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Table 3 Distribution of candidate sequences generated by the P-ER2 computational protocol

From: In-silico design of computational nucleic acids for molecular information processing

  Input state     Input state     
A 1 0 1 0    A 1 0 1 0   
B 1 1 0 0    B 1 1 0 0   
   Output state   Total Success   Output state Total Success
   (LG-B)   candidates rate   (LG-T) candidates rate
  1 0 0 0 1517 5.4%   0 0 0 1 1006 42.8%
  1 0 0 1 326 26.0%   0 0 1 0 3276 26.5%
  1 0 1 0 127 11.0%   0 0 1 1 786 1.7%
  1 1 0 1 167 0.0%   0 1 0 0 3348 29.3%
  1 1 0 0 10004 8.9%   0 1 0 1 1194 3.9%
  1 1 0 1 7470 2.7%   0 1 1 0 200 18.5%
  1 1 1 0 1850 16.6%   0 1 1 1 200 0.0%
   Constants   28539 -   Constants 39990 -
  1. Distribution of candidate sequence generated by the revised computational protocol (P-ER2) in Table 1, classified according to the type of binary logic operator LG-B (depicted in the bottom half of Table 2) and LG-T (depicted in the top-half of Table 2). For LG-B, it is mandatory for the operator to be active, whenever the two inputs are present. Accordingly, for LG-T, The initial start of the design requires the molecule to remain inactive despite the presence of both inputs (i.e., reverse scenario of LG-B). The candidates generated at each run will then undergo a filter cascade (cf. Table 4). The total candidates column represents the total number of candidates generated by the protocol. The percentage of sequences that passed the cascade is listed in the success rate column.