高效约束多序列对齐,保证性能。

Francis Y Chin, N L Ho, T W Lam, Prudence W Wong, M Y Chan
{"title":"高效约束多序列对齐,保证性能。","authors":"Francis Y Chin,&nbsp;N L Ho,&nbsp;T W Lam,&nbsp;Prudence W Wong,&nbsp;M Y Chan","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>The Constrained Multiple Sequence Alignment problem is to align a set of sequences subject to a given constrained sequence, which arises from some knowledge of the structure of the sequences. This paper presents new algorithms for this problem, which are more efficient in terms of time and space (memory) than the previous algorithms [14], and with a worst-case guarantee on the quality of the alignment. Saving the space requirement by a quadratic factor is particularly significant as the previous O(n(4))-space algorithm has limited application due to its huge memory requirement. Experiments on real data sets confirm that our new algorithms show improvements in both alignment quality and resource requirements.</p>","PeriodicalId":87204,"journal":{"name":"Proceedings. IEEE Computer Society Bioinformatics Conference","volume":"2 ","pages":"337-46"},"PeriodicalIF":0.0000,"publicationDate":"2003-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Efficient constrained multiple sequence alignment with performance guarantee.\",\"authors\":\"Francis Y Chin,&nbsp;N L Ho,&nbsp;T W Lam,&nbsp;Prudence W Wong,&nbsp;M Y Chan\",\"doi\":\"\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The Constrained Multiple Sequence Alignment problem is to align a set of sequences subject to a given constrained sequence, which arises from some knowledge of the structure of the sequences. This paper presents new algorithms for this problem, which are more efficient in terms of time and space (memory) than the previous algorithms [14], and with a worst-case guarantee on the quality of the alignment. Saving the space requirement by a quadratic factor is particularly significant as the previous O(n(4))-space algorithm has limited application due to its huge memory requirement. Experiments on real data sets confirm that our new algorithms show improvements in both alignment quality and resource requirements.</p>\",\"PeriodicalId\":87204,\"journal\":{\"name\":\"Proceedings. IEEE Computer Society Bioinformatics Conference\",\"volume\":\"2 \",\"pages\":\"337-46\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. IEEE Computer Society Bioinformatics Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. IEEE Computer Society Bioinformatics Conference","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

约束多序列比对问题是根据给定的约束序列对一组序列进行比对,这是由对序列结构的一定了解而产生的。本文提出了针对该问题的新算法,该算法在时间和空间(内存)方面比以前的算法[14]更有效,并且对对齐质量具有最坏情况保证。由于以前的O(n(4))空间算法由于其巨大的内存需求而限制了应用,因此通过二次因子节省空间需求尤为重要。在真实数据集上的实验证实了我们的新算法在对齐质量和资源需求方面都有改善。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient constrained multiple sequence alignment with performance guarantee.

The Constrained Multiple Sequence Alignment problem is to align a set of sequences subject to a given constrained sequence, which arises from some knowledge of the structure of the sequences. This paper presents new algorithms for this problem, which are more efficient in terms of time and space (memory) than the previous algorithms [14], and with a worst-case guarantee on the quality of the alignment. Saving the space requirement by a quadratic factor is particularly significant as the previous O(n(4))-space algorithm has limited application due to its huge memory requirement. Experiments on real data sets confirm that our new algorithms show improvements in both alignment quality and resource requirements.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信