A model of cancer cells evolving along a spatial oxygen gradient. This model is a companion to a set of laboratory experiments using MEMIC plates.
If you have questions or want to know more, feel free to contact me!
Click the "start" button in the lower left to start the model. Click "stop" at any time to pause it.
The left box shows a map of oxygen concentration across the world (higher hue values (e.g. blue, purple, magenta) have more oxygen). You can click anywhere on the map to add oxygen there.
The right box shows the phylogenetic depth (distance from original ancestor) of each cell in the world. Higher hue values are farther down the tree (i.e. more generations have elapsed). Black cells are unoccupied. To color based on a different piece of data, click the dropdown menu next to the "start" and "reset" buttons and select a new color rule.
You can adjust the sliders to change parameters. For parameters that change the starting conditions (e.g. initial population size), click the "reset" button after adjusting the parameter before clicking "start."
To apply radiation, click the "Radiation" button. This will simulate applying the number of doses specified by the "Doses" parameter (note that the default is 0, which will apply no radiation) of the size specified by the "Dose size" parameter. Applying radiation will mark cells for death, causing them to die when they next try to divide (choose to color be "Marked for death" to see which cells have been marked for death).
Great! Thanks for letting me know! You can send bugs and feature requests by making an issue on GitHub (or contacting me some other way, if that's easier for you).
Fantastic! Send me an e-mail and we can talk about collaboration.
For full details, see the GitHub repo for this site. In summary, though, I used:
This project is being carried out by the Theory Division at the Cleveland Clinic Lerner Research Institute (views expressed here are my own and do not necessarily reflect the views of Cleveland Clinic or LRI).
I'm a Postdoctoral Fellow at the Cleveland Clinic Lerner Research Institute studying evolution, ecology, and computer science. To learn more about my research, see my website.