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Showing 1 - 20 results of 136 for search '(( genes using robust optimization algorithm ) OR ( binary climate codon optimization algorithm ))', query time: 0.48s Refine Results
  1. 1
    Data_Sheet_1_CLGBO: An Algorithm for Constructing Highly Robust Coding Sets for DNA Storage.docx

    Data_Sheet_1_CLGBO: An Algorithm for Constructing Highly Robust Coding Sets for DNA Storage.docx by Yanfen Zheng (3814507)

    Published 2021
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  2. 2
    Optimal use of statistical methods to validate reference gene stability in longitudinal studies

    Optimal use of statistical methods to validate reference gene stability in longitudinal studies by Venkat Krishnan Sundaram (7026989)

    Published 2019
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  3. 3
    Three machine learning algorithms were further employed to select candidate key hub genes.

    Three machine learning algorithms were further employed to select candidate key hub genes. by Zhifeng Wu (303016)

    Published 2025
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  4. 4
    Number of highest variance genes selected per omic for each dataset-approach combination.

    Number of highest variance genes selected per omic for each dataset-approach combination. by Teemu J. Rintala (19333003)

    Published 2024
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  5. 5
    Indels characterization algorithm development and benchmark with simulated data and real data.

    Indels characterization algorithm development and benchmark with simulated data and real data. by Marta Sanvicente-García (12306659)

    Published 2023
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  6. 6
    Runtime (s) of 12 algorithms across six datasets.

    Runtime (s) of 12 algorithms across six datasets. by Siyi Huang (8562174)

    Published 2025
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  7. 7
    DE-DSRGs were identified as diagnostic genes for AMI.

    DE-DSRGs were identified as diagnostic genes for AMI. by Nan Huang (464390)

    Published 2024
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  8. 8
    Table1_Development and evaluation of a chronic kidney disease risk prediction model using random forest.xlsx

    Table1_Development and evaluation of a chronic kidney disease risk prediction model using random forest.xlsx by Krish Mendapara (18890758)

    Published 2024
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  9. 9
    Image2_Development and evaluation of a chronic kidney disease risk prediction model using random forest.png

    Image2_Development and evaluation of a chronic kidney disease risk prediction model using random forest.png by Krish Mendapara (18890758)

    Published 2024
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  10. 10
    Image3_Development and evaluation of a chronic kidney disease risk prediction model using random forest.png

    Image3_Development and evaluation of a chronic kidney disease risk prediction model using random forest.png by Krish Mendapara (18890758)

    Published 2024
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  11. 11
    Image1_Development and evaluation of a chronic kidney disease risk prediction model using random forest.png

    Image1_Development and evaluation of a chronic kidney disease risk prediction model using random forest.png by Krish Mendapara (18890758)

    Published 2024
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  12. 12
    Stability of cancer clustering results with different pathway sets.

    Stability of cancer clustering results with different pathway sets. by Teemu J. Rintala (19333003)

    Published 2024
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  13. 13
    Stability of cancer clustering results with different feature filters.

    Stability of cancer clustering results with different feature filters. by Teemu J. Rintala (19333003)

    Published 2024
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  14. 14
    Cluster survival results with different pathway sets.

    Cluster survival results with different pathway sets. by Teemu J. Rintala (19333003)

    Published 2024
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  15. 15
    Cancer subtype agreement with different pathway sets.

    Cancer subtype agreement with different pathway sets. by Teemu J. Rintala (19333003)

    Published 2024
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  16. 16
    Data Sheet 1_Clinical potential and experimental validation of prognostic genes in hepatocellular carcinoma revealed by risk modeling utilizing single cell and transcriptome constructs.zip

    Data Sheet 1_Clinical potential and experimental validation of prognostic genes in hepatocellular carcinoma revealed by risk modeling utilizing single cell and transcriptome constr... by Hang Deng (1664668)

    Published 2025
    “…Subsequently, univariate Cox regression analysis and PH assumption test were performed, and a risk model was developed using an optimal algorithm from 101 combinations on the TCGA-LIHC dataset to pinpoint prognostic genes. …”
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  17. 17
    Table2_Identification of Pan-Cancer Biomarkers Based on the Gene Expression Profiles of Cancer Cell Lines.XLSX

    Table2_Identification of Pan-Cancer Biomarkers Based on the Gene Expression Profiles of Cancer Cell Lines.XLSX by ShiJian Ding (11764646)

    Published 2021
    “…Researchers want to get robust gene expression signature from pan-cancer patients. …”
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  18. 18
    Table1_Identification of Pan-Cancer Biomarkers Based on the Gene Expression Profiles of Cancer Cell Lines.XLSX

    Table1_Identification of Pan-Cancer Biomarkers Based on the Gene Expression Profiles of Cancer Cell Lines.XLSX by ShiJian Ding (11764646)

    Published 2021
    “…Researchers want to get robust gene expression signature from pan-cancer patients. …”
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  19. 19
    Table3_Identification of Pan-Cancer Biomarkers Based on the Gene Expression Profiles of Cancer Cell Lines.XLSX

    Table3_Identification of Pan-Cancer Biomarkers Based on the Gene Expression Profiles of Cancer Cell Lines.XLSX by ShiJian Ding (11764646)

    Published 2021
    “…Researchers want to get robust gene expression signature from pan-cancer patients. …”
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  20. 20
    Table4_Identification of Pan-Cancer Biomarkers Based on the Gene Expression Profiles of Cancer Cell Lines.XLSX

    Table4_Identification of Pan-Cancer Biomarkers Based on the Gene Expression Profiles of Cancer Cell Lines.XLSX by ShiJian Ding (11764646)

    Published 2021
    “…Researchers want to get robust gene expression signature from pan-cancer patients. …”
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