U-MIMIC Documentation¶

Unified Mechanistic Inference from Multimodal Imaging and Counts

U-MIMIC is a Python package for modeling and analyzing tumor population dynamics under drug treatment. It provides mechanistic simulation (ODE, Gillespie, tau-leaping), multimodal observation models (cell counts, BLI, tumor volume), and inference workflows (MLE, MCMC, SMC, hierarchical Bayesian).

Developed by the Data Analysis Team @KaziLab.se.

Getting Started¶

pip install umimic
umimic --help

User Guide

  • Quickstart
    • Installation
    • Your First Simulation
    • Programmatic Usage
    • Generate Synthetic Data
    • Fit a Model
    • YAML Configuration
    • Loading Public Datasets
    • Next Steps
  • Configuration Reference
    • Top-Level: ExperimentConfig
    • DynamicsConfig
    • PKConfig
    • DosingConfig
    • ObservationConfig
    • InferenceConfig
    • SimulationConfig
    • PriorConfig
    • Complete Example

Reference

  • API Reference
    • Pipeline
    • Dynamics
    • Pharmacokinetics
    • Observations
    • Inference
    • Data
    • Result Types

Infrastructure

  • Read the Docs Implementation from GitHub
    • Architecture
    • Repository files required
    • 1. Import the repository into Read the Docs
    • 2. Connect GitHub webhooks
    • 3. Build configuration details
    • 4. Local validation before pushing
    • 5. Configure versions and preview behavior in RTD
    • 6. Add docs status to GitHub (optional)
    • 7. Troubleshooting
    • Operational checklist
    • Acknowledgements
  • PyPI Trusted Publishing from GitHub Actions
    • What is configured in this repository
    • One-time setup in PyPI
    • One-time setup in GitHub
    • Release process
    • Troubleshooting

U-MIMIC

Navigation

User Guide

  • Quickstart
  • Configuration Reference

Reference

  • API Reference

Infrastructure

  • Read the Docs Implementation from GitHub
  • PyPI Trusted Publishing from GitHub Actions

Related Topics

  • Documentation overview
    • Next: Quickstart
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