{"title":"RSMA Matching Algorithm for searching biological sequences","authors":"Ahmad F. Klaib, H. Osborne","doi":"10.1109/IIT.2009.5413769","DOIUrl":null,"url":null,"abstract":"Huge amounts of biological data are stored in linear files. Biological proteins are sequences of amino acids. The quantities of data in these fields tend to increase year on year. String matching algorithms play a key role in many computer science problems, and in the implementation of computer software. For this reason efficient string-matching algorithms should be used which use minimal computer storage and which minimize the searching response time. In this study, we propose a new algorithm called the Random String Matching Algorithm (RSMA). RSMA combines our enhanced preprocessing phase from the Berry Ravindran algorithm with our proposed new searching phase procedure. This variety of searching order allows our proposed algorithm to reduce the number of comparison characters and enhances the searching response time. Experimental results show that the RSMA algorithm offers a smaller number of comparisons and offers improved elapsed searching time when compared to other well-known algorithms.","PeriodicalId":239829,"journal":{"name":"2009 International Conference on Innovations in Information Technology (IIT)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Innovations in Information Technology (IIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IIT.2009.5413769","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Huge amounts of biological data are stored in linear files. Biological proteins are sequences of amino acids. The quantities of data in these fields tend to increase year on year. String matching algorithms play a key role in many computer science problems, and in the implementation of computer software. For this reason efficient string-matching algorithms should be used which use minimal computer storage and which minimize the searching response time. In this study, we propose a new algorithm called the Random String Matching Algorithm (RSMA). RSMA combines our enhanced preprocessing phase from the Berry Ravindran algorithm with our proposed new searching phase procedure. This variety of searching order allows our proposed algorithm to reduce the number of comparison characters and enhances the searching response time. Experimental results show that the RSMA algorithm offers a smaller number of comparisons and offers improved elapsed searching time when compared to other well-known algorithms.