Showing 141 - 160 results of 8,535 for search '(( algorithm python function ) OR ((( algorithm co functional ) OR ( algorithm cell function ))))', query time: 0.52s Refine Results
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    Efficient algorithms to discover alterations with complementary functional association in cancer by Rebecca Sarto Basso (6728921)

    Published 2019
    “…In addition, our algorithms are much faster than the state-of-the-art, allowing the analysis of large datasets of thousands of target profiles from cancer cell lines. …”
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    Image_1_Novel Survivin Peptides Screened With Computer Algorithm Induce Cytotoxic T Lymphocytes With Higher Cytotoxic Efficiency to Cancer Cells.tiff by Qiuqiang Chen (9332735)

    Published 2020
    “…To obtain novel SV decamers that are able to induce SV-specific cytotoxic T lymphocytes (CTLs) with a higher cytotoxic efficiency against cancer cells, major histocompatibility complex (MHC) peptide binding algorithms were conducted to predict nine modified SV<sub>95</sub> decamers (from SV<sub>95–2</sub> to SV<sub>95–10</sub>) based on the natural SV<sub>95–104</sub> peptide sequence of ELTLGEFLKL (here defined as SV<sub>95–1</sub>). …”
  8. 148

    Image_1_Novel Survivin Peptides Screened With Computer Algorithm Induce Cytotoxic T Lymphocytes With Higher Cytotoxic Efficiency to Cancer Cells.tiff by Qiuqiang Chen (9332735)

    Published 2020
    “…To obtain novel SV decamers that are able to induce SV-specific cytotoxic T lymphocytes (CTLs) with a higher cytotoxic efficiency against cancer cells, major histocompatibility complex (MHC) peptide binding algorithms were conducted to predict nine modified SV<sub>95</sub> decamers (from SV<sub>95–2</sub> to SV<sub>95–10</sub>) based on the natural SV<sub>95–104</sub> peptide sequence of ELTLGEFLKL (here defined as SV<sub>95–1</sub>). …”
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    Comparison of scores obtained by our interpenetration and scoring algorithm (ISA) and ROSETTA for a subset of structures. by Kevin Sawade (16726527)

    Published 2023
    “…However, our algorithm was 1000 times faster than pyROSETTA (both algorithms have been parallelized on a per-structure basis using the Python package joblib [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1010531#pcbi.1010531.ref069" target="_blank">69</a>]).…”
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    Supplementary file 1_Earthworm optimization algorithm for extracting parameters for solar cells and photovoltaic modules.docx by Fatima Wardi (22052360)

    Published 2025
    “…The extracted parameters for each case study are used to reconstruct the I–V and power–voltage (P–V) characteristic curves for the respective solar cell and photovoltaic module technologies. To validate the performance and efficiency of the algorithm, various statistical criteria are computed, including individual absolute error (IAE), relative error (RE), root mean square error (RMSE), mean absolute error (MAE), standard deviation (SD), tracking signal (TS), normalized forecast measure (NFM), and the autocorrelation function (ACF). …”
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