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Showing 1 - 20 results of 172 for search '(( binary step process optimization algorithm ) OR ( degs based cell optimization algorithm ))', query time: 0.58s Refine Results
  1. 1
    Results of Holm’s step-down procedure.

    Results of Holm’s step-down procedure. by Nebojsa Bacanin (13932723)

    Published 2022
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  2. 2
    Homomorphic binary tree.

    Homomorphic binary tree. by Jianhua He (341366)

    Published 2024
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  3. 3
    Validation of image processing steps and metric results using images of a microfluidic device.

    Validation of image processing steps and metric results using images of a microfluidic device. by Gavrielle R. Untracht (11820311)

    Published 2021
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  4. 4
    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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  5. 5
    Application of ABC SMC to the fitting of the binary flip with cusp model.

    Application of ABC SMC to the fitting of the binary flip with cusp model. by Elena Camacho-Aguilar (10906327)

    Published 2021
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  6. 6
    Table3_Comprehensive analysis of the progression mechanisms of CRPC and its inhibitor discovery based on machine learning algorithms.XLSX

    Table3_Comprehensive analysis of the progression mechanisms of CRPC and its inhibitor discovery based on machine learning algorithms.XLSX by Zhen Wang (72451)

    Published 2023
    “…The biological functional enrichment analysis indicated that DEGs were mainly enriched in pathways related to the cell cycle and metabolism. …”
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  7. 7
    Table2_Comprehensive analysis of the progression mechanisms of CRPC and its inhibitor discovery based on machine learning algorithms.XLSX

    Table2_Comprehensive analysis of the progression mechanisms of CRPC and its inhibitor discovery based on machine learning algorithms.XLSX by Zhen Wang (72451)

    Published 2023
    “…The biological functional enrichment analysis indicated that DEGs were mainly enriched in pathways related to the cell cycle and metabolism. …”
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  8. 8
    Table1_Comprehensive analysis of the progression mechanisms of CRPC and its inhibitor discovery based on machine learning algorithms.XLSX

    Table1_Comprehensive analysis of the progression mechanisms of CRPC and its inhibitor discovery based on machine learning algorithms.XLSX by Zhen Wang (72451)

    Published 2023
    “…The biological functional enrichment analysis indicated that DEGs were mainly enriched in pathways related to the cell cycle and metabolism. …”
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  9. 9
    DataSheet1_Comprehensive analysis of immune-related gene signature based on ssGSEA algorithms in the prognosis and immune landscape of hepatocellular carcinoma.ZIP

    DataSheet1_Comprehensive analysis of immune-related gene signature based on ssGSEA algorithms in the prognosis and immune landscape of hepatocellular carcinoma.ZIP by Liangliang Wang (580395)

    Published 2022
    “…We assessed the immune cell infiltration in each HCC specimen using single sample gene set enrichment analysis (ssGSEA) and classified all patients with HCC into high- and low-immune clusters using a hierarchical clustering algorithm. …”
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  10. 10
    Flowchart of software workflow.

    Flowchart of software workflow. by Gavrielle R. Untracht (11820311)

    Published 2021
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  11. 11
    Unsupervised clustering and marker gene signatures.

    Unsupervised clustering and marker gene signatures. by Josh L. Espinoza (10492448)

    Published 2021
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  12. 12
    GSE96058 information.

    GSE96058 information. by Sepideh Zununi Vahed (9861298)

    Published 2024
    “…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …”
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  13. 13
    The performance of classifiers.

    The performance of classifiers. by Sepideh Zununi Vahed (9861298)

    Published 2024
    “…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …”
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  14. 14
    Image_6_Immunological Value of Prognostic Signature Based on Cancer Stem Cell Characteristics in Hepatocellular Carcinoma.TIF

    Image_6_Immunological Value of Prognostic Signature Based on Cancer Stem Cell Characteristics in Hepatocellular Carcinoma.TIF by Qianhui Xu (10517717)

    Published 2021
    “…Estimation of Stromal and Immune Cells in Malignant Tumors using Expression Data and single-sample gene-set enrichment analysis algorithm were performed to characterize the context of tumor immune microenvironment (TIME). …”
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  15. 15
    Image_2_Immunological Value of Prognostic Signature Based on Cancer Stem Cell Characteristics in Hepatocellular Carcinoma.TIF

    Image_2_Immunological Value of Prognostic Signature Based on Cancer Stem Cell Characteristics in Hepatocellular Carcinoma.TIF by Qianhui Xu (10517717)

    Published 2021
    “…Estimation of Stromal and Immune Cells in Malignant Tumors using Expression Data and single-sample gene-set enrichment analysis algorithm were performed to characterize the context of tumor immune microenvironment (TIME). …”
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  16. 16
    Image_1_Immunological Value of Prognostic Signature Based on Cancer Stem Cell Characteristics in Hepatocellular Carcinoma.TIF

    Image_1_Immunological Value of Prognostic Signature Based on Cancer Stem Cell Characteristics in Hepatocellular Carcinoma.TIF by Qianhui Xu (10517717)

    Published 2021
    “…Estimation of Stromal and Immune Cells in Malignant Tumors using Expression Data and single-sample gene-set enrichment analysis algorithm were performed to characterize the context of tumor immune microenvironment (TIME). …”
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  17. 17
    Image_9_Immunological Value of Prognostic Signature Based on Cancer Stem Cell Characteristics in Hepatocellular Carcinoma.TIF

    Image_9_Immunological Value of Prognostic Signature Based on Cancer Stem Cell Characteristics in Hepatocellular Carcinoma.TIF by Qianhui Xu (10517717)

    Published 2021
    “…Estimation of Stromal and Immune Cells in Malignant Tumors using Expression Data and single-sample gene-set enrichment analysis algorithm were performed to characterize the context of tumor immune microenvironment (TIME). …”
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  18. 18
    Image_4_Immunological Value of Prognostic Signature Based on Cancer Stem Cell Characteristics in Hepatocellular Carcinoma.TIF

    Image_4_Immunological Value of Prognostic Signature Based on Cancer Stem Cell Characteristics in Hepatocellular Carcinoma.TIF by Qianhui Xu (10517717)

    Published 2021
    “…Estimation of Stromal and Immune Cells in Malignant Tumors using Expression Data and single-sample gene-set enrichment analysis algorithm were performed to characterize the context of tumor immune microenvironment (TIME). …”
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  19. 19
    Image_7_Immunological Value of Prognostic Signature Based on Cancer Stem Cell Characteristics in Hepatocellular Carcinoma.TIF

    Image_7_Immunological Value of Prognostic Signature Based on Cancer Stem Cell Characteristics in Hepatocellular Carcinoma.TIF by Qianhui Xu (10517717)

    Published 2021
    “…Estimation of Stromal and Immune Cells in Malignant Tumors using Expression Data and single-sample gene-set enrichment analysis algorithm were performed to characterize the context of tumor immune microenvironment (TIME). …”
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  20. 20
    Image_5_Immunological Value of Prognostic Signature Based on Cancer Stem Cell Characteristics in Hepatocellular Carcinoma.TIF

    Image_5_Immunological Value of Prognostic Signature Based on Cancer Stem Cell Characteristics in Hepatocellular Carcinoma.TIF by Qianhui Xu (10517717)

    Published 2021
    “…Estimation of Stromal and Immune Cells in Malignant Tumors using Expression Data and single-sample gene-set enrichment analysis algorithm were performed to characterize the context of tumor immune microenvironment (TIME). …”
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