S. Islam, Md Rashed Asger, Md. Abid Hasan, M. Mottalib
{"title":"一种改进的变长DNA基序发现算法","authors":"S. Islam, Md Rashed Asger, Md. Abid Hasan, M. Mottalib","doi":"10.1109/ICSIMA.2013.6717960","DOIUrl":null,"url":null,"abstract":"Motifs are meaningful short sequences which conserve itself during the evolution and discovery of motifs are used to put DNA sequences into their corresponding categories. Different evolutionary methods have been used for motif discovery i.e. genetic algorithm, PSO etc. In this paper we have incorporated the concept of Linear-PSO to find motifs from DNA sequences. However, Linear-PSO is a slower method which involves linear search for motif discovery. So we have introduced the function of index table to make the motif discovery faster. Before comparing the target motif (a particle selected by Linear-PSO in each cycle) linearly with other DNA sequences, we have first created an index table that contains the information about the index of first base of each of the target motifs. Identifying with the help of index table has lessened the time required for motif discovery. Experimental results show that the proposed method can discover motifs with higher validity and better efficiency.","PeriodicalId":182424,"journal":{"name":"2013 IEEE International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A modified algorithm for variable length DNA motif discovery\",\"authors\":\"S. Islam, Md Rashed Asger, Md. Abid Hasan, M. Mottalib\",\"doi\":\"10.1109/ICSIMA.2013.6717960\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Motifs are meaningful short sequences which conserve itself during the evolution and discovery of motifs are used to put DNA sequences into their corresponding categories. Different evolutionary methods have been used for motif discovery i.e. genetic algorithm, PSO etc. In this paper we have incorporated the concept of Linear-PSO to find motifs from DNA sequences. However, Linear-PSO is a slower method which involves linear search for motif discovery. So we have introduced the function of index table to make the motif discovery faster. Before comparing the target motif (a particle selected by Linear-PSO in each cycle) linearly with other DNA sequences, we have first created an index table that contains the information about the index of first base of each of the target motifs. Identifying with the help of index table has lessened the time required for motif discovery. Experimental results show that the proposed method can discover motifs with higher validity and better efficiency.\",\"PeriodicalId\":182424,\"journal\":{\"name\":\"2013 IEEE International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA)\",\"volume\":\"98 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSIMA.2013.6717960\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSIMA.2013.6717960","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A modified algorithm for variable length DNA motif discovery
Motifs are meaningful short sequences which conserve itself during the evolution and discovery of motifs are used to put DNA sequences into their corresponding categories. Different evolutionary methods have been used for motif discovery i.e. genetic algorithm, PSO etc. In this paper we have incorporated the concept of Linear-PSO to find motifs from DNA sequences. However, Linear-PSO is a slower method which involves linear search for motif discovery. So we have introduced the function of index table to make the motif discovery faster. Before comparing the target motif (a particle selected by Linear-PSO in each cycle) linearly with other DNA sequences, we have first created an index table that contains the information about the index of first base of each of the target motifs. Identifying with the help of index table has lessened the time required for motif discovery. Experimental results show that the proposed method can discover motifs with higher validity and better efficiency.