1. Introduction

To account for cell movement, PhysiCell includes a set of parameters that govern speed and direction of cell motility. The biased, random motility of cells is determined by the following equation:

where b is the level of bias in movement (migration bias), ξ is a random unit vector of length 1, and d_bias is the direction of the bias.

2. Motility Parameters

2.1. is_motile

is motile is a Boolean variable that controls whether or not cells move in the simulation.

2.2. Persistence Time

Persistence time is the amount of time in minutes that a cell moves in its current direction and speed before choosing a new motility vector to follow.

2.3. Migration Speed

Migration speed is the speed at which the cells move in μ m/min.

2.4. Migration Bias

Migration bias impacts the direction that a cell moves. It falls between 0 and 1, where 0 represents the Brownian movement, and 1 represents movement in the direction defined by the migration bias direction variable. The migration bias parameter determines to what extent cells move purely in a given direction.

3. App Instructions

The training app on NanoHUB is called "PhysiCell: biased random migration demonstrator." After launching the tool, a window with 6 tabs appears. The first tab is "About" section which you are in it. The second tab, called Config Basics, sets simulation parameters for plot size, the amount of time the simulation covers, and how often to plot cells and substrates. Microenvironment tab is dedicated to set parameters for BioFVM. The fourth tab, User Params, sets is motile, persistence time, migration speed, and migration bias. The fifth tab, Cell Plots, shows the simulation frames for cell movement. Finally, the sixth tab, Substrate Plots, shows the simulation frames for the chemical environment of the simulation along with the paths cells take as they move.

Researchers should cite this work as follows:

• Ghaffarizadeh A, Heiland R, Friedman SH, Mumenthaler SM, Macklin P (2018) PhysiCell: An open source physics-based cell simulator for 3-D multicellular systems. PLoS Comput Biol 14(2): e1005991.
  https://doi.org/10.1371/journal.pcbi.1005991

  Heiland R, Mishler D, Zhang T, Bower E, Macklin P (2019, in preparation) Xml2jupyter: Mapping parameters between XML and Jupyter widgets. J Open Source Software.

  Ghaffarizadeh A, Friedman SH, Macklin P (2016) BioFVM: an efficient, parallelized diffusive transport solver for 3-D biological simulations. Bioinformatics 32(8):1256-8. https://doi.org/10.1093/bioinformatics/btv73

• Furkan Kurtoglu, Aneequa Sundus, Kali Nicole Konstantinopoulos, Drew Willis, Mary Chen, Randy Heiland, Paul Macklin (2020), "Motility Training App for PhysiCell," https://nanohub.org/resources/trmotility. (DOI: 10.21981/EJ4A-H993).

  BibTex | EndNote

1. agent-based models
2. BioFVM
3. cell motility
4. education
5. Jupyter notebooks
6. Motility
7. nano/bio
8. NanoBio Node at Indiana
9. PhysiCell
10. PhysiCell training
11. xml2jupyter