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- W2019499097 abstract "Recently, genetic algorithms (GAs) have received a lot of attention because of theireasy-to-use features for solving many engineering problems. They are capable of locating agood approximate in extremely large search spaces with a reasonable amount ofcomputational effort. In this study, we have developed the DNA algorithms (DNAAs). Thedistinction between GAs and DNAAs originates from the fact that GAs take into account onlyexons whereas on the other hand DNAAs take into account not only exons but also introns. Intron is an intervening sequence that does not have genetic information, and exon is astructural sequence that is used to construct protein. Advanced animals such as humanbeings have a 90% or higher percentage of introns in their DNA sequences, while lowerorganisms have a smaller percentage of introns in their DNA sequences. In the process oftransferring gene information from one generation to another, the correctness of the geneticinformation can be maintained by holding the useless information together with the importantinformation. Living things have developed such genetic redundancy in the process of theirevolution to avoid the unfavorable effects of mutation. We investigated the role of introns andthe performance of the DNAAs by solving a string search problem and a knapsack problemby the DNAAs. As a result, DNAAs showed a firm robustness for a fairly high ratio of mutation.It was also found that more introns were accumulated near exons whose role seems moreimportant than other exons." @default.
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- W2019499097 date "2003-01-01" @default.
- W2019499097 modified "2023-09-27" @default.
- W2019499097 title "Optimization Algorithm using Evolutionary Process of DNA with Introns" @default.
- W2019499097 doi "https://doi.org/10.13031/2013.14054" @default.
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