Get multi-cell code running on supercomputer

[bcdaniels]

Perhaps we want to run the multi-cell simulations on the ASU supercomputer

[bcdaniels]

This likely breaks down into:

1. Generating a random network representing a single cell. This could be a random threshold network, probably of size ~12-15 (as large as we can easily analyze exactly). Some lightweight code for evaluating threshold network dynamics and their attractors is available here: https://github.com/EnricoBorriello/Threshold_Boolean_Networks Threshold networks can also be defined and analyzed in Neet: see https://github.com/Collective-Logic-Lab/Neet/blob/master/neet/boolean/wtnetwork.py
2. Finding the control kernel for this intracellular network (see Control kernel code #3 )
3. Defining intercellular communication channels: maybe the distance from attractors in one cell influences other nearby cells to be in a similar attractor by (effectively or explicitly) pinning their control nodes
4. Simulating a large 2D tiling of cells that follow the resulting dynamics. Run and visualize this to confirm that having a number of communication channels equal to the control kernel size is enough to get tissue-level coordination.

[bcdaniels]

Note: There is a lot of freedom in how to define cell-cell communication (step 3). Initially, we probably just want to start with the simplest case in which cells try to force their nearby neighbors into a similar attractor.