K-Means Multi-Verse Optimizer (KMVO) Algorithm to Construct DNA Storage Codes

Cao, Ben; Zhao, Sue; Xue, L.; Wang, Bin

doi:10.1109/access.2020.2970838

Cited by 22 publications

(18 citation statements)

References 51 publications

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“…The authors in [9] described the construction of the constraint code for DNA storage systems, taking into account the maximum repetition length and the balance between AT and GC pairs. An improved algorithm was proposed in [10] to store information more efficiently considering Hamming distance and run-length constraints. The architecture in [11] implemented an efficient coding technique to limit the length of repeated occurrences of the same base that are difficult to sequence.…”

Section: Introductionmentioning

confidence: 99%

Notice of Violation of IEEE Publication Principles: Construction of GC-Balanced DNA With Deletion/Insertion/Mutation Error Correction for DNA Storage System

Xue

Lau

2020

IEEE Access

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Synthetic deoxyribonucleic acid (DNA) is a good medium for storing digital data for a long period due to its achievable high data storage density and outstanding longevity. However, synthesizing and sequencing DNA sequences in a DNA storage system are prone to a wide variety of errors, including insertion, deletion and mutation errors a. At the same time, it is known that DNA sequences with 50% GC content are less susceptible to errors. This paper presents the construction of a GC-balanced DNA sequence with error correction capability. A systematic single insertion/deletion/substitution error correction code is first proposed and then used to design a GC-balanced scheme for synthesizing DNA sequences. With the proposed method, DNA sequences with exactly 50% GC content are constructed. Such DNA sequences not only have the maximum endurance to errors, but are able to correct both insertion/deletion and mutation of the nucleotide bases. The decoding procedures for the sequences are described and can readily be used in practice. Simulation results show that the proposed GC-balanced DNA sequences can correct base errors adequately. a Mutation errors occurring in DNA data storage systems are equivalent to substitution errors in conventional data storage and digital communication systems. In this paper, mutation errors and substitution errors may be used interchangeably.

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Section: Introductionmentioning

confidence: 99%

Notice of Violation of IEEE Publication Principles: Construction of GC-Balanced DNA With Deletion/Insertion/Mutation Error Correction for DNA Storage System

Xue

Lau

2020

IEEE Access

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“…Table 4 and table 5 are the maximum number of sets obtained by each algorithm of A RC 4 (n, d) and A GC,RC 4 (n, d, w) respectively. The value range of coding length is [4,13], and the range of distance D is [3, n]. A in each column represents the previous experimental results (the letter in the upper right corner of each result represents the method used, see Table 3 for details), B represents the experimental results of this paper.…”

Section: B Experimental Resultsmentioning

confidence: 99%

“…(12,6,6), are far from the existing experimental results, and some results are equal to the previous results, such as A RC 4 (9, 7) = 8. There are also some cases where the number of codes in the new algorithm is larger than that of the existing codes in the range of coding length [4,13]…”

Section: B Experimental Resultsmentioning

confidence: 99%

“…According to the constraints mentioned above, many researchers and scholars are studying DNA coding ensemble now. Cao et al [13] proposed a K-means multiple optimization algorithm (KMVO) based on Hamming distance constraint, GC constraint and other constraints. The algorithm can find better coding boundary than the previous multiple optimization algorithms (MVO).…”

Section: Introductionmentioning

confidence: 99%

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DNA Design Based on Improved Ant Colony Optimization Algorithm With Bloch Sphere

2021

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DNA computing and coding have good prospects in data storage, data computing, data encryption and other fields. At the same time, it is very important to design a set of DNA coding set that meets a variety of constraints in today's research. DNA code aims to find as many qualified DNA data sets as possible under the same constraints. In this paper, we design an ant colony algorithm based on Bloch Sphere. In this algorithm, Bloch system is used to initialize the DNA coding population, and ant colony algorithm is used to find the best DNA coding. Meanwhile, crossover and mutation operations are added to make the generated population more random. Experimental results show that the coding set found by the algorithm is better than other coding sets.

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“…The results of the mean and standard deviation only show the overall performance of an algorithm, while statistical tests consider whether the results are statistically significant. Therefore, we used the non-parametric Wilcoxon rank-sum test [51] at a 5% significance level [52] to investigate the significant difference between our algorithm results. When P > 0.05 showed that it has significant differences and statistical advantage.…”

Section: Wilcoxon Rank-sum Testmentioning

confidence: 99%

An Intelligent Optimization Algorithm for Constructing a DNA Storage Code: NOL-HHO

Yin

Cao

et al. 2020

IJMS

Self Cite

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The high density, large capacity, and long-term stability of DNA molecules make them an emerging storage medium that is especially suitable for the long-term storage of large datasets. The DNA sequences used in storage need to consider relevant constraints to avoid nonspecific hybridization reactions, such as the No-runlength constraint, GC-content, and the Hamming distance. In this work, a new nonlinear control parameter strategy and a random opposition-based learning strategy were used to improve the Harris hawks optimization algorithm (for the improved algorithm NOL-HHO) in order to prevent it from falling into local optima. Experimental testing was performed on 23 widely used benchmark functions, and the proposed algorithm was used to obtain better coding lower bounds for DNA storage. The results show that our algorithm can better maintain a smooth transition between exploration and exploitation and has stronger global exploration capabilities as compared with other algorithms. At the same time, the improvement of the lower bound directly affects the storage capacity and code rate, which promotes the further development of DNA storage technology.

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K-Means Multi-Verse Optimizer (KMVO) Algorithm to Construct DNA Storage Codes

Cited by 22 publications

References 51 publications

Notice of Violation of IEEE Publication Principles: Construction of GC-Balanced DNA With Deletion/Insertion/Mutation Error Correction for DNA Storage System

Notice of Violation of IEEE Publication Principles: Construction of GC-Balanced DNA With Deletion/Insertion/Mutation Error Correction for DNA Storage System

DNA Design Based on Improved Ant Colony Optimization Algorithm With Bloch Sphere

An Intelligent Optimization Algorithm for Constructing a DNA Storage Code: NOL-HHO

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