Agent-based models predict emergent behavior of heterogeneous cell populations in dynamic microenvironments: GROWTH CONTEXT

Published: 20 July 2021| Version 1 | DOI: 10.17632/mmnh9hsv5y.1
Contributor:
Jessica Yu

Description

Data and results for `GROWTH CONTEXT` simulations. Simulations of all possible combinations of four populations (X, A, B, C) under colony and tissue context. 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. Simulations are labeled as: [context]_[populations] - [context] - C = colony context, cancerous cell populations only - CH = tissue context, cancerous cell populations and healthy cells - [populations] - X = cancerous cell population with basal parameters - A = cancerous cell population with max_height x 1.5 - B = cancerous cell population with meta_pref x 1.5 - C = cancerous cell population with migra_threshold x 0.5

Files

Steps to reproduce

Simulations generated using ARCADE v2.2 (available at https://github.com/bagherilab/ARCADE) using the following setup files: - GROWTH_CONTEXT_C.xml - GROWTH_CONTEXT_CH.xml All setup files are available at https://github.com/bagherilab/arcade_emergent_behavior.

Categories

Computational Biology

Licence