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Table 4 Minimum sequence length and run time required in the computation of state transition matrices for a given accuracy, measured by Norm 2

From: Stochastic Boolean networks: An efficient approach to modeling gene regulatory networks

n N SBN (Norm 2 = 0.04) SBN (Norm 2 = 0.02) Method[22]
   Sequence length Std. deviation Avg. time (s) Std. deviation Sequence length Std. deviation Avg. time (s) Std. deviation Avg. time (s) Std. deviation
2 6 150 46 0.006324 0.003315 480 84 0.013655 0.007568 0.005468 0.004100
3 8 460 89 0.019755 0.008942 800 122 0.017634 0.009536 0.011655 0.007036
4 16 520 109 0.024337 0.009108 1120 84 0.043844 0.010102 0.031391 0.009388
5 32 860 134 0.052112 0.017356 1540 182 0.118927 0.036943 0.157794 0.020922
6 64 1240 270 0.209416 0.030298 2460 241 0.548156 0.042366 0.532971 0.037483
7 128 1340 167 0.453192 0.048960 3680 239 1.208252 0.060325 2.441066 0.163347
8 256 2260 378 2.030217 0.171125 5480 335 4.110083 0.326308 9.368184 0.863544
9 512 2580 303 4.751360 0.421918 6820 471 12.81050 2.061854 39. 26049 4.208466
10 1024 3920 923 16.06112 4.252810 8760 1135 38.60258 6.377620 201.5433 10.90932
11 2048 4700 836 40.44380 5.742303 10400 1140 95.40610 7.547263 811.6358 15.88395
12 4096 5660 882 118.3426 9.031772 13000 1000 286.5043 12.37633 3501.744 86.66141
  1. (no perturbation, n: the number of genes, and N: the number of BNs). The results are obtained from five randomly generated networks, so the standard deviations of the minimum sequence length and run time are also shown.