Parameter Sensitivity in Tumor Models: Dataset from PhysiCell Simulations

This dataset contains simulation outputs generated by applying multiplicative perturbations to parameters in two PhysiCell models. The perturbations, applied at levels of ±1%, ±5%, ±10%, and ±20% around reference parameter values, were repeated across 50 replicates for each condition. The resulting simulations provide comprehensive data on population dynamics, spatial distributions, and biological processes over a 5-day period.

Model 1: Hypoxia Progression in a Metastatic Tumor (Table_ex1)

• Raw Population Data: Records the population of each cell type over time.
• Summary of Population Data: Includes the area under the curve (AUC) for cell populations over the simulation period.
• Raw Spatial Data: Captures the distance of cells from the computational center, offering insights into spatial distribution and invasion patterns.
• Summary of Spatial Data: Pooled cell distances from the center and calculated Wasserstein distances between tumor and motile tumor cell populations.

Model 3: Tumor-Immune Dynamics (Table_ex3)

• Raw Population Data: Tracks the population dynamics of tumor cells, macrophages, and CD8 T cells over time.
• Summary of Population Data: Includes the AUC for each cell population over the simulation period.
• Raw Spatial Data: Records the distances of cells from the computational center to analyze invasion and spatial distribution patterns.
• Summary of Spatial Data: Pooled cell distances from the center and calculated Wasserstein distances between tumor cells and CD8 T cells, and tumor cells and macrophages.

More details and access instructions are available at: PhysiCell-Models GitHub Repository.