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Showing 41 - 60 results of 296 for search '(( gene based function optimization algorithm ) OR ( binary based sars optimization algorithm ))', query time: 0.69s Refine Results
  1. 41
    Table_1_Effect of Pyroptosis-Related Genes on the Prognosis of Breast Cancer.xlsx

    Table_1_Effect of Pyroptosis-Related Genes on the Prognosis of Breast Cancer.xlsx by Ying Zhou (25031)

    Published 2022
    “…</p>Methods<p>Herein, we analyzed the data of BRCA from both The Cancer Genome Atlas (TCGA) and GSEA MSigDB database. Based on the obtained pyroptosis-related genes (PRGs), we searched the interactions by STRING. …”
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  2. 42
    Image_1_Effect of Pyroptosis-Related Genes on the Prognosis of Breast Cancer.tif

    Image_1_Effect of Pyroptosis-Related Genes on the Prognosis of Breast Cancer.tif by Ying Zhou (25031)

    Published 2022
    “…</p>Methods<p>Herein, we analyzed the data of BRCA from both The Cancer Genome Atlas (TCGA) and GSEA MSigDB database. Based on the obtained pyroptosis-related genes (PRGs), we searched the interactions by STRING. …”
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  3. 43
    Table_2_Effect of Pyroptosis-Related Genes on the Prognosis of Breast Cancer.xlsx

    Table_2_Effect of Pyroptosis-Related Genes on the Prognosis of Breast Cancer.xlsx by Ying Zhou (25031)

    Published 2022
    “…</p>Methods<p>Herein, we analyzed the data of BRCA from both The Cancer Genome Atlas (TCGA) and GSEA MSigDB database. Based on the obtained pyroptosis-related genes (PRGs), we searched the interactions by STRING. …”
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  4. 44
    Table_4_Effect of Pyroptosis-Related Genes on the Prognosis of Breast Cancer.xlsx

    Table_4_Effect of Pyroptosis-Related Genes on the Prognosis of Breast Cancer.xlsx by Ying Zhou (25031)

    Published 2022
    “…</p>Methods<p>Herein, we analyzed the data of BRCA from both The Cancer Genome Atlas (TCGA) and GSEA MSigDB database. Based on the obtained pyroptosis-related genes (PRGs), we searched the interactions by STRING. …”
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  5. 45
    Table_5_Effect of Pyroptosis-Related Genes on the Prognosis of Breast Cancer.xlsx

    Table_5_Effect of Pyroptosis-Related Genes on the Prognosis of Breast Cancer.xlsx by Ying Zhou (25031)

    Published 2022
    “…</p>Methods<p>Herein, we analyzed the data of BRCA from both The Cancer Genome Atlas (TCGA) and GSEA MSigDB database. Based on the obtained pyroptosis-related genes (PRGs), we searched the interactions by STRING. …”
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  6. 46
    Table_3_Effect of Pyroptosis-Related Genes on the Prognosis of Breast Cancer.xlsx

    Table_3_Effect of Pyroptosis-Related Genes on the Prognosis of Breast Cancer.xlsx by Ying Zhou (25031)

    Published 2022
    “…</p>Methods<p>Herein, we analyzed the data of BRCA from both The Cancer Genome Atlas (TCGA) and GSEA MSigDB database. Based on the obtained pyroptosis-related genes (PRGs), we searched the interactions by STRING. …”
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  7. 47
    Illustration of PortalCG architecture in terms of its three stages of training.

    Illustration of PortalCG architecture in terms of its three stages of training. by Tian Cai (4227052)

    Published 2023
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  8. 48
    Table 1_Identification of a signature gene set for oxaliplatin sensitivity prediction in colorectal cancer.xlsx

    Table 1_Identification of a signature gene set for oxaliplatin sensitivity prediction in colorectal cancer.xlsx by Xiaopeng Zhan (4170574)

    Published 2025
    “…Machine learning algorithms to these datasets was applied to identify genes associated with oxaliplatin response. …”
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  9. 49
    Image 1_Identification of a signature gene set for oxaliplatin sensitivity prediction in colorectal cancer.pdf

    Image 1_Identification of a signature gene set for oxaliplatin sensitivity prediction in colorectal cancer.pdf by Xiaopeng Zhan (4170574)

    Published 2025
    “…Machine learning algorithms to these datasets was applied to identify genes associated with oxaliplatin response. …”
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  10. 50
    Table1_Identification of Immune-Related Genes for Risk Stratification in Multiple Myeloma Based on Whole Bone Marrow Gene Expression Profiling.XLSX

