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Showing 1,241 - 1,260 results of 1,346 for search '(( algorithm api function ) OR ((( algorithm python function ) OR ( algorithm b function ))))', query time: 0.59s Refine Results
  1. 1241
    Image 4_Identification of three T cell-related genes as diagnostic and prognostic biomarkers for triple-negative breast cancer and exploration of potential mechanisms.tif

    Image 4_Identification of three T cell-related genes as diagnostic and prognostic biomarkers for triple-negative breast cancer and exploration of potential mechanisms.tif by Zhi-Chuan He (21563657)

    Published 2025
    “…</p>Conclusion<p>CACNA1H, KCNJ11, and S100B are potential diagnostic and prognostic biomarkers in TNBC. …”
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  2. 1242
    Image 3_Identification of three T cell-related genes as diagnostic and prognostic biomarkers for triple-negative breast cancer and exploration of potential mechanisms.tif

    Image 3_Identification of three T cell-related genes as diagnostic and prognostic biomarkers for triple-negative breast cancer and exploration of potential mechanisms.tif by Zhi-Chuan He (21563657)

    Published 2025
    “…</p>Conclusion<p>CACNA1H, KCNJ11, and S100B are potential diagnostic and prognostic biomarkers in TNBC. …”
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  3. 1243
    Table 1_Identification of three T cell-related genes as diagnostic and prognostic biomarkers for triple-negative breast cancer and exploration of potential mechanisms.xlsx

    Table 1_Identification of three T cell-related genes as diagnostic and prognostic biomarkers for triple-negative breast cancer and exploration of potential mechanisms.xlsx by Zhi-Chuan He (21563657)

    Published 2025
    “…</p>Conclusion<p>CACNA1H, KCNJ11, and S100B are potential diagnostic and prognostic biomarkers in TNBC. …”
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  4. 1244
    Image 1_Identification of three T cell-related genes as diagnostic and prognostic biomarkers for triple-negative breast cancer and exploration of potential mechanisms.tif

    Image 1_Identification of three T cell-related genes as diagnostic and prognostic biomarkers for triple-negative breast cancer and exploration of potential mechanisms.tif by Zhi-Chuan He (21563657)

    Published 2025
    “…</p>Conclusion<p>CACNA1H, KCNJ11, and S100B are potential diagnostic and prognostic biomarkers in TNBC. …”
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  5. 1245
    Table 3_Identification of three T cell-related genes as diagnostic and prognostic biomarkers for triple-negative breast cancer and exploration of potential mechanisms.xlsx

    Table 3_Identification of three T cell-related genes as diagnostic and prognostic biomarkers for triple-negative breast cancer and exploration of potential mechanisms.xlsx by Zhi-Chuan He (21563657)

    Published 2025
    “…</p>Conclusion<p>CACNA1H, KCNJ11, and S100B are potential diagnostic and prognostic biomarkers in TNBC. …”
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  6. 1246
    Table 4_Identification of three T cell-related genes as diagnostic and prognostic biomarkers for triple-negative breast cancer and exploration of potential mechanisms.xlsx

    Table 4_Identification of three T cell-related genes as diagnostic and prognostic biomarkers for triple-negative breast cancer and exploration of potential mechanisms.xlsx by Zhi-Chuan He (21563657)

    Published 2025
    “…</p>Conclusion<p>CACNA1H, KCNJ11, and S100B are potential diagnostic and prognostic biomarkers in TNBC. …”
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  7. 1247
    Table 2_Identification of three T cell-related genes as diagnostic and prognostic biomarkers for triple-negative breast cancer and exploration of potential mechanisms.xlsx

    Table 2_Identification of three T cell-related genes as diagnostic and prognostic biomarkers for triple-negative breast cancer and exploration of potential mechanisms.xlsx by Zhi-Chuan He (21563657)

    Published 2025
    “…</p>Conclusion<p>CACNA1H, KCNJ11, and S100B are potential diagnostic and prognostic biomarkers in TNBC. …”
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  8. 1248
    Image 2_Identification of three T cell-related genes as diagnostic and prognostic biomarkers for triple-negative breast cancer and exploration of potential mechanisms.tif

    Image 2_Identification of three T cell-related genes as diagnostic and prognostic biomarkers for triple-negative breast cancer and exploration of potential mechanisms.tif by Zhi-Chuan He (21563657)

    Published 2025
    “…</p>Conclusion<p>CACNA1H, KCNJ11, and S100B are potential diagnostic and prognostic biomarkers in TNBC. …”
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  9. 1249
    Data Sheet 1_Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers.xlsx

    Data Sheet 1_Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers.xlsx by Wentong Li (492392)

    Published 2025
    “…PPI network analysis identified HSP90AA1, HSPA1B, and DNAJB1 as core hub genes (degree centrality >20). …”
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  10. 1250
    Data Sheet 5_Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers.csv

