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simulation algorithm » segmentation algorithm (Expand Search), maximization algorithm (Expand Search), selection algorithm (Expand Search)
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Showing 1 - 20 results of 57 for search '(( binary pairs process simulation algorithm ) OR ( binary based work optimization algorithm ))*', query time: 0.52s Refine Results
  1. 1
    One advantage of our algorithm is that it is not binary in nature.

    One advantage of our algorithm is that it is not binary in nature. by Yong Kuk Kim (13955214)

    Published 2022
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  2. 2
    <i>hi</i>PRS algorithm process flow.

    <i>hi</i>PRS algorithm process flow. by Michela C. Massi (14599915)

    Published 2023
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  3. 3
    Hierarchical clustering to infer a binary tree with <i>K</i> = 4 sampled populations.

    Hierarchical clustering to infer a binary tree with <i>K</i> = 4 sampled populations. by Tristan Mary-Huard (3864)

    Published 2023
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  4. 4
    Related Work Summary.

    Related Work Summary. by Hend Bayoumi (22693738)

    Published 2025
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  5. 5
    The extended analyses of the observed ceRNA pairs that are related to miRNA hsa-let-17e-5p.

    The extended analyses of the observed ceRNA pairs that are related to miRNA hsa-let-17e-5p. by Yi-Wen Hsiao (13767916)

    Published 2022
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  6. 6
    Performance of our proposed method in four scenarios (I to IV) using naïve simulated data with the complete version.

    Performance of our proposed method in four scenarios (I to IV) using naïve simulated data with the complete version. by Yi-Wen Hsiao (13767916)

    Published 2022
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  7. 7
    Homomorphic binary tree.

    Homomorphic binary tree. by Jianhua He (341366)

    Published 2024
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  8. 8
    The performance of our proposed method in four scenarios (I to IV) uses simulated data that mimics real-world data distribution with the complete version.

    The performance of our proposed method in four scenarios (I to IV) uses simulated data that mimics real-world data distribution with the complete version. by Yi-Wen Hsiao (13767916)

    Published 2022
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  9. 9
    A graphic overview illustrates the random walk and permutation test in the <i>ceRNApairFiltering</i> method.

    A graphic overview illustrates the random walk and permutation test in the <i>ceRNApairFiltering</i> method. by Yi-Wen Hsiao (13767916)

    Published 2022
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  10. 10
    A graphic overview illustrates sorting and correlation calculation in the <i>ceRNApairFiltering</i> method.

    A graphic overview illustrates sorting and correlation calculation in the <i>ceRNApairFiltering</i> method. by Yi-Wen Hsiao (13767916)

    Published 2022
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  11. 11
    Run time comparisons between published tools and our package.

    Run time comparisons between published tools and our package. by Yi-Wen Hsiao (13767916)

    Published 2022
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  12. 12
    Performance of the ceRNAR package in five scenarios under the complete version using synthetic data with randomly selected correlation values from 0.3 to 0.9.

    Performance of the ceRNAR package in five scenarios under the complete version using synthetic data with randomly selected correlation values from 0.3 to 0.9. by Yi-Wen Hsiao (13767916)

    Published 2022
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  13. 13
    Performance comparisons between ceRNIA, JAMI, SPONGE, GDCRNATools and ceRNAR packages using synthetic data that mimic the real-world case.

    Performance comparisons between ceRNIA, JAMI, SPONGE, GDCRNATools and ceRNAR packages using synthetic data that mimic the real-world case. by Yi-Wen Hsiao (13767916)

    Published 2022
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  14. 14
    Performance of the ceRNAR package in five scenarios under the complete version using synthetic data with a fixed correlation value (0.9).

    Performance of the ceRNAR package in five scenarios under the complete version using synthetic data with a fixed correlation value (0.9). by Yi-Wen Hsiao (13767916)

    Published 2022
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  15. 15
    Performance of the ceRNAR package with different proportions of correlated samples in scenario III under the fast version using synthetic data with a fixed correlation value (0.9).

    Performance of the ceRNAR package with different proportions of correlated samples in scenario III under the fast version using synthetic data with a fixed correlation value (0.9). by Yi-Wen Hsiao (13767916)

    Published 2022
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  16. 16
    The meanings of score S are based on the values of P<sub>obey</sub> and P<sub>violate</sub>.

    The meanings of score S are based on the values of P<sub>obey</sub> and P<sub>violate</sub>. by Yi-Wen Hsiao (13767916)

    Published 2022
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  17. 17
    The graphical outputs of the <i>ceRNAModule</i>, <i>ceRNASurvial</i>, and <i>ceRNALocation</i> functions.

    The graphical outputs of the <i>ceRNAModule</i>, <i>ceRNASurvial</i>, and <i>ceRNALocation</i> functions. by Yi-Wen Hsiao (13767916)

    Published 2022
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  18. 18
    The graphical bubble outputs of the <i>ceRNAFunction</i> function are based on over-representation analysis (ORA).

    The graphical bubble outputs of the <i>ceRNAFunction</i> function are based on over-representation analysis (ORA). by Yi-Wen Hsiao (13767916)

    Published 2022
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  19. 19
    Main tabular output in CSV format.

    Main tabular output in CSV format. by Yi-Wen Hsiao (13767916)

    Published 2022
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  20. 20
    Performance of our proposed method in four scenarios (1 to 4).

    Performance of our proposed method in four scenarios (1 to 4). by Yi-Wen Hsiao (13767916)

    Published 2022
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