Xinmei Peng, Xuedong Zheng, Bin Wang, Changjun Zhou, Qiang Zhang
{"title":"DNA编码序列设计的微遗传算法","authors":"Xinmei Peng, Xuedong Zheng, Bin Wang, Changjun Zhou, Qiang Zhang","doi":"10.1109/CCSSE.2016.7784342","DOIUrl":null,"url":null,"abstract":"Aiming at DNA encoding sequences design, a micro-genetic algorithm (MGA) is proposed by introducing a sharing function based on similarity and H-measure of DNA sequences. In the algorithm, six design criteria are adopted and four genetic operators are applied. Compared with the previous results, the algorithm can get better DNA sequences and improve the computational efficiency.","PeriodicalId":136809,"journal":{"name":"2016 2nd International Conference on Control Science and Systems Engineering (ICCSSE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"A micro-genetic algorithm for DNA encoding sequences design\",\"authors\":\"Xinmei Peng, Xuedong Zheng, Bin Wang, Changjun Zhou, Qiang Zhang\",\"doi\":\"10.1109/CCSSE.2016.7784342\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aiming at DNA encoding sequences design, a micro-genetic algorithm (MGA) is proposed by introducing a sharing function based on similarity and H-measure of DNA sequences. In the algorithm, six design criteria are adopted and four genetic operators are applied. Compared with the previous results, the algorithm can get better DNA sequences and improve the computational efficiency.\",\"PeriodicalId\":136809,\"journal\":{\"name\":\"2016 2nd International Conference on Control Science and Systems Engineering (ICCSSE)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 2nd International Conference on Control Science and Systems Engineering (ICCSSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCSSE.2016.7784342\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 2nd International Conference on Control Science and Systems Engineering (ICCSSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCSSE.2016.7784342","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A micro-genetic algorithm for DNA encoding sequences design
Aiming at DNA encoding sequences design, a micro-genetic algorithm (MGA) is proposed by introducing a sharing function based on similarity and H-measure of DNA sequences. In the algorithm, six design criteria are adopted and four genetic operators are applied. Compared with the previous results, the algorithm can get better DNA sequences and improve the computational efficiency.
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