PyAntiGen

PyAntiGen is a declarative, object-oriented framework for generating compartmental biological models in Antimony format. It is designed to abstract away the repetitive boilerplate of defining reactions and compartments manually, allowing researchers to build complex, scalable models using clean Python syntax.

Features

• Object-Oriented Modules: Encapsulate tissues, flows, synthesis, and excretion into reusable Python classes.
• Dynamic Registration: Automatically binds reactions, compartments, and species to the global model state when a module is instantiated.
• Project Scaffolding: Includes a CLI command to instantly spin up new modeling projects with all necessary directories.
• Isotope Tracking: Natively supports tracking labeled isotopes and generating corresponding parallel reactions.

Installation

You can install PyAntiGen into your Python environment with:

pip install pyantigen

You can also install PyAntiGen globally into your preferred Python environment by cloning this repository and running pip:

git clone https://github.com/elbert5770/PyAntiGen.git
cd PyAntiGen
pip install -e .

Quick Start: Creating a New Model

Because PyAntiGen is installed as a system-level Python package, you don't need a copy of the framework files in your working directory.

To start a brand new modeling workspace, just open a terminal and navigate to a folder where you want your project to live (be careful not to build within the PyAntiGen folder itself) and run:

pyantigen-create MyNewModel

This will automatically scaffold the following project directory:

MyNewModel/
├── .agents/
│   └── skills/          (agent skills, e.g. module generation, ODE conversion)
├── Projects/
│   ├── Example/         (full example: generate, run + Modules/, Engine/)
│   │   ├── Model_generate.py
│   │   ├── Model_run.py
│   │   └── Modules/     (Data, AntimonyGen, Plots, Simulate, Optimize, Experiment, Events)
│   └── MyNewModel/      (same structure, Modules/ pre-populated from Example)
│       ├── Model_generate.py
│       ├── Model_run.py
│       └── Modules/     (Data, AntimonyGen, Plots, Simulate, Optimize, Experiment, Events)
├── antimony_modules/
│   └── __init__.py      (plus Basic/ for the example)
├── data/                (Example experiment CSVs copied for the example)
├── antimony_models/
│   └── Example/         (Example_parameters.csv, Example_InitialConditions.csv, etc.)
├── generated/
│   └── Example/         (reaction dict, rules, etc. after generate)
├── results/
│   └── Example/         (plots from Model_run.py)
├── SBML_models/
└── pyantigen_settings.json   (e.g. archive_with_timestamp: false)

Every project folder under Projects/ has a script called Model_generate.py that is run to generate the model. MODEL_NAME is derived automatically from the enclosing folder name (see AntiGen_paths.py), so being in the right project folder is all that's needed to generate/run the correct project. From MyNewModel/Projects/Example/ run:

python Model_generate.py

This generates the model from the specified files in 'antimony_modules' and writes outputs to antimony_models/Example/ and generated/Example/. This is entirely optional as Model_run.py also calls the constructor functions in Model_generate.py.

To run a simulation or optimization, you may edit the parameters in antimony_models/Example/Example_parameters.csv, derived parameters in antimony_models/Example/Example_manual.txt, and initial conditions in antimony_models/Example/Example_InitialConditions.csv.

Then, run Model_run.py to simulate the Example in Tellurium/RoadRunner:

python Model_run.py --simulate Example

To run optimization examples use the --optimize flag:

python Model_run.py --optimize Example1
python Model_run.py --optimize Example2
python Model_run.py --optimize Example3

Your own model lives under Projects/MyNewModel/. Modify the code for your model in Projects/MyNewModel/Modules/, Projects/MyNewModel/Model_generate.py, and Projects/MyNewModel/Model_run.py. Your problem will also require new modules in antimony_modules/ to define the model.

Running from an IDE (Cursor / VS Code)

The Play button uses whichever Python interpreter is currently selected. If your environment (conda/venv) isn’t loaded, the run may fail with import or path errors.

1. Select the correct interpreter: Ctrl+Shift+P (or Cmd+Shift+P on macOS) → Python: Select Interpreter → choose the environment where you ran pip install -e . (e.g. your conda or venv).
2. Run from project root: Open the project folder (e.g. MyNewModel) as the workspace. Use Run and Debug (or Play on Projects/Example/Model_run.py); the project root is resolved from the script location so antimony_models/Example/, generated/Example/, and results/Example/ resolve correctly.