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Showing 61 - 80 results of 194 for search '(( python code implementation ) OR ( python ((time implementation) OR (modular implementation)) ))', query time: 0.48s Refine Results
  1. 61
    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 <... by Ziyan Jin (21021976)

    Published 2025
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  2. 62
    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... by Ziyan Jin (21021976)

    Published 2025
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  3. 63
    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... by Ziyan Jin (21021976)

    Published 2025
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  4. 64
    SEPARATE Code Repository

    SEPARATE Code Repository by Gyuri Kim (21424973)

    Published 2025
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  5. 65
    Data&Codes.zip

    Data&Codes.zip by Zer0 Star (20545655)

    Published 2025
    “…</p><p dir="ltr">To facilitate the widespread use of the proposed framework, we have implemented it as the <b><i>ESLocalIndi</i></b> open-source package in Python, making it easily accessible to geographers. …”
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  6. 66
    software code of NeoDesign

    software code of NeoDesign by Wenqian Yu (19730101)

    Published 2024
    “…<h2>Implementation and Dependencies</h2><p dir="ltr">neoDesign was developed with python (recommend>3.9) and shell (bash) language. …”
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  7. 67
    DA-Faster-RCNN code

    DA-Faster-RCNN code by Seunghyeon Wang (16500132)

    Published 2025
    “…The implementation is written in Python using PyTorch and Detectron2.…”
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  8. 68
    Reproducible Code and Data for figures

    Reproducible Code and Data for figures by Bonyad Ahmadi (20750327)

    Published 2025
    “…</i></p><p dir="ltr">It contains:</p><p dir="ltr">✅ <b>Python Code</b> – Scripts used for data preprocessing, and visualization.…”
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  9. 69
    Simulation Code and Raw Data

    Simulation Code and Raw Data by Melih Özkurt (22278520)

    Published 2025
    “…<p dir="ltr">Reproducible code (Python) implementing a symmetrized split-step Fourier method (SSFM), with configuration files for all scans. …”
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  10. 70
    Tracking module training details.

    Tracking module training details. by Khelina Fedorchuk (19130089)

    Published 2025
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  11. 71
    Segmentation module training details.

    Segmentation module training details. by Khelina Fedorchuk (19130089)

    Published 2025
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  12. 72
    BlueRecording simulates hippocampal LFP.

    BlueRecording simulates hippocampal LFP. by Joseph James Tharayil (21416715)

    Published 2025
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  13. 73
    The format of the electrode csv file

    The format of the electrode csv file by Joseph James Tharayil (21416715)

    Published 2025
    “…To enable efficient calculation of extracellular signals from large neural network simulations, we have developed <i>BlueRecording</i>, a pipeline consisting of standalone Python code, along with extensions to the Neurodamus simulation control application, the CoreNEURON computation engine, and the SONATA data format, to permit online calculation of such signals. …”
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  14. 74
    The format of the simulation reports

    The format of the simulation reports by Joseph James Tharayil (21416715)

    Published 2025
    “…To enable efficient calculation of extracellular signals from large neural network simulations, we have developed <i>BlueRecording</i>, a pipeline consisting of standalone Python code, along with extensions to the Neurodamus simulation control application, the CoreNEURON computation engine, and the SONATA data format, to permit online calculation of such signals. …”
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  15. 75
    Comparison of BlueRecording with existing tools

    Comparison of BlueRecording with existing tools by Joseph James Tharayil (21416715)

    Published 2025
    “…To enable efficient calculation of extracellular signals from large neural network simulations, we have developed <i>BlueRecording</i>, a pipeline consisting of standalone Python code, along with extensions to the Neurodamus simulation control application, the CoreNEURON computation engine, and the SONATA data format, to permit online calculation of such signals. …”
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  16. 76
    The format of the weights file

    The format of the weights file by Joseph James Tharayil (21416715)

    Published 2025
    “…To enable efficient calculation of extracellular signals from large neural network simulations, we have developed <i>BlueRecording</i>, a pipeline consisting of standalone Python code, along with extensions to the Neurodamus simulation control application, the CoreNEURON computation engine, and the SONATA data format, to permit online calculation of such signals. …”
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  17. 77
    RealBench: A Repo-Level Code Generation Benchmark Aligned with Real-World Software Development Practices

    RealBench: A Repo-Level Code Generation Benchmark Aligned with Real-World Software Development Practices by RealBench RealBench (22275393)

    Published 2025
    “…<br>│ ├── model_gen/ # Code generation using various LLMs.<br>│ │ ├── generate/ # LLM inference implementations.…”
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  18. 78
    DeepB3Pred - code

    DeepB3Pred - code by Saleh Musleh (22263718)

    Published 2025
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  19. 79
    A game of life with dormancy - Code

    A game of life with dormancy - Code by Daniel Henrik Nevermann (20376933)

    Published 2024
    “…</p><ul><li>To run an animated simulation, use `python simulation.py'.</li><li>The implementation of Spore Life can be found in gol.py.…”
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  20. 80
    Simple implementation examples of agent AI on free energy calculation and phase-field simulation

    Simple implementation examples of agent AI on free energy calculation and phase-field simulation by Toshiyuki Koyama (22828581)

    Published 2025
    “…</p> <p>Using Gibbs energy calculations and diffusion simulations as examples, we demonstrated the implementation method and usefulness of simple agent AI, where sample python codes are distributed as supplemental materials.…”
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