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Showing 10,141 - 10,160 results of 10,350 for search '(((( algorithm etc function ) OR ( algorithm based function ))) OR ( algorithm python function ))', query time: 0.79s Refine Results
  1. 10141
    Image_3_Identification of CFH and FHL2 as biomarkers for idiopathic pulmonary fibrosis.TIF

    Image_3_Identification of CFH and FHL2 as biomarkers for idiopathic pulmonary fibrosis.TIF by Xingchen Liu (524190)

    Published 2024
    “…The differentially expressed genes (DEGs) were identified and subjected to functional enrichment analysis. By utilizing a combination of three machine learning algorithms, specific genes associated with idiopathic pulmonary fibrosis (IPF) were pinpointed. …”
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  2. 10142
    Image_4_Identification of CFH and FHL2 as biomarkers for idiopathic pulmonary fibrosis.TIF

    Image_4_Identification of CFH and FHL2 as biomarkers for idiopathic pulmonary fibrosis.TIF by Xingchen Liu (524190)

    Published 2024
    “…The differentially expressed genes (DEGs) were identified and subjected to functional enrichment analysis. By utilizing a combination of three machine learning algorithms, specific genes associated with idiopathic pulmonary fibrosis (IPF) were pinpointed. …”
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  3. 10143
    Table_1_Identification of CFH and FHL2 as biomarkers for idiopathic pulmonary fibrosis.XLSX

    Table_1_Identification of CFH and FHL2 as biomarkers for idiopathic pulmonary fibrosis.XLSX by Xingchen Liu (524190)

    Published 2024
    “…The differentially expressed genes (DEGs) were identified and subjected to functional enrichment analysis. By utilizing a combination of three machine learning algorithms, specific genes associated with idiopathic pulmonary fibrosis (IPF) were pinpointed. …”
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  4. 10144
    Image_11_Identification of CFH and FHL2 as biomarkers for idiopathic pulmonary fibrosis.TIF

    Image_11_Identification of CFH and FHL2 as biomarkers for idiopathic pulmonary fibrosis.TIF by Xingchen Liu (524190)

    Published 2024
    “…The differentially expressed genes (DEGs) were identified and subjected to functional enrichment analysis. By utilizing a combination of three machine learning algorithms, specific genes associated with idiopathic pulmonary fibrosis (IPF) were pinpointed. …”
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  5. 10145
    Image_13_Identification of CFH and FHL2 as biomarkers for idiopathic pulmonary fibrosis.TIF

    Image_13_Identification of CFH and FHL2 as biomarkers for idiopathic pulmonary fibrosis.TIF by Xingchen Liu (524190)

    Published 2024
    “…The differentially expressed genes (DEGs) were identified and subjected to functional enrichment analysis. By utilizing a combination of three machine learning algorithms, specific genes associated with idiopathic pulmonary fibrosis (IPF) were pinpointed. …”
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  6. 10146
    Image_2_Identification of CFH and FHL2 as biomarkers for idiopathic pulmonary fibrosis.TIF

    Image_2_Identification of CFH and FHL2 as biomarkers for idiopathic pulmonary fibrosis.TIF by Xingchen Liu (524190)

    Published 2024
    “…The differentially expressed genes (DEGs) were identified and subjected to functional enrichment analysis. By utilizing a combination of three machine learning algorithms, specific genes associated with idiopathic pulmonary fibrosis (IPF) were pinpointed. …”
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  7. 10147
    Image_7_Identification of CFH and FHL2 as biomarkers for idiopathic pulmonary fibrosis.TIF

    Image_7_Identification of CFH and FHL2 as biomarkers for idiopathic pulmonary fibrosis.TIF by Xingchen Liu (524190)

    Published 2024
    “…The differentially expressed genes (DEGs) were identified and subjected to functional enrichment analysis. By utilizing a combination of three machine learning algorithms, specific genes associated with idiopathic pulmonary fibrosis (IPF) were pinpointed. …”
    Save to List
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  8. 10148
    Image_8_Identification of CFH and FHL2 as biomarkers for idiopathic pulmonary fibrosis.TIF

    Image_8_Identification of CFH and FHL2 as biomarkers for idiopathic pulmonary fibrosis.TIF by Xingchen Liu (524190)

    Published 2024
    “…The differentially expressed genes (DEGs) were identified and subjected to functional enrichment analysis. By utilizing a combination of three machine learning algorithms, specific genes associated with idiopathic pulmonary fibrosis (IPF) were pinpointed. …”
    Save to List
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  9. 10149
    Image_12_Identification of CFH and FHL2 as biomarkers for idiopathic pulmonary fibrosis.TIF

    Image_12_Identification of CFH and FHL2 as biomarkers for idiopathic pulmonary fibrosis.TIF by Xingchen Liu (524190)

    Published 2024
    “…The differentially expressed genes (DEGs) were identified and subjected to functional enrichment analysis. By utilizing a combination of three machine learning algorithms, specific genes associated with idiopathic pulmonary fibrosis (IPF) were pinpointed. …”
    Save to List
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  10. 10150
    Image_14_Identification of CFH and FHL2 as biomarkers for idiopathic pulmonary fibrosis.TIF

