蛋白质序列相似性搜索的HMMER Web服务器

Q1 Biochemistry, Genetics and Molecular Biology Current protocols in bioinformatics Pub Date : 2017-12-08 DOI:10.1002/cpbi.40
Ananth Prakash, Matt Jeffryes, Alex Bateman, Robert D. Finn
{"title":"蛋白质序列相似性搜索的HMMER Web服务器","authors":"Ananth Prakash,&nbsp;Matt Jeffryes,&nbsp;Alex Bateman,&nbsp;Robert D. Finn","doi":"10.1002/cpbi.40","DOIUrl":null,"url":null,"abstract":"<p>Protein sequence similarity search is one of the most commonly used bioinformatics methods for identifying evolutionarily related proteins. In general, sequences that are evolutionarily related share some degree of similarity, and sequence-search algorithms use this principle to identify homologs. The requirement for a fast and sensitive sequence search method led to the development of the HMMER software, which in the latest version (v3.1) uses a combination of sophisticated acceleration heuristics and mathematical and computational optimizations to enable the use of profile hidden Markov models (HMMs) for sequence analysis. The HMMER Web server provides a common platform by linking the HMMER algorithms to databases, thereby enabling the search for homologs, as well as providing sequence and functional annotation by linking external databases. This unit describes three basic protocols and two alternate protocols that explain how to use the HMMER Web server using various input formats and user defined parameters. © 2017 by John Wiley &amp; Sons, Inc.</p>","PeriodicalId":10958,"journal":{"name":"Current protocols in bioinformatics","volume":"60 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2017-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/cpbi.40","citationCount":"103","resultStr":"{\"title\":\"The HMMER Web Server for Protein Sequence Similarity Search\",\"authors\":\"Ananth Prakash,&nbsp;Matt Jeffryes,&nbsp;Alex Bateman,&nbsp;Robert D. Finn\",\"doi\":\"10.1002/cpbi.40\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Protein sequence similarity search is one of the most commonly used bioinformatics methods for identifying evolutionarily related proteins. In general, sequences that are evolutionarily related share some degree of similarity, and sequence-search algorithms use this principle to identify homologs. The requirement for a fast and sensitive sequence search method led to the development of the HMMER software, which in the latest version (v3.1) uses a combination of sophisticated acceleration heuristics and mathematical and computational optimizations to enable the use of profile hidden Markov models (HMMs) for sequence analysis. The HMMER Web server provides a common platform by linking the HMMER algorithms to databases, thereby enabling the search for homologs, as well as providing sequence and functional annotation by linking external databases. This unit describes three basic protocols and two alternate protocols that explain how to use the HMMER Web server using various input formats and user defined parameters. © 2017 by John Wiley &amp; Sons, Inc.</p>\",\"PeriodicalId\":10958,\"journal\":{\"name\":\"Current protocols in bioinformatics\",\"volume\":\"60 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-12-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1002/cpbi.40\",\"citationCount\":\"103\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current protocols in bioinformatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/cpbi.40\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Biochemistry, Genetics and Molecular Biology\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current protocols in bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cpbi.40","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Biochemistry, Genetics and Molecular Biology","Score":null,"Total":0}
引用次数: 103

摘要

蛋白质序列相似性搜索是鉴定进化相关蛋白最常用的生物信息学方法之一。一般来说,在进化上相关的序列具有一定程度的相似性,序列搜索算法使用这一原理来识别同源物。对快速和敏感的序列搜索方法的需求导致了HMMER软件的开发,该软件在最新版本(v3.1)中结合了复杂的加速启发式和数学和计算优化,从而能够使用剖面隐马尔可夫模型(hmm)进行序列分析。HMMER Web服务器通过将HMMER算法链接到数据库提供了一个公共平台,从而能够搜索同源物,并通过链接外部数据库提供序列和功能注释。本单元描述了三个基本协议和两个替代协议,这些协议解释了如何使用各种输入格式和用户定义的参数来使用HMMER Web服务器。©2017 by John Wiley &儿子,Inc。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
The HMMER Web Server for Protein Sequence Similarity Search

Protein sequence similarity search is one of the most commonly used bioinformatics methods for identifying evolutionarily related proteins. In general, sequences that are evolutionarily related share some degree of similarity, and sequence-search algorithms use this principle to identify homologs. The requirement for a fast and sensitive sequence search method led to the development of the HMMER software, which in the latest version (v3.1) uses a combination of sophisticated acceleration heuristics and mathematical and computational optimizations to enable the use of profile hidden Markov models (HMMs) for sequence analysis. The HMMER Web server provides a common platform by linking the HMMER algorithms to databases, thereby enabling the search for homologs, as well as providing sequence and functional annotation by linking external databases. This unit describes three basic protocols and two alternate protocols that explain how to use the HMMER Web server using various input formats and user defined parameters. © 2017 by John Wiley & Sons, Inc.

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
Current protocols in bioinformatics
Current protocols in bioinformatics Biochemistry, Genetics and Molecular Biology-Biochemistry
自引率
0.00%
发文量
0
期刊介绍: With Current Protocols in Bioinformatics, it"s easier than ever for the life scientist to become "fluent" in bioinformatics and master the exciting new frontiers opened up by DNA sequencing. Updated every three months in all formats, CPBI is constantly evolving to keep pace with the very latest discoveries and developments.
期刊最新文献
Issue Information Protein Sequence Analysis Using the MPI Bioinformatics Toolkit Exploring Manually Curated Annotations of Intrinsically Disordered Proteins with DisProt Network Building with the Cytoscape BioGateway App Explained in Five Use Cases Issue Information
×
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