tumorgrowth - Analysis of the equilibrium phase in immune-controlled tumors to predict best strategies for cancer treatment

Source codes to simulate tumor growth in interaction with immune cell in a size and space structured tumor-immune interaction model and to perform sensitivity analysis of the stationary profile.

• System Requirements
• Organization of the code
• Demo
• License

System requirements

Hardware requirements

The source codes can be runned on a standard computer (in the case of the sensitivity analysis it can be beneficial to have enough cpus in order to be able to exploit the parallel computation )

Software requirements

OS requirements

the source codes are supported by all OS

Python Dependencies

the following python version must be installed to run to source codes:

• python 3.7

the sources codes depend on the following Python packages

• fipy (version 3.3)
• gmsh (version 3.0.6)
• scipy (version 1.5.3)
• matplotlib (version 3.2.1)
• numpy (version 1.19.1)
• pandas (version 1.1.0)
• seaborn (version 0.10.1)
• h5py (version 2.10.0)
• pygpc (version 0.2.7.5)
• cma (version 3.0.3)

The organization of the code

1. Simulations of the evolution problem

• the file 2DTumorImmuneInteraction.py
• the file 2DTumorImmuneInteraction_withRealParameters.py

2. Estimation the model parameters

• the file params_estimation.py

3. The power-dichotomy algorithm

• the file power_dichotomy_algorithm.py
• the file power_dichotomy_algorithm_withRealParameters.py
• the file power_dichotomy_algorithm_withRealParameters_multSimu.py
• the file power_dichotomy_algorithm_withRealParameters_multSimu_matrix.py

4. The global sensitivity analysis of the tumor mass at equilibrium

• the file sensitivity_analysis_withRealParameters.py
• the file sensitivity_analysis_results_postprocessing.py

License

This project is covered under the Creative Commons Zero v1.0 Universal.