بدائل البحث:
code implementation » model implementation (توسيع البحث), time implementation (توسيع البحث), world implementation (توسيع البحث)
model implementing » model implemented (توسيع البحث), model implementation (توسيع البحث), model representing (توسيع البحث)
code implementing » consider implementing (توسيع البحث), _ implementing (توسيع البحث)
يعرض 101 - 120 نتائج من 286 نتيجة بحث عن '(( python code implementation ) OR ( python ((code implementing) OR (model implementing)) ))', وقت الاستعلام: 0.45s تنقيح النتائج
  1. 101
    Type I error rate from estimation of simulated outcomes using the EE algorithm.

    Type I error rate from estimation of simulated outcomes using the EE algorithm. حسب Alex Stivala (8356257)

    منشور في 2024
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  2. 102
    Example ALAAMEE output.

    Example ALAAMEE output. حسب Alex Stivala (8356257)

    منشور في 2024
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  3. 103
    Type II error rate as the number of runs used for each sample is varied.

    Type II error rate as the number of runs used for each sample is varied. حسب Alex Stivala (8356257)

    منشور في 2024
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  4. 104
    Parameter estimates and estimated standard errors from the EE algorithm.

    Parameter estimates and estimated standard errors from the EE algorithm. حسب Alex Stivala (8356257)

    منشور في 2024
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  5. 105
    Network descriptive statistics for the Deezer networks.

    Network descriptive statistics for the Deezer networks. حسب Alex Stivala (8356257)

    منشور في 2024
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  6. 106
    Example ALAAMEE goodness-of-fit output.

    Example ALAAMEE goodness-of-fit output. حسب Alex Stivala (8356257)

    منشور في 2024
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  7. 107
    ZILLNB_Model

    ZILLNB_Model حسب Qinhuan Luo (21288548)

    منشور في 2025
    "…<p dir="ltr">Acquire latent variables using deep-learning based model implemented in python</p>…"
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  8. 108
    Bursty model and Refractory model simulation results. (A) Bursty model simulation results ( samples). The production of nascent mRNA occurs in bursts and degrade after delay time <i>τ</i>. The burst frequency , the mean burst size and . (B) Refractory model simulation results ( samples). The gene has three states, , and , and can switch from one state to another. Moreover, nascent mRNA is produced only when the gene is in state . The parameters are , , , and <i>τ</i> = 1.

    Bursty model and Refractory model simulation results. (A) Bursty model simulation results ( samples). The production of nascent mRNA occurs in bursts and degrade after delay time <... حسب Ziyan Jin (21021976)

    منشور في 2025
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  9. 109
    Flowchart representation of lion optimization algorithm for hyperparameter tuning in the HCAP model.

    Flowchart representation of lion optimization algorithm for hyperparameter tuning in the HCAP model. حسب Mohanad Faeq Ali (21354273)

    منشور في 2025
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  10. 110
    RNA Velocity model simulation results. (A) Simulation results for RNA Velocity model without delay ( samples). The simulation is composed of an up-regulation phase (both production and degradation) and a down-regulation phase (degradation-only). In the first phase, <i>%</i>, <i>%</i> and <i>%</i> for the reaction time . In the second phase,  ∕ 1, <i>X</i> ∼ NB ( <i>r</i> , <i>μ</i> )  and <i>μ</i>. (B) Simulation results for RNA Velocity model with delay in degradation ( samples). RNA degradation is specified as a delayed reaction. In the first (up-regulation) phase: <i>Y</i> ≡ <i>n</i>, <i>t</i> = 0 and <i>%</i>. In the second (down-regulation) phase: <i>%</i>, <i>%</i> and <i>%.</i>

    RNA Velocity model simulation results. (A) Simulation results for RNA Velocity model without delay ( samples). The simulation is composed of an up-regulation phase (both production... حسب Ziyan Jin (21021976)

    منشور في 2025
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  11. 111
    Modeling lung cancer AST network and its perturbation with a SOX2 degrader. (A) Lung Cancer AST Network and the corresponding stochastic equations. Parameters are , , , , , , , , with different . The control parameter is . (B) The potential landscape is approximated by simulating a large number of molecules corresponding to concentrations ( samples) with parameter values , , and , respectively representing the adenocarcinoma state, the intermediate state, and the squamous carcinoma state. FOXA2 and SOX2 amounts are chosen to visualize the landscape. (C) Principle of SOX2-targeted degradation by the PROTAC technique. The PROTAC molecule here is designed to recognize SOX2 proteins and to recruit E3 ligases to induce an addition of ubiquitin (Ub) proteins onto SOX2, which causes degradation of SOX2 subsequently. (D) Application of a SOX2 degrader to the squamous carcinoma state () reprogram the AST network back to the adenocarcinoma state. Here the treatment effect of the SOX2 degrad

    Modeling lung cancer AST network and its perturbation with a SOX2 degrader. (A) Lung Cancer AST Network and the corresponding stochastic equations. Parameters are , , , , , , , , w... حسب Ziyan Jin (21021976)

    منشور في 2025
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  12. 112
    High-Throughput Mass Spectral Library Searching of Small Molecules in R with NIST MSPepSearch

    High-Throughput Mass Spectral Library Searching of Small Molecules in R with NIST MSPepSearch حسب Andrey Samokhin (20282728)

    منشور في 2025
    "…Despite the availability of numerous library search algorithms, those developed by NIST and implemented in MS Search remain predominant, partly because commercial databases (e.g., NIST, Wiley) are distributed in proprietary formats inaccessible to custom code. …"
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  13. 113
    Comparison data 7 for <i>Lamprologus ocellatus</i>.

    Comparison data 7 for <i>Lamprologus ocellatus</i>. حسب Nicolai Kraus (19949667)

    منشور في 2024
    "…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …"
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  14. 114
    Sample data for <i>Neolamprologus multifasciatus</i>.

    Sample data for <i>Neolamprologus multifasciatus</i>. حسب Nicolai Kraus (19949667)

    منشور في 2024
    "…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …"
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  15. 115
    Sample data for <i>Lamprologus ocellatus</i>.

    Sample data for <i>Lamprologus ocellatus</i>. حسب Nicolai Kraus (19949667)

    منشور في 2024
    "…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …"
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  16. 116
    Comparison data 3 for <i>Lamprologus ocellatus</i>.

    Comparison data 3 for <i>Lamprologus ocellatus</i>. حسب Nicolai Kraus (19949667)

    منشور في 2024
    "…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …"
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  17. 117
    Sample data for <i>Telmatochromis temporalis</i>.

    Sample data for <i>Telmatochromis temporalis</i>. حسب Nicolai Kraus (19949667)

    منشور في 2024
    "…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …"
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  18. 118
    Comparison data 4 for <i>Lamprologus ocellatus</i>.

    Comparison data 4 for <i>Lamprologus ocellatus</i>. حسب Nicolai Kraus (19949667)

    منشور في 2024
    "…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …"
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  19. 119
    Comparison data 1 for <i>Lamprologus ocellatus</i>.

    Comparison data 1 for <i>Lamprologus ocellatus</i>. حسب Nicolai Kraus (19949667)

    منشور في 2024
    "…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …"
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  20. 120
    Comparison data 2 for <i>Lamprologus ocellatus</i>.

    Comparison data 2 for <i>Lamprologus ocellatus</i>. حسب Nicolai Kraus (19949667)

    منشور في 2024
    "…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …"
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