Skip to content

Cell Population Dynamics in Continuous Time Domain

Description

This project explores the mathematical modeling of cell population dynamics using the McKendrick–Von Foerster equation. The focus is on understanding the time-independent case where cell division and death rates depend on the cell's age.

Learning Outcomes

  • Understand the McKendrick–Von Foerster equation for population dynamics.
  • Apply separation of variables to solve partial differential equations.
  • Derive and interpret the Euler-Lotka equation for population growth rates.

Requirements

Academic

  • Basic knowledge of differential equations and mathematical modeling.
  • Familiarity with population dynamics concepts.

System

  • Python 3.11 or newer
  • MkDocs for documentation generation
  • Miniconda (recommended for managing dependencies)

Getting Started

  1. Clone the repository and navigate to the project directory.
  2. Set up a virtual environment and install the required dependencies: 
    conda create --name cell-population-dynamics python=3.11
conda activate cell-population-dynamics
pip install -r requirements.txt

Project Structure

.
├── docs
├── notebooks
├── src
│   ├── __init__.py
|   ├── cells_manager.py   # Cell population manager
|   ├── plots.py           # Plotting functions
|   ├── run.py             # Main script to run the simulation
|   ├── simulation.py      # Core simulation logic
│   └── utils.py           # Utility functions
├── mkdocs.yml
├── requirements.txt
└── README.md

MkDocs Documentation

To generate local documentation, run the following command:

mkdocs serve

License

This project is licensed under the BSD-3-Clause license