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Showing 1 - 9 results of 9 for search '(((( algorithm based function ) OR ( algorithm cl function ))) OR ( algorithm both function ))~', query time: 0.31s Refine Results
  1. 1
    Table 1_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.xlsx

    Table 1_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.xlsx by Peng Liu (120506)

    Published 2025
    “…Further, based upon the upstream regulatory network, TP53, RARB, RXRB, and CTCF potentially exerted regulatory functions. …”
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  2. 2
    Image 1_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff

    Image 1_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff by Peng Liu (120506)

    Published 2025
    “…Further, based upon the upstream regulatory network, TP53, RARB, RXRB, and CTCF potentially exerted regulatory functions. …”
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  3. 3
    Image 4_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff

    Image 4_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff by Peng Liu (120506)

    Published 2025
    “…Further, based upon the upstream regulatory network, TP53, RARB, RXRB, and CTCF potentially exerted regulatory functions. …”
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  4. 4
    Image 5_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff

    Image 5_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff by Peng Liu (120506)

    Published 2025
    “…Further, based upon the upstream regulatory network, TP53, RARB, RXRB, and CTCF potentially exerted regulatory functions. …”
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  5. 5
    Image 3_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff

    Image 3_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff by Peng Liu (120506)

    Published 2025
    “…Further, based upon the upstream regulatory network, TP53, RARB, RXRB, and CTCF potentially exerted regulatory functions. …”
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  6. 6
    Image 2_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff

    Image 2_Comprehensive analysis of anoikis-related gene signature in ulcerative colitis using machine learning algorithms.tiff by Peng Liu (120506)

    Published 2025
    “…Further, based upon the upstream regulatory network, TP53, RARB, RXRB, and CTCF potentially exerted regulatory functions. …”
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  7. 7
    Supporting Data for “All-temperature barocaloric effects at pressure-induced phase transitions”

    Supporting Data for “All-temperature barocaloric effects at pressure-induced phase transitions” by Zhao Xueting (21796316)

    Published 2025
    “…The PBEsol<sup>40</sup> exchange-correlation functional was used, which yields a better description of the equilibrium properties of solids<sup>40</sup>. …”
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  8. 8
    Akt1 prodigiosin docking and dynamic molecular

    Akt1 prodigiosin docking and dynamic molecular by Fares ELGHALI (18467655)

    Published 2024
    “…Long-range electrostatic interactions were calculated using the particle-mesh Ewald (PME) algorithm, with a real space cutoff of 1.2 nm. (8) Initial Velocities Assignment: Initial velocities of particles were assigned based on Maxwell distributions to set the system in motion. (9) Molecular Dynamics Simulation: tow simulations have been performed between 10 and 100 nanosecond (ns) with sampling of each 5 ns, MD simulation was conducted to observe and analyze the system's behavior over an extended period. (10) Analysis: Various parameters including root mean square deviations (RMSD), residue root means square fluctuation (RMSF), number of hydrogen bonds (HB), radius of gyration (Rg) were calculated to analyze the system's dynamics and interactions. …”
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  9. 9
    Raw LC-MS/MS and RNA-Seq Mitochondria data

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

    Published 2025
    “…The missing values were imputed with the minimum intensity value for each specific data set; (b) for samples expressed in both scLRP1+/+ and scLRP1-/- tissue, the filtering process required 2 or more proteins to be detected in both scLRP1+/+ and scLRP1-/- samples. …”
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