Agent-based models predict emergent behavior of heterogeneous cell populations in dynamic microenvironments: MODULE COMPLEXITY

Published: 21 July 2021| Version 1 | DOI: 10.17632/7w2cdsrt87.1
Jessica Yu


Data and results for `MODULE COMPLEXITY` simulations. Simulations of population with different combinations of metabolism and signaling module complexities (random, simple, medium, and complex). Each condition is run for 15 days (21600 ticks) with 20 replicates (random seeds 0 - 19). Cells are introduced to the center of the constant source environment after a 1 day delay. Snapshots are taken every 0.5 days (720 ticks). The data folder contains .tar.xz compressed replicate sets. The results folder contains .pkl files of data parsed into arrays (only for the full model rule simulations). Simulations are labeled as: [case]_[metabolism]_[signaling] - [case] - simulations full model rules do not have this label - both = fixed state with both modules - metabolism = fixed state with only metabolism module - signaling = fixed state with only signaling module - [metabolism] - R = random metabolism module - S = simple metabolism module - M = medium metabolism module - C = complex metabolism module - [signaling] - R = random signaling module - S = simple signaling module - M = medium signaling module - C = complex signaling module


Steps to reproduce

Simulations generated using ARCADE v2.2 (available at using the following setup files: - MODULE_COMPLEXITY.xml - MODULE_COMPLEXITY_both.xml * - MODULE_COMPLEXITY_metabolism.xml * - MODULE_COMPLEXITY_signaling.xml * Simulations with * used modified code; see article for details. All setup files are available at


Computational Biology