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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.