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. 2023 Feb 19;26(3):106231. doi: 10.1016/j.isci.2023.106231

Table 3.

GCNSA compares the number of encodings dataset that satisfy the GC content, no-runlength, and Hamming distance constraints with different baseline methods

n = 6, d = 3 n = 6, d = 4 n = 7, d = 3 n = 7, d = 4 n = 7, d = 5 n = 8, d = 3 n = 8, d = 4 n = 8, d = 5 n = 8, d = 6
BC29 95.16% 67.86% 100.0% 100.0% 100.0% 78.09% 89.84% 80.00% 50.00%
EP30 96.77% 100.0% 88.81% 88.46% 84.21% 84.02% 85.94% 82.22% 70.00%
NHO51 88.71% 82.14% 84.62% 80.77% 73.68% 87.37% 84.38% 77.78% 65.00%
KMVO49 90.32% 82.14% 88.81% 86.54% 89.47% 82.22% 73.44% 71.11% 65.00%
BMVO52 93.55% 85.71% 87.41% 84.62% 89.47% 83.51% 82.81% 77.78% 70.00%
GCN 93.55% 85.71% 93.01% 90.38% 94.74% 95.36% 91.41% 86.67% 95.00%
GCNSA 100.0% 100.0% 96.50% 94.23% 100.0% 99.74% 100.0% 100.0% 100.0%

The percentage in the table is the ratio of the current method to the optimal number. and the bold represents the optimal value under the current coding length (n) and Hamming distance value (d).