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Showing 5,441 - 5,459 results of 5,459 for search '(( algorithm brain function ) OR ((( algorithm python function ) OR ( algorithm b function ))))', query time: 0.54s Refine Results
  1. 5441
    Image5_Pan-cancer analysis of CREB3L1 as biomarker in the prediction of prognosis and immunotherapeutic efficacy.PDF

    Image5_Pan-cancer analysis of CREB3L1 as biomarker in the prediction of prognosis and immunotherapeutic efficacy.PDF by Zhengjun Lin (11050797)

    Published 2022
    “…Furthermore, Gene Set Enrichment Analysis (GSEA) was conducted to explore the potential biological functions and downstream pathways of CREB3L1 in different human cancers. …”
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  2. 5442
    DataSheet1_Pan-cancer analysis of CREB3L1 as biomarker in the prediction of prognosis and immunotherapeutic efficacy.docx

    DataSheet1_Pan-cancer analysis of CREB3L1 as biomarker in the prediction of prognosis and immunotherapeutic efficacy.docx by Zhengjun Lin (11050797)

    Published 2022
    “…Furthermore, Gene Set Enrichment Analysis (GSEA) was conducted to explore the potential biological functions and downstream pathways of CREB3L1 in different human cancers. …”
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  3. 5443
    Image_2_Identification of the immune-associated characteristics and predictive biomarkers of keratoconus based on single-cell RNA-sequencing and bulk RNA-sequencing.tif

    Image_2_Identification of the immune-associated characteristics and predictive biomarkers of keratoconus based on single-cell RNA-sequencing and bulk RNA-sequencing.tif by Xiaoguang Niu (17293525)

    Published 2023
    “…Three bulk RNA-seq datasets were merged and used to identify the differentially expressed genes (DEGs), biological functions, and immune characteristics. Weighted gene coexpression network analysis (WGCNA) was used to select the IAG score-related hub genes. …”
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  4. 5444
    DataSheet_7_Identification of the immune-associated characteristics and predictive biomarkers of keratoconus based on single-cell RNA-sequencing and bulk RNA-sequencing.csv

    DataSheet_7_Identification of the immune-associated characteristics and predictive biomarkers of keratoconus based on single-cell RNA-sequencing and bulk RNA-sequencing.csv by Xiaoguang Niu (17293525)

    Published 2023
    “…Three bulk RNA-seq datasets were merged and used to identify the differentially expressed genes (DEGs), biological functions, and immune characteristics. Weighted gene coexpression network analysis (WGCNA) was used to select the IAG score-related hub genes. …”
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  5. 5445
    Image 1_Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in precision medicine.tif

    Image 1_Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in prec... by Yutong Fang (16621143)

    Published 2025
    “…We constructed ML-based diagnostic models using 12 algorithms and evaluated their performance for identifying the optimal ML diagnostic model. …”
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  6. 5446
    Image1_Role of ARRB1 in prognosis and immunotherapy: A Pan-Cancer analysis.jpeg

    Image1_Role of ARRB1 in prognosis and immunotherapy: A Pan-Cancer analysis.jpeg by Yingquan Ye (13036128)

    Published 2025
    “…ESTIMATE and CIBERSORT algorithms were performed to assess immune infiltration. …”
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  7. 5447
    Image1_Pan-cancer analysis of CREB3L1 as biomarker in the prediction of prognosis and immunotherapeutic efficacy.JPEG

    Image1_Pan-cancer analysis of CREB3L1 as biomarker in the prediction of prognosis and immunotherapeutic efficacy.JPEG by Zhengjun Lin (11050797)

    Published 2022
    “…Furthermore, Gene Set Enrichment Analysis (GSEA) was conducted to explore the potential biological functions and downstream pathways of CREB3L1 in different human cancers. …”
    Save to List
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  8. 5448
    Image3_Pan-cancer analysis of CREB3L1 as biomarker in the prediction of prognosis and immunotherapeutic efficacy.JPEG

    Image3_Pan-cancer analysis of CREB3L1 as biomarker in the prediction of prognosis and immunotherapeutic efficacy.JPEG by Zhengjun Lin (11050797)

    Published 2022
    “…Furthermore, Gene Set Enrichment Analysis (GSEA) was conducted to explore the potential biological functions and downstream pathways of CREB3L1 in different human cancers. …”
    Save to List
    Saved in:
  9. 5449
    Image1_Pan-cancer analysis of CREB3L1 as biomarker in the prediction of prognosis and immunotherapeutic efficacy.JPEG

    Image1_Pan-cancer analysis of CREB3L1 as biomarker in the prediction of prognosis and immunotherapeutic efficacy.JPEG by Zhengjun Lin (11050797)

    Published 2022
    “…Furthermore, Gene Set Enrichment Analysis (GSEA) was conducted to explore the potential biological functions and downstream pathways of CREB3L1 in different human cancers. …”
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  10. 5450
    Image_3_Serum-derived extracellular vesicles from breast cancer patients contribute to differential regulation of T-cell-mediated immune-escape mechanisms in breast cancer subtypes.tif

    Image_3_Serum-derived extracellular vesicles from breast cancer patients contribute to differential regulation of T-cell-mediated immune-escape mechanisms in breast cancer subtypes... by Rosalind Graham (10979421)

    Published 2023
    “…In-house bioinformatics algorithms were utilized for the computation of EV associated expression scores within The Cancer Genome Atlas (TCGA) and correlated with tumour infiltrating lymphocyte (TIL) scores. …”
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  11. 5451
    Image_1_Serum-derived extracellular vesicles from breast cancer patients contribute to differential regulation of T-cell-mediated immune-escape mechanisms in breast cancer subtypes.tif

    Image_1_Serum-derived extracellular vesicles from breast cancer patients contribute to differential regulation of T-cell-mediated immune-escape mechanisms in breast cancer subtypes... by Rosalind Graham (10979421)

    Published 2023
    “…In-house bioinformatics algorithms were utilized for the computation of EV associated expression scores within The Cancer Genome Atlas (TCGA) and correlated with tumour infiltrating lymphocyte (TIL) scores. …”
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  12. 5452
    Image_2_Serum-derived extracellular vesicles from breast cancer patients contribute to differential regulation of T-cell-mediated immune-escape mechanisms in breast cancer subtypes.tif

    Image_2_Serum-derived extracellular vesicles from breast cancer patients contribute to differential regulation of T-cell-mediated immune-escape mechanisms in breast cancer subtypes... by Rosalind Graham (10979421)

    Published 2023
    “…In-house bioinformatics algorithms were utilized for the computation of EV associated expression scores within The Cancer Genome Atlas (TCGA) and correlated with tumour infiltrating lymphocyte (TIL) scores. …”
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  13. 5453
    DataSheet_1_Serum-derived extracellular vesicles from breast cancer patients contribute to differential regulation of T-cell-mediated immune-escape mechanisms in breast cancer subtypes.pdf

    DataSheet_1_Serum-derived extracellular vesicles from breast cancer patients contribute to differential regulation of T-cell-mediated immune-escape mechanisms in breast cancer subt... by Rosalind Graham (10979421)

    Published 2023
    “…In-house bioinformatics algorithms were utilized for the computation of EV associated expression scores within The Cancer Genome Atlas (TCGA) and correlated with tumour infiltrating lymphocyte (TIL) scores. …”
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  14. 5454
    Image_2_Serum-derived extracellular vesicles from breast cancer patients contribute to differential regulation of T-cell-mediated immune-escape mechanisms in breast cancer subtypes.tif

    Image_2_Serum-derived extracellular vesicles from breast cancer patients contribute to differential regulation of T-cell-mediated immune-escape mechanisms in breast cancer subtypes... by Rosalind Graham (10979421)

    Published 2023
    “…In-house bioinformatics algorithms were utilized for the computation of EV associated expression scores within The Cancer Genome Atlas (TCGA) and correlated with tumour infiltrating lymphocyte (TIL) scores. …”
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    Saved in:
  15. 5455
    DataSheet_1_Serum-derived extracellular vesicles from breast cancer patients contribute to differential regulation of T-cell-mediated immune-escape mechanisms in breast cancer subtypes.pdf

    DataSheet_1_Serum-derived extracellular vesicles from breast cancer patients contribute to differential regulation of T-cell-mediated immune-escape mechanisms in breast cancer subt... by Rosalind Graham (10979421)

    Published 2023
    “…In-house bioinformatics algorithms were utilized for the computation of EV associated expression scores within The Cancer Genome Atlas (TCGA) and correlated with tumour infiltrating lymphocyte (TIL) scores. …”
    Save to List
    Saved in:
  16. 5456
    Image_1_Serum-derived extracellular vesicles from breast cancer patients contribute to differential regulation of T-cell-mediated immune-escape mechanisms in breast cancer subtypes.tif

    Image_1_Serum-derived extracellular vesicles from breast cancer patients contribute to differential regulation of T-cell-mediated immune-escape mechanisms in breast cancer subtypes... by Rosalind Graham (10979421)

    Published 2023
    “…In-house bioinformatics algorithms were utilized for the computation of EV associated expression scores within The Cancer Genome Atlas (TCGA) and correlated with tumour infiltrating lymphocyte (TIL) scores. …”
    Save to List
    Saved in:
  17. 5457
    Image_3_Serum-derived extracellular vesicles from breast cancer patients contribute to differential regulation of T-cell-mediated immune-escape mechanisms in breast cancer subtypes.tif

    Image_3_Serum-derived extracellular vesicles from breast cancer patients contribute to differential regulation of T-cell-mediated immune-escape mechanisms in breast cancer subtypes... by Rosalind Graham (10979421)

    Published 2023
    “…In-house bioinformatics algorithms were utilized for the computation of EV associated expression scores within The Cancer Genome Atlas (TCGA) and correlated with tumour infiltrating lymphocyte (TIL) scores. …”
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  18. 5458
    Data_Sheet_1_Back-Propagation Learning in Deep Spike-By-Spike Networks.pdf

    Data_Sheet_1_Back-Propagation Learning in Deep Spike-By-Spike Networks.pdf by David Rotermund (7213793)

    Published 2019
    “…What is missing, however, are algorithms for finding weight sets that would optimize the output performances of deep SbS networks with many layers. …”
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  19. 5459
    Data_Sheet_2_Back-Propagation Learning in Deep Spike-By-Spike Networks.ZIP

    Data_Sheet_2_Back-Propagation Learning in Deep Spike-By-Spike Networks.ZIP by David Rotermund (7213793)

    Published 2019
    “…What is missing, however, are algorithms for finding weight sets that would optimize the output performances of deep SbS networks with many layers. …”
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