pred_prey_rules1
Science Score: 18.0%
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✓CITATION.cff file
Found CITATION.cff file -
○codemeta.json file
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○.zenodo.json file
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○DOI references
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○Academic publication links
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○Scientific vocabulary similarity
Low similarity (3.6%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: rheiland
- Language: C++
- Default Branch: main
- Size: 5.1 MB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
This model attempts to model a type of predator-prey where, if the prey clump together, the predator is unable to eat them. This is accomplished by detecting how many (spring) attachments there are to each prey and, if there are greater than some threshold, transform the "prey" cell type into "preybig". (Note the values for "attachment rate" in Cell Types|Mechanics for the different cell types). A single Rule transforms "prey" to "preybig" if the number of attachments (Custom Data of cell types) exceeds a threshold.
Note that it is necessary to save the number of spring attachments into a custom data variable in custom.cpp (since that value is not exposed in the rules (yet)).
void phenotype_function( Cell* pCell, Phenotype& phenotype, double dt )
{
pCell->custom_data["num_attached"] = pCell->state.spring_attachments.size();
return;
}
See the 'images' folder for some output screenshots.
Owner
- Name: Randy Heiland
- Login: rheiland
- Kind: user
- Location: Bloomington, IN
- Company: Indiana University
- Website: https://rheiland.github.io/
- Repositories: 210
- Profile: https://github.com/rheiland
Research Associate in @MathCancer Lab. Intelligent Systems Engineering, IU.
Citation (CITATION.txt)
If you use PhysiCell in your project, please cite PhysiCell and the version
number, such as below:
We implemented and solved the model using PhysiCell (Version 1.13.1) [1].
[1] A Ghaffarizadeh, R Heiland, SH Friedman, SM Mumenthaler, and P Macklin,
PhysiCell: an Open Source Physics-Based Cell Simulator for Multicellu-
lar Systems, PLoS Comput. Biol. 14(2): e1005991, 2018
DOI: 10.1371/journal.pcbi.1005991
Because PhysiCell extensively uses BioFVM, we suggest you also cite BioFVM
as below:
We implemented and solved the model using PhysiCell (Version 1.13.1) [1],
with BioFVM [2] to solve the transport equations.
[1] A Ghaffarizadeh, R Heiland, SH Friedman, SM Mumenthaler, and P Macklin,
PhysiCell: an Open Source Physics-Based Cell Simulator for Multicellu-
lar Systems, PLoS Comput. Biol. 14(2): e1005991, 2018
DOI: 10.1371/journal.pcbi.1005991
[2] A Ghaffarizadeh, SH Friedman, and P Macklin, BioFVM: an efficient para-
llelized diffusive transport solver for 3-D biological simulations,
Bioinformatics 32(8): 1256-8, 2016. DOI: 10.1093/bioinformatics/btv730
If you use PhysiBoSS, please cite:
G. Letort, A. Montagud, G. Stoll, R. Heiland, E. Barillot, P. Macklin,
A. Zinovyev, and L. Calzone. PhysiBoSS: a multi-scale agent based
modelling framework integrating physical dimension and cell signalling.
Bioinformatics 35(7):1188-96, 2019. DOI: 10.1093/bioinformatics/bty766.
If you use libRoadrunner, please cite:
Endre T. Somogyi, Jean-Marie Bouteiller, James A. Glazier, Matthias
König, J. Kyle Medley, Maciej H. Swat, Herbert M. Sauro, libRoadRunner:
a high performance SBML simulation and analysis library,
Bioinformatics 31(20): 3315–21, 2015: DOI: 10.1093/bioinformatics/btv363