Construction of codes for DNA computing by the greedy algorithm

Bennenni, Nabil; Guenda, Kenza; Gulliver, Aaron

doi:10.1145/2768577.2768583

Cited by 4 publications

(2 citation statements)

References 6 publications

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“…In the process of removing the worst code at each stage it may remove a potentially good code at earlier stages and may not remove bad code at the later stages. So it doesn't always produce the best optimal result [54]. Example 8.…”

Section: Various Approaches For the Dna Codes Constructionsmentioning

confidence: 99%

The Art of DNA Strings: Sixteen Years of DNA Coding Theory

Limbachiya,

Rao,

Gupta

2016

Preprint

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The idea of computing with DNA was given by Tom Head in 1987, however in 1994 in a seminal paper, the actual successful experiment for DNA computing was performed by Adleman. The heart of the DNA computing is the DNA hybridization, however, it is also the source of errors. Thus the success of the DNA computing depends on the error control techniques. The classical coding theory techniques have provided foundation for the current information and communication technology (ICT). Thus it is natural to expect that coding theory will be the foundational subject for the DNA computing paradigm. For the successful experiments with DNA computing usually we design DNA strings which are sufficiently dissimilar. This leads to the construction of a large set of DNA strings which satisfy certain combinatorial and thermodynamic constraints. Over the last 16 years, many approaches such as combinatorial, algebraic, computational have been used to construct such DNA strings. In this work, we survey this interesting area of DNA coding theory by providing key ideas of the area and current known results.

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Section: Various Approaches For the Dna Codes Constructionsmentioning

confidence: 99%

The Art of DNA Strings: Sixteen Years of DNA Coding Theory

Limbachiya,

Rao,

Gupta

2016

Preprint

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“…This was inspired by the fact that, as the major genetic material in life, DNA encodes and processes an enormous amount of genetic information. DNA computing, proposed by Adleman [11] in 1994, may potentially provide a promising method for solving complex optimization problems because its parallel computing may efficiently search through a large space for potential solutions [12]. However, using DNA as computing hardware [13] still faces many challenges.…”

Section: Introductionmentioning

confidence: 99%

A Genetic Algorithm Using Triplet Nucleotide Encoding and DNA Reproduction Operations for Unconstrained Optimization Problems

Zang

Zhang

et al. 2017

Algorithms

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As one of the evolutionary heuristics methods, genetic algorithms (GAs) have shown a promising ability to solve complex optimization problems. However, existing GAs still have difficulties in finding the global optimum and avoiding premature convergence. To further improve the search efficiency and convergence rate of evolution algorithms, inspired by the mechanism of biological DNA genetic information and evolution, we present a new genetic algorithm, called GA-TNE+DRO, which uses a novel triplet nucleotide coding scheme to encode potential solutions and a set of new genetic operators to search for globally optimal solutions. The coding scheme represents potential solutions as a sequence of triplet nucleotides and the DNA reproduction operations mimic the DNA reproduction process more vividly than existing DNA-GAs. We compared our algorithm with several existing GA and DNA-based GA algorithms using a benchmark of eight unconstrained optimization functions. Our experimental results show that the proposed algorithm can converge to solutions much closer to the global optimal solutions in a much lower number of iterations than the existing algorithms. A complexity analysis also shows that our algorithm is computationally more efficient than the existing algorithms.

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Effective decoders for DNA codes

Houghten¹,

Banik²

2022

Biosystems

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Construction of codes for DNA computing by the greedy algorithm

Cited by 4 publications

References 6 publications

The Art of DNA Strings: Sixteen Years of DNA Coding Theory

The Art of DNA Strings: Sixteen Years of DNA Coding Theory

A Genetic Algorithm Using Triplet Nucleotide Encoding and DNA Reproduction Operations for Unconstrained Optimization Problems

Effective decoders for DNA codes

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