Prakash Ananth, Jeffryes Matt, Bateman Alex, Finn Robert D
European Molecular Biology Laboratory, The European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom.
Curr Protoc Bioinformatics. 2017 Dec 8;60:3.15.1-3.15.23. doi: 10.1002/cpbi.40.
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.
蛋白质序列相似性搜索是用于识别进化相关蛋白质的最常用生物信息学方法之一。一般来说，进化相关的序列具有一定程度的相似性，序列搜索算法利用这一原理来识别同源物。对快速且灵敏的序列搜索方法的需求促使了HMMER软件的开发，其最新版本（v3.1）使用了复杂的加速启发式方法与数学和计算优化相结合的方式，以便能够使用轮廓隐马尔可夫模型（HMM）进行序列分析。HMMER网络服务器通过将HMMER算法与数据库相链接，提供了一个通用平台，从而能够搜索同源物，还能通过链接外部数据库提供序列和功能注释。本单元描述了三种基本方案和两种替代方案，这些方案解释了如何使用各种输入格式和用户定义参数来使用HMMER网络服务器。© 2017约翰威立国际出版公司。
