This repository contains the code, data, and documentation for the mathematical modeling work presented in:
Auther names: Mark Y Xiang 1,2,3,†, Haripriya Vaidehi Narayanan 1,2,†, Vaibhava Kesarwani 1, Tiffany Wang 1, Alexander Hoffmann 1,2,*
Affiliations: 1. Institute for Quantitative and Computational Biosciences, 2. Department of Microbiology, Immunology, and Molecular Genetics, 3. 3Bioinformatics Interdepartmental Program, University of California Los Angeles; Los Angeles, California 90095, USA, † These authors contributed equally to this work, * Corresponding author. Email: [email protected].
This study investigates the fundamental question of how epigenetic heterogeneity of B-cells affects the genetic evolution of high affinity antibody required for effective immune responses.
We developed a probabilistic, agent-based model to simulate:
- Affinity-based selection in the light zone
- Proliferation and somatic hypermutation in the dark zone
- The impact of fragility and stability of the epigenetic cell state on affinity maturation
root
├── Simulation_code
├── Model_simulation
└── Experiments
├── ELISA
└── Flow
└── Raw_readoutgit clone https://github.com/signalingsystemslab/GC_evolution_model.git
cd GC_evolution_modelIt is recommended to use a virtual environment
python3 - m venv venv
source venv/bin/activate
pip install - r Simulation_code/requirements.txtGenerate simulations regarding Figure 1 results
bash Model_simulation/Simulation_Fig1.shGenerate simulations regarding Figure 2 and 3 results
bash Model_simulation/Simulation_Fig23.shGenerate simulations regarding Figure 4 results
bash Model_simulation/Simulation_Fig4.shWe thank the members of the Hoffmann lab for valuable discussions and feedback on the manuscript, particularly Helen Huang, Chengyuan Li, Xiaolu Guo, Patrick Yuan, and Joseph Schirle as well as Roy Wollman and Eric Deeds for critical feedback and/or review of our manuscript.
For questions or suggestions, feel free to open an issue or contact