Abstract
DNA computing and coding have good application prospects in data storage, data computing, data encryption and other fields. Meanwhile, it is very important to design a set of DNA coding set that meets a variety of constraints in today's research. The purpose of DNA coding is to find as many qualified code sets as possible under given conditions or to keep each DNA code in the DNA code set as far as possible from other codes. The former is used in this paper. The algorithm uses the Bloch system to initialize the DNA coding population, and uses the Ant Colony Algorithm to find the optimal DNA coding. At the same time, crossover and mutation operations are added to make the generated population more random and diverse. Experimental results show that the number of code sets obtained by this algorithm under certain specific conditions is better than the number of code sets obtained by other algorithms.
Highlights
D NA computing was proposed by Head T [1] in 1987
Deng et al [8] proposed an improved hybrid coding method of variablelength run-length limited (VL-RLL) coding and low-density parity-check (LDPC) coding based on DNA based data storage technology
The basic ant colony algorithm will calculate the distance of all DNA codes when calculating the ant transfer strategy, and select the code with the highest probability to add to the candidate code, but this operation will greatly improve the computing time of the computer
Summary
D NA computing was proposed by Head T [1] in 1987. Adleman [2] proved head’s conjecture with an innovative method in 1994. The experimental results show that the hybrid coding method proposed in this paper has better performance than the current traditional DNA data storage technology. We design an ant colony algorithm based on Bloch Sphere to find the coding set under various constraints. In this method, Bloch coordinates are regarded as three gene sequences, and each chromosome is composed of three genes. The value range of n chromosomes generated by formula (4) is between [-1,1], which does not meet the requirements of our DNA coding set, so we need to perform space transformation to convert n chromosomes into our own In the required space, the formula for solution space conversion is as follows: Xijx = round. After the transformation of the above solution space formula, a set of DNA codes in the range [0, 4] can be obtained
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