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Showing 61 - 80 results of 197 for search '(( genes based process optimization algorithm ) OR ( binary based cell optimization algorithm ))', query time: 0.73s Refine Results
  1. 61
    Optimal Time Intervals of Breech Births Dataset

    Optimal Time Intervals of Breech Births Dataset by Emma Spillane (11249121)

    Published 2021
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  2. 62
    Testing results for classifying AD, MCI and NC.

    Testing results for classifying AD, MCI and NC. by Nicodemus Songose Awarayi (18414494)

    Published 2024
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  3. 63
    Summary of existing CNN models.

    Summary of existing CNN models. by Nicodemus Songose Awarayi (18414494)

    Published 2024
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  4. 64
    Simultaneous Estimation of Many Sparse Networks via Hierarchical Poisson Log-Normal Model

    Simultaneous Estimation of Many Sparse Networks via Hierarchical Poisson Log-Normal Model by Changhao Ge (22410399)

    Published 2025
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  5. 65
    Table_1_An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization.pdf

    Table_1_An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization.pdf by Muhammad Awais (263096)

    Published 2024
    “…To optimize feature selection, a customized binary Grey Wolf Algorithm is utilized, achieving an impressive 80% reduction in feature size while preserving key discriminative information. …”
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  6. 66
    Summary of steps in iterative point set registration for scRNA-seq data.

    Summary of steps in iterative point set registration for scRNA-seq data. by Amir Alavi (9569337)

    Published 2020
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  7. 67
    Table_2_Identification of cortical interneuron cell markers in mouse embryos based on machine learning analysis of single-cell transcriptomics.XLSX

    Table_2_Identification of cortical interneuron cell markers in mouse embryos based on machine learning analysis of single-cell transcriptomics.XLSX by Zhandong Li (4284526)

    Published 2022
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  8. 68
    Table_1_Identification of cortical interneuron cell markers in mouse embryos based on machine learning analysis of single-cell transcriptomics.XLSX

    Table_1_Identification of cortical interneuron cell markers in mouse embryos based on machine learning analysis of single-cell transcriptomics.XLSX by Zhandong Li (4284526)

    Published 2022
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  9. 69
    Image1_mtPCDI: a machine learning-based prognostic model for prostate cancer recurrence.pdf

    Image1_mtPCDI: a machine learning-based prognostic model for prostate cancer recurrence.pdf by Guoliang Cheng (12458973)

    Published 2024
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  10. 70
    Table1_mtPCDI: a machine learning-based prognostic model for prostate cancer recurrence.xls

    Table1_mtPCDI: a machine learning-based prognostic model for prostate cancer recurrence.xls by Guoliang Cheng (12458973)

    Published 2024
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  11. 71
    Presentation1_A novel approach to analyze the association characteristics between post-spliced introns and their corresponding mRNA.zip

    Presentation1_A novel approach to analyze the association characteristics between post-spliced introns and their corresponding mRNA.zip by Suling Bo (11146299)

    Published 2023
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  12. 72
    DataSheet_1_A Novel Radiogenomics Biomarker Based on Hypoxic-Gene Subset: Accurate Survival and Prognostic Prediction of Renal Clear Cell Carcinoma.doc

    DataSheet_1_A Novel Radiogenomics Biomarker Based on Hypoxic-Gene Subset: Accurate Survival and Prognostic Prediction of Renal Clear Cell Carcinoma.doc by Jiahao Gao (7799222)

    Published 2021
    “…Purpose<p>To construct a novel radiogenomics biomarker based on hypoxic-gene subset for the accurate prognostic prediction of clear cell renal cell carcinoma (ccRCC).…”
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  13. 73
    Changed differential alternative splicing events (DASEs) patterns between PCOS and Normal granulosa cells.

    Changed differential alternative splicing events (DASEs) patterns between PCOS and Normal granulosa cells. by Linlin Yang (737661)

    Published 2024
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  14. 74
    BOFdat Step 3: Identifying species-specific metabolic end goals.

    BOFdat Step 3: Identifying species-specific metabolic end goals. by Jean-Christophe Lachance (6619307)

    Published 2019
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  15. 75
    Table2_MHIF-MSEA: a novel model of miRNA set enrichment analysis based on multi-source heterogeneous information fusion.XLSX

    Table2_MHIF-MSEA: a novel model of miRNA set enrichment analysis based on multi-source heterogeneous information fusion.XLSX by Jianwei Li (135213)

    Published 2024
    “…These networks were built based on miRNA-disease association, gene ontology (GO) annotation of target genes, and protein-protein interaction of target genes, respectively. …”
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  16. 76
    Table3_MHIF-MSEA: a novel model of miRNA set enrichment analysis based on multi-source heterogeneous information fusion.XLSX

    Table3_MHIF-MSEA: a novel model of miRNA set enrichment analysis based on multi-source heterogeneous information fusion.XLSX by Jianwei Li (135213)

    Published 2024
    “…These networks were built based on miRNA-disease association, gene ontology (GO) annotation of target genes, and protein-protein interaction of target genes, respectively. …”
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  17. 77
    Table1_MHIF-MSEA: a novel model of miRNA set enrichment analysis based on multi-source heterogeneous information fusion.XLSX

    Table1_MHIF-MSEA: a novel model of miRNA set enrichment analysis based on multi-source heterogeneous information fusion.XLSX by Jianwei Li (135213)

    Published 2024
    “…These networks were built based on miRNA-disease association, gene ontology (GO) annotation of target genes, and protein-protein interaction of target genes, respectively. …”
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  18. 78
    Table5_MHIF-MSEA: a novel model of miRNA set enrichment analysis based on multi-source heterogeneous information fusion.XLSX

    Table5_MHIF-MSEA: a novel model of miRNA set enrichment analysis based on multi-source heterogeneous information fusion.XLSX by Jianwei Li (135213)

    Published 2024
    “…These networks were built based on miRNA-disease association, gene ontology (GO) annotation of target genes, and protein-protein interaction of target genes, respectively. …”
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  19. 79
    Table6_MHIF-MSEA: a novel model of miRNA set enrichment analysis based on multi-source heterogeneous information fusion.XLSX

    Table6_MHIF-MSEA: a novel model of miRNA set enrichment analysis based on multi-source heterogeneous information fusion.XLSX by Jianwei Li (135213)

    Published 2024
    “…These networks were built based on miRNA-disease association, gene ontology (GO) annotation of target genes, and protein-protein interaction of target genes, respectively. …”
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  20. 80
    Table4_MHIF-MSEA: a novel model of miRNA set enrichment analysis based on multi-source heterogeneous information fusion.XLSX

    Table4_MHIF-MSEA: a novel model of miRNA set enrichment analysis based on multi-source heterogeneous information fusion.XLSX by Jianwei Li (135213)

    Published 2024
    “…These networks were built based on miRNA-disease association, gene ontology (GO) annotation of target genes, and protein-protein interaction of target genes, respectively. …”
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