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DOI: 10.14569/IJACSA.2016.070316
PDF

Improving DNA Computing Using Evolutionary Techniques

Author 1: Godar J. Ibrahim
Author 2: Tarik A. Rashid
Author 3: Ahmed T. Sadiq

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 3, 2016.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: the field of DNA Computing has attracted many biologists and computer scientists as it has a biological interface, small size and substantial parallelism. DNA computing depends on DNA molecules’ biochemical reactions which they can randomly anneal and they might accidentally cause improper or unattractive computations. This will inspire opportunities to use evolutionary computation via DNA. Evolutionary Computation emphasizes on probabilistic search and optimization methods which are mimicking the organic evolution models. The research work aims at offering a simulated evolutionary DNA computing model which incorporates DNA computing with an evolutionary algorithm. This evolutionary approach provides the likelihood for increasing dimensionality through replacing the typical filtering method by an evolutionary one. Thus, via iteratively increasing and recombination a population of strands, eliminating incorrect solutions from the population, and choosing the best solutions via gel electrophoresis, an optimal or near-optimal solution can be evolved rather than extracted from the initial population.

Keywords: Parallel Computation; DNA Computation Algorithm; Evolutionary DNA Computing Algorithm

Godar J. Ibrahim, Tarik A. Rashid and Ahmed T. Sadiq, “Improving DNA Computing Using Evolutionary Techniques” International Journal of Advanced Computer Science and Applications(IJACSA), 7(3), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070316

@article{Ibrahim2016,
title = {Improving DNA Computing Using Evolutionary Techniques},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070316},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070316},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {3},
author = {Godar J. Ibrahim and Tarik A. Rashid and Ahmed T. Sadiq}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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