Cellular automata simulation of topological effects on the dynamics of feed-forward motifs

Table 3 Linear dependence of the overall rate of feed-forward motifs on the number of motive nodes

Series	N	Iterations range	Regression	R²	SD %
FFA-50	3–9	804 – 2160	219.00 N + 227.14	0.9796	4.14
FFB-50	4–10	1735 – 3736	320.18 N + 483.46	0.9966	1.43
FFC-50	4–10	2043 – 4530	402.36 N + 481.36	0.9980	1.71
FFD-50	4–10	1375 – 3428	329.93 N + 148.50	0.9939	2.38
FFE-50	4–10	1080 – 2247	202.93 N + 258.64	0.9874	2.62
FFF-50	4–10	785 – 1574	133.36 N + 235.07	0.9981	1.70
FFG-50	4–10	1955 – 4104	365.61 N + 395.89	0.9900	2.78
FFA-100	3–9	2966 – 8444	920.75 N + 187.50	0.9996	0.31
FFB-100	4–10	4187 – 9044	800.93 N + 998.07	0.9994	0.29
FFC-100	4–10	4542 – 10565	993.71 N + 556.00	0.9990	0.25
FFD-100	4–10	3291 – 8067	802.64 N + 89.357	0.9993	0.34
FFE-100	4–10	3505 – 7599	683.57 N + 766.14	0.9994	0.33
FFF-100	4–10	2408 – 4927	418.21 N + 705.07	0.9991	0.50
FFG-100	4–10	2721 – 5086	397.61 N + 1121.8	0.9991	0.42

The overall rate is measured by the number of iterations needed for 50% and 100% conversion of the source substrate into the target product. Seven series (Fig. 3) of feed-forward motifs with different topology, constant number of source cells, N = 500, and constant lattice density, D = 3.6%, are studied.

ISSN: 1754-1611