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Cited by 18 publications
(9 citation statements)
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“…Since all operations mentioned above can be performed in lab within constant biological steps, it is reasonable to assume that the complexity of each operation is O (1). In previous works ([ 10 12 , 14 , 15 , 27 ]), many researchers have used this same approach to analyze the complexity of DNA computing algorithms. Therefore, the same approach is used in this study.…”
Section: Preliminariesmentioning
confidence: 99%
See 1 more Smart Citation
“…Since all operations mentioned above can be performed in lab within constant biological steps, it is reasonable to assume that the complexity of each operation is O (1). In previous works ([ 10 12 , 14 , 15 , 27 ]), many researchers have used this same approach to analyze the complexity of DNA computing algorithms. Therefore, the same approach is used in this study.…”
Section: Preliminariesmentioning
confidence: 99%
“…Nehi and Hamidi [ 13 ] corrected and further improved the DNA model proposed by Yang et al [ 12 ]. Wang et al [ 14 ] solved a traveling salesman problem by a DNA algorithm using the Adleman-Lipton model with an O ( n ) complexity. Based on the Adleman- Lipton model, Wang et al [ 15 ] proposed a new DNA computing algorithm to tackle the capacitated vehicle routing problem with an O ( n 2 ) complexity.…”
Section: Introductionmentioning
confidence: 99%
“…Some typical DNA computing models, such as the Adleman-Lipton model [ 1 , 2 ], the sticker model [ 3 ], the restriction enzyme model [ 4 ], the self-assembly model [ 5 ], the hairpin model [ 6 ], and the surface-based model [ 7 ], have already been established. Based on these models, lots of papers have been written for designing DNA procedures and algorithms to solve various NP-complete problems [ 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 ]. In order to fully understand the power of biological computation, it is worthwhile to try to solve more kinds of computationally-intractable problems with the aid of DNA biologic operations.…”
Section: Introductionmentioning
confidence: 99%
“…DNA biological computing has three advantages: high parallelism, low energy consumption, and large memory capacity. Many research scholars, designing DNA procedures and algorithms, succeed in solving multifarious kinds of complicated NP-complete problems [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21], which promoted development of DNA computing. In order to better apply DNA computing theory to more practical engineering science broad, it is worth trying to solve more intractable problems using the DNA molecular computing.…”
Section: Introductionmentioning
confidence: 99%