Gallery

If you would like us to include one of your examples on this page, please send (a) the code with sufficient comments; (b) a description; (c) a link to a youtube video that shows the code running.

More examples on our youtube channel.

	E. coli Nations by Tileli Amimeur(UW), Dec. 2012 Rise of Nations meets gro! In this simulaton, strains of E. coli form nations, each with one leader to control its population. As the cells grow and divide, they get weaker/hungrier. The weaker a cell is, the darker its fluorescence. For the cells to eat and regain their strength, some must lyse (kill themselves) to release food. It is up to the leader cell of each nation to determine how many cells will lyse and when. When the two opposing nations meet, they will fight to kill each other. Only the strongest and largest nation will survive. ... more
	Merge by Eric Klavins(UW), Sept. 2012 In an attempt to see just how many cells gro can reasonably handle in a simulation, we let this one go for a while. The simulation shows bacterial microcolony growth, starting with five cells (although you can initially only see one). Blue represents a nutrient source. Cells emit an enzyme that breaks the nutrient down into a digestable substance, shown in yellow. Greener cells are growing faster and emitting more enzyme. See the code for details. The number of cells in the simulation gets to about 84,000 and took 5 days to simulate. ... more
	Spots by Andrea Samoré (University of Bologna), July 2012 A finite state machine that forms spots. Cells divide and sometimes become leader. Leaders decrease their growth rates, produce GFP and emit two different signals. The short range signal causes the closest neighbors to produce RFP while the long range one inhibits the switching to the leader state of the nearby cells.
	Chemotaxis by Eric Klavins (UW), May 2012 They run when the scent increases. They tumble, and find a new direction to go, when the scent decreases. This example demonstrates the run and tumble functions in gro (new and pretty untested in a5.2).
	Coupled Oscillators by Kevin Oishi (UW), May 2012 This example is inspired by the paper from Hasty's group on synchronized oscillators in synthetic bacteria. They used a simple network of transcription factors along with quorum sensing to achieve a self-replicating coupled oscillator. Among many innovations is their use of a microfluidic chemostat, which this example mimics using gro's chemostat mode. Note that the example code is at a high level of specification, describing mainly the logic of how coupled oscillators work, and not describing the detailed bio-molecular interactions. You are welcome to write a more detailed version of the system, gro let's you use whatever level ob abstraction you like. ... more
	Morphogenesis by Eric Klavins (UW), April 2012 This example, which is from our recent submission on gro, produces micro-colonies with three bands of color. The initial cell divides until there are four cells. Two of them become senders of different signals. These two cells also spawn receivers. If the receivers get both signals, they grow, producing a blob of receivers between the two senders. Eventually the senders switch into a new state, where they grow for a certain amount of time before stopping. The example uses finite state machines coded in gro to control the behavior. Check out the code to see the details, and try making your own state machine! ... more
	Population Control by Shelly Jang (UW), April 2012 In their 2004 paper, You, Cox, Weiss and Arnold showed they could use quorum sensing and programmed cell-death to regulate the density of a population. Here is demonstration of the idea using gro's chemostat mode. The cells constitutively emit a quorum sensing signal. If they sense too much of the signal, they increase the probability with which they pop themselves. The movie shows they effect of tuning the (stochastic) rate at which they pop given that their local concentration of quorum sensing molecule is above a threshold. ... more
	Edge Detection by Rehana Rodrigues, Kevin Oishi (UW), Dec. 2011 This example is derived from the one that won Rehana Rodrigues the "best simulation" award in UW's 2011 Introduction to Synthetic Biology contest. As the colony grows, cells randomly initiate waves of signaling. As the signal propogates past a particular cell, that cell can tell if it is near an edge or in the middle of the colony based on the concentration of signal just after the wave passes. The detection of the edge condition is filtered by expression or degrading rfp, so that the edge state is remains current even as the cells are moved around by growth. ... more

For more examples see our youtube channel, or download gro!

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