    Table1_Identification of Immune-Related Genes for Risk Stratification in Multiple Myeloma Based on Whole Bone Marrow Gene Expression Profiling.XLSX by Qiang-Sheng Wang (12641971)

    Published 2022
    “…Moreover, ssGSEA and GSEA algorithm reveled different immunological characteristics and biological function variation in different risk groups. …”
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  11. 51
    Image2_Identification of Immune-Related Genes for Risk Stratification in Multiple Myeloma Based on Whole Bone Marrow Gene Expression Profiling.TIFF

    Image2_Identification of Immune-Related Genes for Risk Stratification in Multiple Myeloma Based on Whole Bone Marrow Gene Expression Profiling.TIFF by Qiang-Sheng Wang (12641971)

    Published 2022
    “…Moreover, ssGSEA and GSEA algorithm reveled different immunological characteristics and biological function variation in different risk groups. …”
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  12. 52
    Image1_Identification of Immune-Related Genes for Risk Stratification in Multiple Myeloma Based on Whole Bone Marrow Gene Expression Profiling.TIFF

    Image1_Identification of Immune-Related Genes for Risk Stratification in Multiple Myeloma Based on Whole Bone Marrow Gene Expression Profiling.TIFF by Qiang-Sheng Wang (12641971)

    Published 2022
    “…Moreover, ssGSEA and GSEA algorithm reveled different immunological characteristics and biological function variation in different risk groups. …”
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  13. 53
    The brief description on the WTCCC dataset.

    The brief description on the WTCCC dataset. by Liyan Sun (760586)

    Published 2024
    “…Epi-SSA draws inspiration from the sparrow search algorithm and optimizes the population based on multiple objective functions in each iteration, in order to be able to more precisely identify epistatic interactions.…”
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  14. 54
    The penetrance tables for the 8 DNME models.

    The penetrance tables for the 8 DNME models. by Liyan Sun (760586)

    Published 2024
    “…Epi-SSA draws inspiration from the sparrow search algorithm and optimizes the population based on multiple objective functions in each iteration, in order to be able to more precisely identify epistatic interactions.…”
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  15. 55
    The penetrance tables for the 8 DME models.

    The penetrance tables for the 8 DME models. by Liyan Sun (760586)

    Published 2024
    “…Epi-SSA draws inspiration from the sparrow search algorithm and optimizes the population based on multiple objective functions in each iteration, in order to be able to more precisely identify epistatic interactions.…”
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  16. 56
    The penetrance tables for the 6 DNME3 models.

    The penetrance tables for the 6 DNME3 models. by Liyan Sun (760586)

    Published 2024
    “…Epi-SSA draws inspiration from the sparrow search algorithm and optimizes the population based on multiple objective functions in each iteration, in order to be able to more precisely identify epistatic interactions.…”
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  17. 57
    Data Sheet 4_Identification of a signature gene set for oxaliplatin sensitivity prediction in colorectal cancer.pdf

    Data Sheet 4_Identification of a signature gene set for oxaliplatin sensitivity prediction in colorectal cancer.pdf by Xiaopeng Zhan (4170574)

    Published 2025
    “…Machine learning algorithms to these datasets was applied to identify genes associated with oxaliplatin response. …”
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  18. 58
    Data Sheet 1_Identification of a signature gene set for oxaliplatin sensitivity prediction in colorectal cancer.pdf

    Data Sheet 1_Identification of a signature gene set for oxaliplatin sensitivity prediction in colorectal cancer.pdf by Xiaopeng Zhan (4170574)

    Published 2025
    “…Machine learning algorithms to these datasets was applied to identify genes associated with oxaliplatin response. …”
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  19. 59
    Data Sheet 2_Identification of a signature gene set for oxaliplatin sensitivity prediction in colorectal cancer.pdf

    Data Sheet 2_Identification of a signature gene set for oxaliplatin sensitivity prediction in colorectal cancer.pdf by Xiaopeng Zhan (4170574)

    Published 2025
    “…Machine learning algorithms to these datasets was applied to identify genes associated with oxaliplatin response. …”
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  20. 60
    Data Sheet 3_Identification of a signature gene set for oxaliplatin sensitivity prediction in colorectal cancer.pdf

    Data Sheet 3_Identification of a signature gene set for oxaliplatin sensitivity prediction in colorectal cancer.pdf by Xiaopeng Zhan (4170574)

    Published 2025
    “…Machine learning algorithms to these datasets was applied to identify genes associated with oxaliplatin response. …”
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