    Data Sheet 5_Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers.csv by Wentong Li (492392)

    Published 2025
    “…PPI network analysis identified HSP90AA1, HSPA1B, and DNAJB1 as core hub genes (degree centrality >20). …”
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  11. 1251
    Supplementary file 1_Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers.docx

    Supplementary file 1_Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers.docx by Wentong Li (492392)

    Published 2025
    “…PPI network analysis identified HSP90AA1, HSPA1B, and DNAJB1 as core hub genes (degree centrality >20). …”
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  12. 1252
    Data Sheet 2_Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers.xlsx

    Data Sheet 2_Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers.xlsx by Wentong Li (492392)

    Published 2025
    “…PPI network analysis identified HSP90AA1, HSPA1B, and DNAJB1 as core hub genes (degree centrality >20). …”
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  13. 1253
    Data Sheet 3_Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers.xlsx

    Data Sheet 3_Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers.xlsx by Wentong Li (492392)

    Published 2025
    “…PPI network analysis identified HSP90AA1, HSPA1B, and DNAJB1 as core hub genes (degree centrality >20). …”
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  14. 1254
    Data Sheet 4_Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers.xlsx

    Data Sheet 4_Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers.xlsx by Wentong Li (492392)

    Published 2025
    “…PPI network analysis identified HSP90AA1, HSPA1B, and DNAJB1 as core hub genes (degree centrality >20). …”
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  15. 1255
    Supplementary file 1_Identification of glycolysis-related clusters and immune cell infiltration in hepatic fibrosis progression using machine learning models and experimental validation.docx

    Supplementary file 1_Identification of glycolysis-related clusters and immune cell infiltration in hepatic fibrosis progression using machine learning models and experimental valid... by Guanglin Xiao (18113302)

    Published 2025
    “…Integrated weighted gene co-expression network analysis (WGCNA) with six machine learning algorithms to identify core GRGs genes associated with HF progression, and systematically characterized their biological functions and immunoregulatory roles through immune infiltration assessment, functional enrichment, consensus clustering, and single-cell differential state analysis. …”
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  16. 1256
    Bioinformatics-based screening and experimental validation of biomarkers for the treatment of connective tissue-associated interstitial lung disease with liquorice and dried ginger soup

    Bioinformatics-based screening and experimental validation of biomarkers for the treatment of connective tissue-associated interstitial lung disease with liquorice and dried ginger... by Hui Yuan (402180)

    Published 2025
    “…</p> <p>Five biomarkers (CXCL8, IL1A, IL1B, NFE2L2, and PTGS2) were identified. Functional analysis linked these pathways to innate immunity, cytokine activity, and pertussis pathways. …”
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  17. 1257
    Image 2_Leveraging the integration of bioinformatics and machine learning to uncover common biomarkers and molecular pathways underlying diabetes and nephrolithiasis.tif

    Image 2_Leveraging the integration of bioinformatics and machine learning to uncover common biomarkers and molecular pathways underlying diabetes and nephrolithiasis.tif by Xudong Shen (205653)

    Published 2025
    “…Among 101 machine learning models, S100A4, ARPC1B, and CEBPD were identified as the most significant interacting genes linking diabetes and kidney stones. …”
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  18. 1258
    Image 3_Leveraging the integration of bioinformatics and machine learning to uncover common biomarkers and molecular pathways underlying diabetes and nephrolithiasis.tif

    Image 3_Leveraging the integration of bioinformatics and machine learning to uncover common biomarkers and molecular pathways underlying diabetes and nephrolithiasis.tif by Xudong Shen (205653)

    Published 2025
    “…Among 101 machine learning models, S100A4, ARPC1B, and CEBPD were identified as the most significant interacting genes linking diabetes and kidney stones. …”
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  19. 1259
    Image 1_Leveraging the integration of bioinformatics and machine learning to uncover common biomarkers and molecular pathways underlying diabetes and nephrolithiasis.tif

    Image 1_Leveraging the integration of bioinformatics and machine learning to uncover common biomarkers and molecular pathways underlying diabetes and nephrolithiasis.tif by Xudong Shen (205653)

    Published 2025
    “…Among 101 machine learning models, S100A4, ARPC1B, and CEBPD were identified as the most significant interacting genes linking diabetes and kidney stones. …”
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  20. 1260
    Image 4_Leveraging the integration of bioinformatics and machine learning to uncover common biomarkers and molecular pathways underlying diabetes and nephrolithiasis.tif

    Image 4_Leveraging the integration of bioinformatics and machine learning to uncover common biomarkers and molecular pathways underlying diabetes and nephrolithiasis.tif by Xudong Shen (205653)

    Published 2025
    “…Among 101 machine learning models, S100A4, ARPC1B, and CEBPD were identified as the most significant interacting genes linking diabetes and kidney stones. …”
    Save to List
    Saved in:

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