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Showing 701 - 720 results of 760 for search '(((( algorithm pre function ) OR ( algorithm fc function ))) OR ( algorithm python function ))', query time: 0.31s Refine Results
  1. 701
    Image 4_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.tif

    Image 4_Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning.tif by Bin He (75597)

    Published 2025
    “…Ion channel-related genes were extracted from microarray datasets and analyzed for differential expression and functional relevance to AF pathology. Machine learning algorithms (LASSO and SVM) were used to identify signature genes from ion channels in AF, followed by drug-enrichment analysis to explore potential therapeutic options.…”
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  2. 702
    Image_1_Balancing Current and Future Reproductive Investment: Variation in Resource Selection During Stages of Reproduction in a Long-Lived Herbivore.TIFF

    Image_1_Balancing Current and Future Reproductive Investment: Variation in Resource Selection During Stages of Reproduction in a Long-Lived Herbivore.TIFF by Levi J. Heffelfinger (8988731)

    Published 2020
    “…We used radio-collar and randomly generated locations to model resource selection in a hierarchical approach utilizing machine learning algorithms and traditional resource selection functions (RSFs). …”
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  3. 703
    Image_1_Balancing Current and Future Reproductive Investment: Variation in Resource Selection During Stages of Reproduction in a Long-Lived Herbivore.TIFF

    Image_1_Balancing Current and Future Reproductive Investment: Variation in Resource Selection During Stages of Reproduction in a Long-Lived Herbivore.TIFF by Levi J. Heffelfinger (8988731)

    Published 2020
    “…We used radio-collar and randomly generated locations to model resource selection in a hierarchical approach utilizing machine learning algorithms and traditional resource selection functions (RSFs). …”
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  4. 704
    Image_2_Balancing Current and Future Reproductive Investment: Variation in Resource Selection During Stages of Reproduction in a Long-Lived Herbivore.TIFF

    Image_2_Balancing Current and Future Reproductive Investment: Variation in Resource Selection During Stages of Reproduction in a Long-Lived Herbivore.TIFF by Levi J. Heffelfinger (8988731)

    Published 2020
    “…We used radio-collar and randomly generated locations to model resource selection in a hierarchical approach utilizing machine learning algorithms and traditional resource selection functions (RSFs). …”
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  5. 705
    Image_2_Balancing Current and Future Reproductive Investment: Variation in Resource Selection During Stages of Reproduction in a Long-Lived Herbivore.TIFF

    Image_2_Balancing Current and Future Reproductive Investment: Variation in Resource Selection During Stages of Reproduction in a Long-Lived Herbivore.TIFF by Levi J. Heffelfinger (8988731)

    Published 2020
    “…We used radio-collar and randomly generated locations to model resource selection in a hierarchical approach utilizing machine learning algorithms and traditional resource selection functions (RSFs). …”
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  6. 706
    DataSheet1_Identification of cuproptosis-related biomarkers and analysis of immune infiltration in allograft lung ischemia-reperfusion injury.docx

    DataSheet1_Identification of cuproptosis-related biomarkers and analysis of immune infiltration in allograft lung ischemia-reperfusion injury.docx by Jianying Qin (12042813)

    Published 2023
    “…We identified differentially expressed CRGs (DE-CRGs) and performed functional analyses. Biomarker genes were selected using three machine learning algorithms. …”
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  7. 707
    Table_1_A Co-Association Network Analysis Reveals Putative Regulators for Health-Related Traits in Pigs.xlsx

    Table_1_A Co-Association Network Analysis Reveals Putative Regulators for Health-Related Traits in Pigs.xlsx by Daniel Crespo-Piazuelo (4003058)

    Published 2021
    “…The five regulators were involved in pathways related to immunity such as lymphocyte differentiation and activation, platelet activation and degranulation, megakaryocyte differentiation, FcγR-mediated phagocytosis and response to nitric oxide, among others, but also in immunometabolism. …”
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  8. 708
    Table_4_A Co-Association Network Analysis Reveals Putative Regulators for Health-Related Traits in Pigs.xlsx

    Table_4_A Co-Association Network Analysis Reveals Putative Regulators for Health-Related Traits in Pigs.xlsx by Daniel Crespo-Piazuelo (4003058)

    Published 2021
    “…The five regulators were involved in pathways related to immunity such as lymphocyte differentiation and activation, platelet activation and degranulation, megakaryocyte differentiation, FcγR-mediated phagocytosis and response to nitric oxide, among others, but also in immunometabolism. …”
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  9. 709
    DataSheet_1_A Co-Association Network Analysis Reveals Putative Regulators for Health-Related Traits in Pigs.docx

    DataSheet_1_A Co-Association Network Analysis Reveals Putative Regulators for Health-Related Traits in Pigs.docx by Daniel Crespo-Piazuelo (4003058)

