{"title":"使用压缩后缀数组查找最大重叠的节省空间的解决方案","authors":"M. Rachid, Q. Malluhi, M. Abouelhoda","doi":"10.1109/MECBME.2014.6783270","DOIUrl":null,"url":null,"abstract":"Compressed indices are important data structures in stringology. Compressed versions of many well-known data structures such as suffix tree and suffix array, which are used in string matching problems, have been studied and proposed. This paper takes advantage of a very recent compressed suffix array to build a space-economic solution for an important bioinformatics problem, namely the all-pairs suffix prefix problem. The paper also presents a simple technique for parallelizing the solution. Our results show that the proposed solution consumes less than one fifth of the space required by other solutions based on standard data structures. In addition, our results demonstrate that good performance scalability can be achieved by employing the proposed parallel algorithm.","PeriodicalId":384055,"journal":{"name":"2nd Middle East Conference on Biomedical Engineering","volume":"310 ","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"A space-efficient solution to find the maximum overlap using a compressed suffix array\",\"authors\":\"M. Rachid, Q. Malluhi, M. Abouelhoda\",\"doi\":\"10.1109/MECBME.2014.6783270\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Compressed indices are important data structures in stringology. Compressed versions of many well-known data structures such as suffix tree and suffix array, which are used in string matching problems, have been studied and proposed. This paper takes advantage of a very recent compressed suffix array to build a space-economic solution for an important bioinformatics problem, namely the all-pairs suffix prefix problem. The paper also presents a simple technique for parallelizing the solution. Our results show that the proposed solution consumes less than one fifth of the space required by other solutions based on standard data structures. In addition, our results demonstrate that good performance scalability can be achieved by employing the proposed parallel algorithm.\",\"PeriodicalId\":384055,\"journal\":{\"name\":\"2nd Middle East Conference on Biomedical Engineering\",\"volume\":\"310 \",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-04-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2nd Middle East Conference on Biomedical Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MECBME.2014.6783270\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2nd Middle East Conference on Biomedical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MECBME.2014.6783270","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A space-efficient solution to find the maximum overlap using a compressed suffix array
Compressed indices are important data structures in stringology. Compressed versions of many well-known data structures such as suffix tree and suffix array, which are used in string matching problems, have been studied and proposed. This paper takes advantage of a very recent compressed suffix array to build a space-economic solution for an important bioinformatics problem, namely the all-pairs suffix prefix problem. The paper also presents a simple technique for parallelizing the solution. Our results show that the proposed solution consumes less than one fifth of the space required by other solutions based on standard data structures. In addition, our results demonstrate that good performance scalability can be achieved by employing the proposed parallel algorithm.