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Data · dataset · 2021

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

Listed in Teesside University Research Data Repository

Data and results for `GROWTH CONTEXT` simulations.

Description

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.

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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

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Teesside University Research Data Repositoryoai:data.mendeley.com/mmnh9hsv5y.111 d agoJSON v1
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