    Image_14_Identification of CFH and FHL2 as biomarkers for idiopathic pulmonary fibrosis.TIF by Xingchen Liu (524190)

    Published 2024
    “…The differentially expressed genes (DEGs) were identified and subjected to functional enrichment analysis. By utilizing a combination of three machine learning algorithms, specific genes associated with idiopathic pulmonary fibrosis (IPF) were pinpointed. …”
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  11. 10151
    Image_15_Identification of CFH and FHL2 as biomarkers for idiopathic pulmonary fibrosis.TIF

    Image_15_Identification of CFH and FHL2 as biomarkers for idiopathic pulmonary fibrosis.TIF by Xingchen Liu (524190)

    Published 2024
    “…The differentially expressed genes (DEGs) were identified and subjected to functional enrichment analysis. By utilizing a combination of three machine learning algorithms, specific genes associated with idiopathic pulmonary fibrosis (IPF) were pinpointed. …”
    Save to List
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  12. 10152
    Image_10_Identification of CFH and FHL2 as biomarkers for idiopathic pulmonary fibrosis.TIF

    Image_10_Identification of CFH and FHL2 as biomarkers for idiopathic pulmonary fibrosis.TIF by Xingchen Liu (524190)

    Published 2024
    “…The differentially expressed genes (DEGs) were identified and subjected to functional enrichment analysis. By utilizing a combination of three machine learning algorithms, specific genes associated with idiopathic pulmonary fibrosis (IPF) were pinpointed. …”
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  13. 10153
    DataSheet_1_Identification of prognostic immune-related lncRNAs in pancreatic cancer.docx

    DataSheet_1_Identification of prognostic immune-related lncRNAs in pancreatic cancer.docx by Yan Ma (88810)

    Published 2022
    “…Several immune-related algorithms demonstrated that four IRlncRNAs were related to immune infiltration, immune checkpoints, and immune-related functions. …”
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  14. 10154
    DataSheet1_Significance of cuproptosis- related genes in the diagnosis and classification of psoriasis.PDF

    DataSheet1_Significance of cuproptosis- related genes in the diagnosis and classification of psoriasis.PDF by Qingyuan Lin (13166349)

    Published 2023
    “…The consensus clustering approach was used to classify psoriasis into clusters and the principal component analysis algorithms were constructed to calculate the cuproptosis score. …”
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  15. 10155
    DataSheet2_Significance of cuproptosis- related genes in the diagnosis and classification of psoriasis.PDF

    DataSheet2_Significance of cuproptosis- related genes in the diagnosis and classification of psoriasis.PDF by Qingyuan Lin (13166349)

    Published 2023
    “…The consensus clustering approach was used to classify psoriasis into clusters and the principal component analysis algorithms were constructed to calculate the cuproptosis score. …”
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  16. 10156
    DataSheet_1_Maturation and Phenotypic Heterogeneity of Human CD4+ Regulatory T Cells From Birth to Adulthood and After Allogeneic Stem Cell Transplantation.docx

    DataSheet_1_Maturation and Phenotypic Heterogeneity of Human CD4+ Regulatory T Cells From Birth to Adulthood and After Allogeneic Stem Cell Transplantation.docx by Tiago R. Matos (9997934)

    Published 2021
    “…This approach to characterize Treg heterogeneity based on expression of a large panel of functional markers may enable future studies to identify specific Treg defects that contribute to immune dysfunction.…”
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  17. 10157
    Supplementary information files for Three-dimension dithering and its effect on the interfacial strength of multi-material and emulated multi-material additive manufacturing processes

    Supplementary information files for Three-dimension dithering and its effect on the interfacial strength of multi-material and emulated multi-material additive manufacturing proces... by James Willmott (11163819)

    Published 2023
    “…This work focuses, initially, on the creation of different interfacial geometries within functionally graded tensile bars by extending two dimensional dithering algorithms from the realm of image processing into the third dimension. …”
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  18. 10158
    Image7_A curated census of pathogenic and likely pathogenic UTR variants and evaluation of deep learning models for variant effect prediction.TIFF

    Image7_A curated census of pathogenic and likely pathogenic UTR variants and evaluation of deep learning models for variant effect prediction.TIFF by Emma Bohn (16954161)

    Published 2023
    “…These datasets will support further development and validation of DL algorithms designed to predict the functional impact of variants that may be implicated in rare disease.…”
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  19. 10159
    Table1_A curated census of pathogenic and likely pathogenic UTR variants and evaluation of deep learning models for variant effect prediction.xlsx

    Table1_A curated census of pathogenic and likely pathogenic UTR variants and evaluation of deep learning models for variant effect prediction.xlsx by Emma Bohn (16954161)

    Published 2023
    “…These datasets will support further development and validation of DL algorithms designed to predict the functional impact of variants that may be implicated in rare disease.…”
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  20. 10160
    Table5_A curated census of pathogenic and likely pathogenic UTR variants and evaluation of deep learning models for variant effect prediction.xlsx

    Table5_A curated census of pathogenic and likely pathogenic UTR variants and evaluation of deep learning models for variant effect prediction.xlsx by Emma Bohn (16954161)

    Published 2023
    “…These datasets will support further development and validation of DL algorithms designed to predict the functional impact of variants that may be implicated in rare disease.…”
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