    Published 2021
    “…The five regulators were involved in pathways related to immunity such as lymphocyte differentiation and activation, platelet activation and degranulation, megakaryocyte differentiation, FcγR-mediated phagocytosis and response to nitric oxide, among others, but also in immunometabolism. …”
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  10. 710
    Table_5_A Co-Association Network Analysis Reveals Putative Regulators for Health-Related Traits in Pigs.xlsx

    Table_5_A Co-Association Network Analysis Reveals Putative Regulators for Health-Related Traits in Pigs.xlsx by Daniel Crespo-Piazuelo (4003058)

    Published 2021
    “…The five regulators were involved in pathways related to immunity such as lymphocyte differentiation and activation, platelet activation and degranulation, megakaryocyte differentiation, FcγR-mediated phagocytosis and response to nitric oxide, among others, but also in immunometabolism. …”
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  11. 711
    Table_7_A Co-Association Network Analysis Reveals Putative Regulators for Health-Related Traits in Pigs.xlsx

    Table_7_A Co-Association Network Analysis Reveals Putative Regulators for Health-Related Traits in Pigs.xlsx by Daniel Crespo-Piazuelo (4003058)

    Published 2021
    “…The five regulators were involved in pathways related to immunity such as lymphocyte differentiation and activation, platelet activation and degranulation, megakaryocyte differentiation, FcγR-mediated phagocytosis and response to nitric oxide, among others, but also in immunometabolism. …”
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  12. 712
    Table_3_A Co-Association Network Analysis Reveals Putative Regulators for Health-Related Traits in Pigs.xlsx

    Table_3_A Co-Association Network Analysis Reveals Putative Regulators for Health-Related Traits in Pigs.xlsx by Daniel Crespo-Piazuelo (4003058)

    Published 2021
    “…The five regulators were involved in pathways related to immunity such as lymphocyte differentiation and activation, platelet activation and degranulation, megakaryocyte differentiation, FcγR-mediated phagocytosis and response to nitric oxide, among others, but also in immunometabolism. …”
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  13. 713
    Table_2_A Co-Association Network Analysis Reveals Putative Regulators for Health-Related Traits in Pigs.xlsx

    Table_2_A Co-Association Network Analysis Reveals Putative Regulators for Health-Related Traits in Pigs.xlsx by Daniel Crespo-Piazuelo (4003058)

    Published 2021
    “…The five regulators were involved in pathways related to immunity such as lymphocyte differentiation and activation, platelet activation and degranulation, megakaryocyte differentiation, FcγR-mediated phagocytosis and response to nitric oxide, among others, but also in immunometabolism. …”
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  14. 714
    Data Sheet 1_Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers.xlsx

    Data Sheet 1_Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers.xlsx by Wentong Li (492392)

    Published 2025
    “…Differentially expressed genes (DEGs) were identified using the limma package (log2FC>0.656, p<0.05). Protein-protein interaction (PPI) networks were constructed using the STRING database. …”
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  15. 715
    Data Sheet 5_Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers.csv

    Data Sheet 5_Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers.csv by Wentong Li (492392)

    Published 2025
    “…Differentially expressed genes (DEGs) were identified using the limma package (log2FC>0.656, p<0.05). Protein-protein interaction (PPI) networks were constructed using the STRING database. …”
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  16. 716
    Supplementary file 1_Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers.docx

    Supplementary file 1_Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers.docx by Wentong Li (492392)

    Published 2025
    “…Differentially expressed genes (DEGs) were identified using the limma package (log2FC>0.656, p<0.05). Protein-protein interaction (PPI) networks were constructed using the STRING database. …”
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  17. 717
    Data Sheet 2_Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers.xlsx

    Data Sheet 2_Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers.xlsx by Wentong Li (492392)

    Published 2025
    “…Differentially expressed genes (DEGs) were identified using the limma package (log2FC>0.656, p<0.05). Protein-protein interaction (PPI) networks were constructed using the STRING database. …”
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  18. 718
    Data Sheet 3_Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers.xlsx

    Data Sheet 3_Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers.xlsx by Wentong Li (492392)

    Published 2025
    “…Differentially expressed genes (DEGs) were identified using the limma package (log2FC>0.656, p<0.05). Protein-protein interaction (PPI) networks were constructed using the STRING database. …”
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  19. 719
    Data Sheet 4_Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers.xlsx

    Data Sheet 4_Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers.xlsx by Wentong Li (492392)

    Published 2025
    “…Differentially expressed genes (DEGs) were identified using the limma package (log2FC>0.656, p<0.05). Protein-protein interaction (PPI) networks were constructed using the STRING database. …”
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  20. 720
    Multiscale software for quantum simulations of nanostructured materials and devices

    Multiscale software for quantum simulations of nanostructured materials and devices by Wenchang Lu (8385402)

    Published 2020
    “…<div>The development of robust, adaptive software and algorithms that can fully exploit exascale</div><div>capabilities and future computing architectures is critical to designing advanced materials and</div><div>devices with targeted properties. …”
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