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Showing 101 - 120 results of 13,066 for search '(((( algorithm gene function ) OR ( algorithm based functions ))) OR ( algorithm python function ))', query time: 0.76s Refine Results
  1. 101
    Table_2_FI-Net: Identification of Cancer Driver Genes by Using Functional Impact Prediction Neural Network.XLSX

    Table_2_FI-Net: Identification of Cancer Driver Genes by Using Functional Impact Prediction Neural Network.XLSX by Hong Gu (68558)

    Published 2021
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  2. 102
    Table_2_FI-Net: Identification of Cancer Driver Genes by Using Functional Impact Prediction Neural Network.XLSX

    Table_2_FI-Net: Identification of Cancer Driver Genes by Using Functional Impact Prediction Neural Network.XLSX by Hong Gu (68558)

    Published 2020
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  3. 103
    Table_1_FI-Net: Identification of Cancer Driver Genes by Using Functional Impact Prediction Neural Network.XLSX

    Table_1_FI-Net: Identification of Cancer Driver Genes by Using Functional Impact Prediction Neural Network.XLSX by Hong Gu (68558)

    Published 2021
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  4. 104
    Table_3_FI-Net: Identification of Cancer Driver Genes by Using Functional Impact Prediction Neural Network.XLSX

    Table_3_FI-Net: Identification of Cancer Driver Genes by Using Functional Impact Prediction Neural Network.XLSX by Hong Gu (68558)

    Published 2021
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  5. 105
    Table_1_FI-Net: Identification of Cancer Driver Genes by Using Functional Impact Prediction Neural Network.XLSX

    Table_1_FI-Net: Identification of Cancer Driver Genes by Using Functional Impact Prediction Neural Network.XLSX by Hong Gu (68558)

    Published 2020
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  6. 106
    Table_4_FI-Net: Identification of Cancer Driver Genes by Using Functional Impact Prediction Neural Network.XLSX

    Table_4_FI-Net: Identification of Cancer Driver Genes by Using Functional Impact Prediction Neural Network.XLSX by Hong Gu (68558)

    Published 2021
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  7. 107
    Table_4_FI-Net: Identification of Cancer Driver Genes by Using Functional Impact Prediction Neural Network.XLSX

    Table_4_FI-Net: Identification of Cancer Driver Genes by Using Functional Impact Prediction Neural Network.XLSX by Hong Gu (68558)

    Published 2020
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  8. 108
    4 genes were identified as hub genes for PD.

    4 genes were identified as hub genes for PD. by Guanghao Xin (17583227)

    Published 2023
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  9. 109
    UPEFinder: A Bioinformatic Tool for the Study of Uncharacterized Proteins Based on Gene Expression Correlation and the PageRank Algorithm

    UPEFinder: A Bioinformatic Tool for the Study of Uncharacterized Proteins Based on Gene Expression Correlation and the PageRank Algorithm by José González-Gomariz (9610967)

    Published 2020
    “…In this way, we applied the PageRank algorithm to this network to identify the most relevant nodes, which were the biological annotations of the uncharacterized proteins. …”
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  10. 110
    UPEFinder: A Bioinformatic Tool for the Study of Uncharacterized Proteins Based on Gene Expression Correlation and the PageRank Algorithm

    UPEFinder: A Bioinformatic Tool for the Study of Uncharacterized Proteins Based on Gene Expression Correlation and the PageRank Algorithm by José González-Gomariz (9610967)

    Published 2020
    “…In this way, we applied the PageRank algorithm to this network to identify the most relevant nodes, which were the biological annotations of the uncharacterized proteins. …”
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  11. 111
    UPEFinder: A Bioinformatic Tool for the Study of Uncharacterized Proteins Based on Gene Expression Correlation and the PageRank Algorithm

    UPEFinder: A Bioinformatic Tool for the Study of Uncharacterized Proteins Based on Gene Expression Correlation and the PageRank Algorithm by José González-Gomariz (9610967)

    Published 2020
    “…In this way, we applied the PageRank algorithm to this network to identify the most relevant nodes, which were the biological annotations of the uncharacterized proteins. …”
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  12. 112
    UPEFinder: A Bioinformatic Tool for the Study of Uncharacterized Proteins Based on Gene Expression Correlation and the PageRank Algorithm

    UPEFinder: A Bioinformatic Tool for the Study of Uncharacterized Proteins Based on Gene Expression Correlation and the PageRank Algorithm by José González-Gomariz (9610967)

    Published 2020
    “…In this way, we applied the PageRank algorithm to this network to identify the most relevant nodes, which were the biological annotations of the uncharacterized proteins. …”
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  13. 113
    KEGG analysis bubble plot for other four module.

    KEGG analysis bubble plot for other four module. by Zongjin Li (38031)

    Published 2025
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  14. 114
    Visualization for the module 1.

    Visualization for the module 1. by Zongjin Li (38031)

    Published 2025
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  15. 115
    Clustering performance comparison.

    Clustering performance comparison. by Zongjin Li (38031)

    Published 2025
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  16. 116
    Heat map analysis of the biomarkers.

    Heat map analysis of the biomarkers. by Zongjin Li (38031)

    Published 2025
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  17. 117
    Comparison with published methods.

    Comparison with published methods. by Zongjin Li (38031)

    Published 2025
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  18. 118
    GO analysis bubble plot for module 1.

    GO analysis bubble plot for module 1. by Zongjin Li (38031)

    Published 2025
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  19. 119
    Pathway analysis bubble plot for module 1.

    Pathway analysis bubble plot for module 1. by Zongjin Li (38031)

    Published 2025
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  20. 120
    The most significant GO terms and p-values for each of the five modules.

    The most significant GO terms and p-values for each of the five modules. by Zongjin Li (38031)

    Published 2025
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