Feedback algorithm and web-server for protein structure alignment.

Zhiyu Zhao, Bin Fu, Francisco J Alanis, Christopher M Summa
{"title":"Feedback algorithm and web-server for protein structure alignment.","authors":"Zhiyu Zhao,&nbsp;Bin Fu,&nbsp;Francisco J Alanis,&nbsp;Christopher M Summa","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>We have developed a feedback algorithm for protein structure alignment between two protein backbones. A web portal implementing this method has been constructed and is freely available for use at http://fpsa.cs.uno.edu/ with a mirror site at http://fpsa.cs.panam.edu/FPSA/. We compare our algorithm with three other, commonly used methods: CE, DaliLite and SSM. The results show that in most cases our algorithm outputs a larger number of aligned positions when the (Calpha) RMSD is comparable. Also, in many cases where the number of aligned positions is larger or comparable, our learning method is able to achieve a smaller (Calpha) RMSD than the other methods tested. This trend of larger number of aligned positions and smaller (Calpha) RMSD is observed more frequently in cases where the similarity between protein structures is weak.</p>","PeriodicalId":72665,"journal":{"name":"Computational systems bioinformatics. Computational Systems Bioinformatics Conference","volume":"7 ","pages":"109-20"},"PeriodicalIF":0.0000,"publicationDate":"2008-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational systems bioinformatics. Computational Systems 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

Abstract

We have developed a feedback algorithm for protein structure alignment between two protein backbones. A web portal implementing this method has been constructed and is freely available for use at http://fpsa.cs.uno.edu/ with a mirror site at http://fpsa.cs.panam.edu/FPSA/. We compare our algorithm with three other, commonly used methods: CE, DaliLite and SSM. The results show that in most cases our algorithm outputs a larger number of aligned positions when the (Calpha) RMSD is comparable. Also, in many cases where the number of aligned positions is larger or comparable, our learning method is able to achieve a smaller (Calpha) RMSD than the other methods tested. This trend of larger number of aligned positions and smaller (Calpha) RMSD is observed more frequently in cases where the similarity between protein structures is weak.

分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
蛋白质结构比对的反馈算法和web服务器。
我们开发了一种反馈算法,用于两个蛋白质骨干之间的蛋白质结构比对。已经构建了一个实现这种方法的门户网站,可以在http://fpsa.cs.uno.edu/上免费使用,在http://fpsa.cs.panam.edu/FPSA/上有一个镜像站点。我们将我们的算法与其他三种常用的方法进行了比较:CE、DaliLite和SSM。结果表明,在大多数情况下,当(Calpha) RMSD可比较时,我们的算法输出更多的对齐位置。此外,在许多情况下,当对齐位置的数量较大或可比较时,我们的学习方法能够获得比其他测试方法更小的RMSD (Calpha)。在蛋白质结构之间的相似性较弱的情况下,更经常观察到这种排列位置数量较多和RMSD (Calpha)较小的趋势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Novel Gene Discovery in the Human Malaria Parasite using Nucleosome Positioning Data. Estimating support for protein-protein interaction data with applications to function prediction. On the accurate construction of consensus genetic maps. Efficient haplotype inference from pedigrees with missing data using linear systems with disjoint-set data structures. Knowledge representation and data mining for biological imaging.
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1