Search alternatives:
algorithm python » algorithms within (Expand Search), algorithm both (Expand Search)
within function » fibrin function (Expand Search), protein function (Expand Search), catenin function (Expand Search)
python function » protein function (Expand Search)
Showing 601 - 620 results of 731 for search '(( algorithm within function ) OR ( algorithm python function ))*', query time: 0.23s Refine Results
  1. 601
    Table 2_A novel prognostic signature identifies MFAP4 as a tumor suppressor linking the tumor microenvironment to PI3K/AKT signaling in triple-negative breast cancer.xlsx

    Table 2_A novel prognostic signature identifies MFAP4 as a tumor suppressor linking the tumor microenvironment to PI3K/AKT signaling in triple-negative breast cancer.xlsx by Xiaoqin Yu (3918377)

    Published 2025
    “…The model’s association with TME characteristics was assessed using ESTIMATE algorithm and immune infiltration analyses. The biological functions of the key gene, Microfibril Associated Protein 4 (MFAP4), were investigated in vitro via proliferation and migration assays. …”
    Save to List
    Saved in:
  2. 602
    Data Sheet 1_A novel prognostic signature identifies MFAP4 as a tumor suppressor linking the tumor microenvironment to PI3K/AKT signaling in triple-negative breast cancer.pdf

    Data Sheet 1_A novel prognostic signature identifies MFAP4 as a tumor suppressor linking the tumor microenvironment to PI3K/AKT signaling in triple-negative breast cancer.pdf by Xiaoqin Yu (3918377)

    Published 2025
    “…The model’s association with TME characteristics was assessed using ESTIMATE algorithm and immune infiltration analyses. The biological functions of the key gene, Microfibril Associated Protein 4 (MFAP4), were investigated in vitro via proliferation and migration assays. …”
    Save to List
    Saved in:
  3. 603
    Table 1_The analysis of gene co-expression network and immune infiltration revealed biomarkers between triple-negative and non-triple negative breast cancer.xlsx

    Table 1_The analysis of gene co-expression network and immune infiltration revealed biomarkers between triple-negative and non-triple negative breast cancer.xlsx by Yao Yi (459571)

    Published 2025
    “…CIBERSORT analysis was used to characterize the composition of immune cells within complex tissues based on gene expression data, typically derived from bulk RNA sequencing or microarray datasets. …”
    Save to List
    Saved in:
  4. 604
    Image 1_The analysis of gene co-expression network and immune infiltration revealed biomarkers between triple-negative and non-triple negative breast cancer.tif

    Image 1_The analysis of gene co-expression network and immune infiltration revealed biomarkers between triple-negative and non-triple negative breast cancer.tif by Yao Yi (459571)

    Published 2025
    “…CIBERSORT analysis was used to characterize the composition of immune cells within complex tissues based on gene expression data, typically derived from bulk RNA sequencing or microarray datasets. …”
    Save to List
    Saved in:
  5. 605
    Image 3_The analysis of gene co-expression network and immune infiltration revealed biomarkers between triple-negative and non-triple negative breast cancer.tif

    Image 3_The analysis of gene co-expression network and immune infiltration revealed biomarkers between triple-negative and non-triple negative breast cancer.tif by Yao Yi (459571)

    Published 2025
    “…CIBERSORT analysis was used to characterize the composition of immune cells within complex tissues based on gene expression data, typically derived from bulk RNA sequencing or microarray datasets. …”
    Save to List
    Saved in:
  6. 606
    Image 2_The analysis of gene co-expression network and immune infiltration revealed biomarkers between triple-negative and non-triple negative breast cancer.tif

    Image 2_The analysis of gene co-expression network and immune infiltration revealed biomarkers between triple-negative and non-triple negative breast cancer.tif by Yao Yi (459571)

    Published 2025
    “…CIBERSORT analysis was used to characterize the composition of immune cells within complex tissues based on gene expression data, typically derived from bulk RNA sequencing or microarray datasets. …”
    Save to List
    Saved in:
  7. 607
    Table 2_The analysis of gene co-expression network and immune infiltration revealed biomarkers between triple-negative and non-triple negative breast cancer.xlsx

    Table 2_The analysis of gene co-expression network and immune infiltration revealed biomarkers between triple-negative and non-triple negative breast cancer.xlsx by Yao Yi (459571)

    Published 2025
    “…CIBERSORT analysis was used to characterize the composition of immune cells within complex tissues based on gene expression data, typically derived from bulk RNA sequencing or microarray datasets. …”
    Save to List
    Saved in:
  8. 608
    Table 3_The analysis of gene co-expression network and immune infiltration revealed biomarkers between triple-negative and non-triple negative breast cancer.xlsx

    Table 3_The analysis of gene co-expression network and immune infiltration revealed biomarkers between triple-negative and non-triple negative breast cancer.xlsx by Yao Yi (459571)

    Published 2025
    “…CIBERSORT analysis was used to characterize the composition of immune cells within complex tissues based on gene expression data, typically derived from bulk RNA sequencing or microarray datasets. …”
    Save to List
    Saved in:
  9. 609
    Image 4_The analysis of gene co-expression network and immune infiltration revealed biomarkers between triple-negative and non-triple negative breast cancer.tif

    Image 4_The analysis of gene co-expression network and immune infiltration revealed biomarkers between triple-negative and non-triple negative breast cancer.tif by Yao Yi (459571)

    Published 2025
    “…CIBERSORT analysis was used to characterize the composition of immune cells within complex tissues based on gene expression data, typically derived from bulk RNA sequencing or microarray datasets. …”
    Save to List
    Saved in:
  10. 610
    Image 1_Targeting a distinct binding pocket in the pregnane X receptor with natural agonist TRLW-2 ameliorates murine ulcerative colitis.tif

