1. In this presentation, we developed an algorithm for describing the bending structure of myxobacteria. In this algorithm, cell structure is presented by key nodes and connection bonds. System potential energy includes stretching energy and bonding energy. Cell collision is implemented by a MC algorithm. Further development is still in progress.

2. Algorithm for bending structure of Myxobacteria Nan Chen and Yilin Wu

3. Key nodes are used to describe the flexibility of myxobacteria Algorithm Description

4. Stretching Energy Bending Energy Stretching and bending Energy

5. MonteCarlo Algorithm for cells movement Algorithm for one MC step For I = 1 to n-1 Randomly choose one node Randomly choose one moving direction and distance If (Collision happen) Not accepted and next Calculate energy change Calculate acceptance probability if (Accpted) update configuration

6. Turn to this direction Algorithm for cells collision

7. Why we choose MC algorithm, not deterministic algorithm (MD)? Advantage MC Algorithm could easily handle very complicated cell configurations MC algorithm allows cells still to move when cell lock happens Disadvantage MC algorithm is slower than deterministic algorithm

8. Algorithm of Adding slime field The 2D surface was already mapped into 2D lattice. I create a slime field on this lattice; In every time step, each cell deposits slimes by adding 1 slime to each lattice site occupied by the A-end; In every time step, before moving a cell, specify the position O(x, y) of the its S-end or head; The cell “ searches ” the slime field in front of S- end. Sum all the slimes in the N areas (as shown in next slide) respectively, denoting by S(i), i= 1, … N; The probability to choose one of the N directions (as shown in next slide) is proportional to the slime concentrations in the N areas:

9. Slime distribution f(x) -90 90 X Y X’ Y’ Moving direction Search area S end A end 1 2 3 n N-1

10. Summary ● Further work to integrate both the cell-cell interactions and slime field.