCs in SMC lineage-traced mouse models. …”
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  14. 4414
    Table 4_Athero-oncology perspective: identifying hub genes for atherosclerosis diagnosis using machine learning.csv

    Table 4_Athero-oncology perspective: identifying hub genes for atherosclerosis diagnosis using machine learning.csv by Liyan Zhao (340225)

    Published 2025
    “…UMAP plots from single-cell RNA sequencing data were used to analyze the expression patterns of hub genes, particularly focusing on macrophage-like SMCs in SMC lineage-traced mouse models. …”
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  15. 4415
    Image 2_Athero-oncology perspective: identifying hub genes for atherosclerosis diagnosis using machine learning.tif

    Image 2_Athero-oncology perspective: identifying hub genes for atherosclerosis diagnosis using machine learning.tif by Liyan Zhao (340225)

    Published 2025
    “…UMAP plots from single-cell RNA sequencing data were used to analyze the expression patterns of hub genes, particularly focusing on macrophage-like SMCs in SMC lineage-traced mouse models. …”
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  16. 4416
    EKC virus-specific HMGB1 secretion.

    EKC virus-specific HMGB1 secretion. by Amrita Saha (1771837)

    Published 2025
    “…Sequence differences across types are color coded and sequence conservation are shown with dots. …”
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  17. 4417
    Primer sequences of <i>Bm</i>x and β-actin.

    Primer sequences of <i>Bm</i>x and β-actin. by Tianbao Feng (21722233)

    Published 2025
    “…Additionally, a protein-protein interaction (PPI) network was established to identify hub genes, and 8 machine learning algorithms were used to narrowed down hub genes. <i>BMX</i> and <i>CASP5</i> were consistently identified across all algorithms. …”
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  18. 4418
    Table 1_Demethylase FTO mediates m6A modification of ENST00000619282 to promote apoptosis escape in rheumatoid arthritis and the intervention effect of Xinfeng Capsule.docx

    Table 1_Demethylase FTO mediates m6A modification of ENST00000619282 to promote apoptosis escape in rheumatoid arthritis and the intervention effect of Xinfeng Capsule.docx by Fanfan Wang (1669474)

    Published 2025
    “…The m6A modification of long non-coding RNAs (lncRNAs) plays a critical regulatory role in RA pathogenesis. …”
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  19. 4419
    <b>Neural Symbolic Vault: Symbolic Species and</b> <b>DNA Co-Encoding Research Bundle v1.0 (A+M[S] Archive)</b>

    <b>Neural Symbolic Vault: Symbolic Species and</b> <b>DNA Co-Encoding Research Bundle v1.0 (A+M[S] Archive)</b> by Jeffrey Siergiej (20937434)

    Published 2025
    “…Symbolic DNA encoding structures, vector libraries, and derived algorithms are under private protection via in-house symbolic token ledger and mutation tracking systems.…”
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