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{"title":"蛋白质序列相似性搜索的HMMER Web服务器","authors":"Ananth Prakash, Matt Jeffryes, Alex Bateman, 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 & 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, Matt Jeffryes, Alex Bateman, 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 & 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}
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