Created by Ming Wu, 07/2012

First one need to have a signaling pathway map in which the activation/inhibition relationship should be clearly defined. Then translate the map into anadjacency matrix, for example:

element (i,j) is 1 if i activates j, -1 if i inhibits j, 0 otherwise.

The matrix can then be input into MATLAB.

Our code for simulating a discrete dynamic model is:

To run the code, one can use:

result01=MK008j(init01,rule01,500,10,6,15,10);

The initial conditions should be specified, 1 for activated, 0 for control, -1 for inhibited, 9 for unknown (will be randomly generated)

The "rule" matrix is the adjacency matrix abovementioned.

one need to also define the population (No. of different simulations: 500 different cells), the number of steps to compute, and if want to plot some of the components.

In many cases the rule matrix is sparse, thus I have another code to generate the matrix by giving only total number of the components, and a three column vector *(i,j,k)* meaning component *i* regulate component *j* in the form of *k (+1/-1)*.