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Showing 2,921 - 2,939 results of 2,939 for search '(( algorithm without functional ) OR ( ((algorithm python) OR (algorithm within)) function ))', query time: 0.44s Refine Results
  1. 2921

    Enrichment analysis of GO. by Yinghao Ren (17915291)

    Published 2025
    “…We also identified differentially expressed genes (DEGs) within the clusters and between SLE patients and healthy controls. …”
  2. 2922

    Lasso gene RF hub gene. by Yinghao Ren (17915291)

    Published 2025
    “…We also identified differentially expressed genes (DEGs) within the clusters and between SLE patients and healthy controls. …”
  3. 2923

    Enrichment analysis of KEGG. by Yinghao Ren (17915291)

    Published 2025
    “…We also identified differentially expressed genes (DEGs) within the clusters and between SLE patients and healthy controls. …”
  4. 2924

    Image 1_Characterization of cancer-related fibroblasts in bladder cancer and construction of CAFs-based bladder cancer classification: insights from single-cell and multi-omics ana... by Zhaokai Zhou (15239078)

    Published 2025
    “…Moreover, machine learning algorithms were applied to identify novel potential targets for each subtype, and experimentally validate their effects.…”
  5. 2925

    Table 1_Characterization of cancer-related fibroblasts in bladder cancer and construction of CAFs-based bladder cancer classification: insights from single-cell and multi-omics ana... by Zhaokai Zhou (15239078)

    Published 2025
    “…Moreover, machine learning algorithms were applied to identify novel potential targets for each subtype, and experimentally validate their effects.…”
  6. 2926

    Image 2_Characterization of cancer-related fibroblasts in bladder cancer and construction of CAFs-based bladder cancer classification: insights from single-cell and multi-omics ana... by Zhaokai Zhou (15239078)

    Published 2025
    “…Moreover, machine learning algorithms were applied to identify novel potential targets for each subtype, and experimentally validate their effects.…”
  7. 2927

    Raw LC-MS/MS and RNA-Seq Mitochondria data by Stefano Martellucci (16284377)

    Published 2025
    “…Differentially altered pathways were evaluated by using the enrich plot package in R for visualization of functional enrichment (i.e., dot plot).</p>…”
  8. 2928

    Image_1_A Novel CpG Methylation Risk Indicator for Predicting Prognosis in Bladder Cancer.TIF by Yufeng Guo (563481)

    Published 2021
    “…In the MRSB high-risk group, the hazard curve exhibited an initial wide, high peak within 10 months after treatment, whereas some gentle peaks around 2 years were noted. …”
  9. 2929

    Image_2_A Novel CpG Methylation Risk Indicator for Predicting Prognosis in Bladder Cancer.TIF by Yufeng Guo (563481)

    Published 2021
    “…In the MRSB high-risk group, the hazard curve exhibited an initial wide, high peak within 10 months after treatment, whereas some gentle peaks around 2 years were noted. …”
  10. 2930

    Image_3_A Novel CpG Methylation Risk Indicator for Predicting Prognosis in Bladder Cancer.TIF by Yufeng Guo (563481)

    Published 2021
    “…In the MRSB high-risk group, the hazard curve exhibited an initial wide, high peak within 10 months after treatment, whereas some gentle peaks around 2 years were noted. …”
  11. 2931

    Data_Sheet_1_A Novel CpG Methylation Risk Indicator for Predicting Prognosis in Bladder Cancer.CSV by Yufeng Guo (563481)

    Published 2021
    “…In the MRSB high-risk group, the hazard curve exhibited an initial wide, high peak within 10 months after treatment, whereas some gentle peaks around 2 years were noted. …”
  12. 2932

    Table_1_A Novel CpG Methylation Risk Indicator for Predicting Prognosis in Bladder Cancer.XLSX by Yufeng Guo (563481)

    Published 2021
    “…In the MRSB high-risk group, the hazard curve exhibited an initial wide, high peak within 10 months after treatment, whereas some gentle peaks around 2 years were noted. …”
  13. 2933

    Image_4_A Novel CpG Methylation Risk Indicator for Predicting Prognosis in Bladder Cancer.TIF by Yufeng Guo (563481)

    Published 2021
    “…In the MRSB high-risk group, the hazard curve exhibited an initial wide, high peak within 10 months after treatment, whereas some gentle peaks around 2 years were noted. …”
  14. 2934

    Data_Sheet_2_A Novel CpG Methylation Risk Indicator for Predicting Prognosis in Bladder Cancer.CSV by Yufeng Guo (563481)

    Published 2021
    “…In the MRSB high-risk group, the hazard curve exhibited an initial wide, high peak within 10 months after treatment, whereas some gentle peaks around 2 years were noted. …”
  15. 2935

    DataSheet1_Mitochondrial-related genes as prognostic and metastatic markers in breast cancer: insights from comprehensive analysis and clinical models.docx by Yutong Fang (16621143)

    Published 2024
    “…Moreover, leveraging the GSE102484 dataset, we conducted differential gene expression analysis to identify MRGs related to metastasis, subsequently developing metastasis models via 10 distinct machine-learning algorithms and then selecting the best-performing model. …”
  16. 2936

    Table1_Mitochondrial-related genes as prognostic and metastatic markers in breast cancer: insights from comprehensive analysis and clinical models.xlsx by Yutong Fang (16621143)

    Published 2024
    “…Moreover, leveraging the GSE102484 dataset, we conducted differential gene expression analysis to identify MRGs related to metastasis, subsequently developing metastasis models via 10 distinct machine-learning algorithms and then selecting the best-performing model. …”
  17. 2937

    Table2_YinChen WuLing powder attenuates non-alcoholic steatohepatitis through the inhibition of the SHP2/PI3K/NLRP3 pathway.xlsx by Xingxing Yuan (6615878)

    Published 2024
    “…Through analytic integration with multiple algorithms, PTPN11 (also known as SHP2) emerged as a core target of YCWLP in mitigating NASH. …”
  18. 2938

    Table1_YinChen WuLing powder attenuates non-alcoholic steatohepatitis through the inhibition of the SHP2/PI3K/NLRP3 pathway.pdf by Xingxing Yuan (6615878)

    Published 2024
    “…Through analytic integration with multiple algorithms, PTPN11 (also known as SHP2) emerged as a core target of YCWLP in mitigating NASH. …”
  19. 2939

    FCP dataset for forecasting temperature, PV, price, and load by Hanwen Zhang (18259666)

    Published 2025
    “…</p><p><br></p><p dir="ltr">In this project, we propose to empower the EV chargers with 5G capabilities for connectivity and computing and bring smartness and intelligence into them. 5G is fast, so the high-resolution EV charger data can be accessed in real-time with minimal delay. 5G supports high concurrency, so a large number of EV chargers can utilize the connectivity without being forced to be sequential to avoid conflict and long delay. 5G has great bandwidth, so abundant information from EV chargers and the associated facilities like battery energy storage systems (BESS) and solar panels can be transmitted. 5G is also ultra-reliable with low latency which makes 5G suitable for mission critical functionalities and time-sensitive control. …”