    Image 1_Targeting a distinct binding pocket in the pregnane X receptor with natural agonist TRLW-2 ameliorates murine ulcerative colitis.tif by Shangrui Rao (18189241)

    Published 2025
    “…</p>Methods<p>A distinct binding pocket (Pocket 1–5) within the PXR ligand-binding domain was identified using a multi-algorithm computational approach (SiteMap, Fpocket, Prank, CASTpFold). …”
    Save to List
    Saved in:
  11. 611
    Image 2_Targeting a distinct binding pocket in the pregnane X receptor with natural agonist TRLW-2 ameliorates murine ulcerative colitis.tif

    Image 2_Targeting a distinct binding pocket in the pregnane X receptor with natural agonist TRLW-2 ameliorates murine ulcerative colitis.tif by Shangrui Rao (18189241)

    Published 2025
    “…</p>Methods<p>A distinct binding pocket (Pocket 1–5) within the PXR ligand-binding domain was identified using a multi-algorithm computational approach (SiteMap, Fpocket, Prank, CASTpFold). …”
    Save to List
    Saved in:
  12. 612
    Image 3_Targeting a distinct binding pocket in the pregnane X receptor with natural agonist TRLW-2 ameliorates murine ulcerative colitis.tif

    Image 3_Targeting a distinct binding pocket in the pregnane X receptor with natural agonist TRLW-2 ameliorates murine ulcerative colitis.tif by Shangrui Rao (18189241)

    Published 2025
    “…</p>Methods<p>A distinct binding pocket (Pocket 1–5) within the PXR ligand-binding domain was identified using a multi-algorithm computational approach (SiteMap, Fpocket, Prank, CASTpFold). …”
    Save to List
    Saved in:
  13. 613
    Image 4_Targeting a distinct binding pocket in the pregnane X receptor with natural agonist TRLW-2 ameliorates murine ulcerative colitis.tif

    Image 4_Targeting a distinct binding pocket in the pregnane X receptor with natural agonist TRLW-2 ameliorates murine ulcerative colitis.tif by Shangrui Rao (18189241)

    Published 2025
    “…</p>Methods<p>A distinct binding pocket (Pocket 1–5) within the PXR ligand-binding domain was identified using a multi-algorithm computational approach (SiteMap, Fpocket, Prank, CASTpFold). …”
    Save to List
    Saved in:
  14. 614
    Additional data for the polyanion sodium cathode materials dataset

    Additional data for the polyanion sodium cathode materials dataset by Martin Hoffmann Petersen (13626778)

    Published 2024
    “…All simulations are executed within the canonical (NVT) ensemble and a sample frequency was set to 1fs.…”
    Save to List
    Saved in:
  15. 615
    Data Sheet 1_TGM2 regulated by transcription factor NR3C1 drives p38 MAPK-mediated tumor progression and immune evasion in lung squamous cell carcinoma.zip

    Data Sheet 1_TGM2 regulated by transcription factor NR3C1 drives p38 MAPK-mediated tumor progression and immune evasion in lung squamous cell carcinoma.zip by Chunlong Lin (18931437)

    Published 2025
    “…Key genes were screened via random forest algorithm. Functional validation was performed in NCI-H520 and SK-MES-1 cell lines. …”
    Save to List
    Saved in:
  16. 616
    Supporting data for "Machine learning based prognosis prediction of intracerebral hemorrhage outcome".

    Supporting data for "Machine learning based prognosis prediction of intracerebral hemorrhage outcome". by Eunhye Yang (17853260)

    Published 2025
    “…The resulting prognosis prediction ML model, based on Random Forest algorithm, achieved an overall accuracy of 0.81, with AUROCs of 0.93, 0.84 and 0.95 for good, poor, and death outcomes, respectively. …”
    Save to List
    Saved in:
  17. 617
    University of Arizona authors' scholarly works published and cited works year 2022 from OpenAlex

    University of Arizona authors' scholarly works published and cited works year 2022 from OpenAlex by Yan Han (11106597)

    Published 2025
    “…</li><li><b>Data Retrieval:</b> The process involves using the oa_fetch function from the openalexR package with the entity="works" parameter and specifying the institutions.ror.…”
    Save to List
    Saved in:
  18. 618
    University of Arizona authors' scholarly works published and cited works year 2023 from OpenAlex

    University of Arizona authors' scholarly works published and cited works year 2023 from OpenAlex by Yan Han (11106597)

    Published 2025
    “…</li></ul><p dir="ltr">The second dataset "works_cited", refers to <b>scholarly works cited by the publications within the </b><b>works_published</b><b> dataset</b>. …”
    Save to List
    Saved in:
  19. 619
    University of Arizona authors' scholarly works published and cited works year 2021 from OpenAlex

    University of Arizona authors' scholarly works published and cited works year 2021 from OpenAlex by Yan Han (11106597)

    Published 2025
    “…</li><li><b>Data Retrieval:</b> The process involves using the oa_fetch function from the openalexR package with the entity="works" parameter and specifying the institutions.ror.…”
    Save to List
    Saved in:
  20. 620
    University of Arizona authors' scholarly works published and cited works year 2024 from OpenAlex

    University of Arizona authors' scholarly works published and cited works year 2024 from OpenAlex by Yan Han (11106597)

    Published 2025
    “…</li><li><b>Data Retrieval:</b> The process involves using the oa_fetch function from the openalexR package with the entity="works" parameter and specifying the institutions.ror.…”
    Save to List
    Saved in:

Search Tools: