Agent-based models predict emergent behavior of heterogeneous cell populations in dynamic microenvironments: POPULATION HETEROGENEITY (5/5)
2021
- 478Usage
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Usage478
- Downloads405
- Views73
Dataset Description
Data and results for `POPULATION HETEROGENEITY` simulations. Simulations of all possible combinations of four populations (X, A, B, C) under colony and tissue context with different levels of parameter heterogeneity (0, 0.1, 0.2, 0.3, 0.4, and 0.5). For tissue context, the healthy cell populations also varies parameter heterogeneity independent of the cancerous cell populations. 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 data.param folder contains .tar.xz compressed replicate sets for .PARAM output. The results folder contains .pkl files of data parsed into arrays. Simulations are labeled as: [context]_[populations]_[population heterogeneity]_[background heterogeneity] - [context] - C = colony context, cancerous cell populations only - C...
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