This repository contains simulation code and analysis files for the “Bigger is Faster” project. The goal of this work is to study how immune search and first-contact times scale with system size, population size, and spatial organization.
The project combines an Agent-Based Model (ABM) with post-simulation analysis of Initial First Contact Time (IFCT), Mean First Contact Time (MFCT), and scaling relationships.
NetBeansProjects/ Contains the core Agent-Based Model (ABM) and simulation source code. This folder implements the immune-search dynamics and produces raw simulation outputs.
Data/ Stores simulation outputs and processed data used by analysis notebooks.
Main_IFCT_MFCT.ipynb Computes Initial First Contact Time (IFCT) and Mean First Contact Time (MFCT) from simulation outputs for two T cell motion: CRW and Brownian, and for two types of LN and T cell-DC scaling: M^1/2 and M^2/3.
ScalingAll.ipynb Runs scaling analyses across different numbers of searchers and system sizes.
Main_VolM0.5.ipynb (for reproducibility) Examines scaling behavior under volume scaling assumptions (V ~ M^0.5).
PopulationPlot.ipynb Visualization of population-level dynamics and peak behavior after infection for two epitopes.
PopulationPeak.csv Extracted summary statistics from DeBoer paper used in population plots.
.ipynb_checkpoints/ Auto-generated Jupyter notebook checkpoint files.
The ABM is implemented in the NetBeansProjects directory and serves as the primary simulation engine. The model simulates individual searchers (e.g., immune cells) moving within a spatial domain to locate a target.
Key outputs include:
- First contact time (IFCT, MFCT)
- Population-level encounter statistics
These outputs are exported and subsequently analyzed using the Jupyter notebooks in the root directory.
1)MASON libraries. MASON installation guide is available at: https://cs.gmu.edu/~eclab/projects/mason/ 2)JDK 1.8
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Run the ABM simulation from the NetBeansProjects folder to generate raw output data.
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Store simulation outputs in the Data directory or as CSV files.
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Run the analysis notebooks:
- Main_IFCT_MFCT.ipynb
- ScalingAll.ipynb
- PopulationPlot.ipynb
- Initial First Contact Time (IFCT)
- Mean First Contact Time (MFCT)
- Scaling with number of searchers and targets
- Scaling with system size and volume
- Simulations are stochastic; fixed random seeds are recommended.
- Results are aggregated over multiple independent simulation runs.
- Only processed or summarized data is committed to the repository.
Jannatul Ferdous PhD, Computer Science
- .ipynb_checkpoints is auto-generated by Jupyter.
- Some older files are preserved for reproducibility.
- This repository is actively evolving as analysis progresses.