S. A. Al Junid, M. Reffin, Z. Majid, N. Tahir, M. A. Haron
{"title":"优化DNA序列比对的遗传算法的实现","authors":"S. A. Al Junid, M. Reffin, Z. Majid, N. Tahir, M. A. Haron","doi":"10.1109/BEIAC.2012.6226111","DOIUrl":null,"url":null,"abstract":"This paper presents potential of genetic algorithms (GA) for optimizing DNA sequences alignment based on dynamic programming or evolutionary programming. The ultimate objective of this paper is to accelerate the process of DNA sequences alignment towards reducing the time and space complexity. In addition, the theoretical study, design, compilation and simulation of the proposed GA were carried out using Xilinx ISE 12.3 EDA software by applying divide and conquer design technique towards finding the optimal solution. The proposed GA has shown that it can solve up to 10 DNA sequences base pair in three clock cycles with reduction time up to 84.21 % as compare to original Smith-Waterman algorithm. As a conclusion, the proposed GA has proved and able to optimize the existing DNA sequences alignment time complexity.","PeriodicalId":404626,"journal":{"name":"2012 IEEE Business, Engineering & Industrial Applications Colloquium (BEIAC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Implementation of genetic algorithm for optimizing DNA sequence alignment\",\"authors\":\"S. A. Al Junid, M. Reffin, Z. Majid, N. Tahir, M. A. Haron\",\"doi\":\"10.1109/BEIAC.2012.6226111\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents potential of genetic algorithms (GA) for optimizing DNA sequences alignment based on dynamic programming or evolutionary programming. The ultimate objective of this paper is to accelerate the process of DNA sequences alignment towards reducing the time and space complexity. In addition, the theoretical study, design, compilation and simulation of the proposed GA were carried out using Xilinx ISE 12.3 EDA software by applying divide and conquer design technique towards finding the optimal solution. The proposed GA has shown that it can solve up to 10 DNA sequences base pair in three clock cycles with reduction time up to 84.21 % as compare to original Smith-Waterman algorithm. As a conclusion, the proposed GA has proved and able to optimize the existing DNA sequences alignment time complexity.\",\"PeriodicalId\":404626,\"journal\":{\"name\":\"2012 IEEE Business, Engineering & Industrial Applications Colloquium (BEIAC)\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-04-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE Business, Engineering & Industrial Applications Colloquium (BEIAC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BEIAC.2012.6226111\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE Business, Engineering & Industrial Applications Colloquium (BEIAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BEIAC.2012.6226111","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Implementation of genetic algorithm for optimizing DNA sequence alignment
This paper presents potential of genetic algorithms (GA) for optimizing DNA sequences alignment based on dynamic programming or evolutionary programming. The ultimate objective of this paper is to accelerate the process of DNA sequences alignment towards reducing the time and space complexity. In addition, the theoretical study, design, compilation and simulation of the proposed GA were carried out using Xilinx ISE 12.3 EDA software by applying divide and conquer design technique towards finding the optimal solution. The proposed GA has shown that it can solve up to 10 DNA sequences base pair in three clock cycles with reduction time up to 84.21 % as compare to original Smith-Waterman algorithm. As a conclusion, the proposed GA has proved and able to optimize the existing DNA sequences alignment time complexity.