下载PDF
{"title":"Sequence Similarity Searching","authors":"Gang Hu, Lukasz Kurgan","doi":"10.1002/cpps.71","DOIUrl":null,"url":null,"abstract":"<p>Sequence similarity searching has become an important part of the daily routine of molecular biologists, bioinformaticians and biophysicists. With the rapidly growing sequence databanks, this computational approach is commonly applied to determine functions and structures of unannotated sequences, to investigate relationships between sequences, and to construct phylogenetic trees. We introduce arguably the most popular BLAST-based family of the sequence similarity search tools. We explain basic concepts related to the sequence alignment and demonstrate how to search the current databanks using Web site versions of BLASTP, PSI-BLAST and BLASTN. We also describe the standalone BLAST+ tool. Moreover, this unit discusses the inputs, parameter settings and outputs of these tools. Lastly, we cover recent advances in the sequence similarity searching, focusing on the fast MMseqs2 method. © 2018 by John Wiley & Sons, Inc.</p>","PeriodicalId":10866,"journal":{"name":"Current Protocols in Protein Science","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/cpps.71","citationCount":"48","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Protocols in Protein Science","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cpps.71","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: 48
引用
批量引用
Abstract
Sequence similarity searching has become an important part of the daily routine of molecular biologists, bioinformaticians and biophysicists. With the rapidly growing sequence databanks, this computational approach is commonly applied to determine functions and structures of unannotated sequences, to investigate relationships between sequences, and to construct phylogenetic trees. We introduce arguably the most popular BLAST-based family of the sequence similarity search tools. We explain basic concepts related to the sequence alignment and demonstrate how to search the current databanks using Web site versions of BLASTP, PSI-BLAST and BLASTN. We also describe the standalone BLAST+ tool. Moreover, this unit discusses the inputs, parameter settings and outputs of these tools. Lastly, we cover recent advances in the sequence similarity searching, focusing on the fast MMseqs2 method. © 2018 by John Wiley & Sons, Inc.
序列相似性搜索
序列相似性搜索已成为分子生物学家、生物信息学家和生物物理学家日常工作的重要组成部分。随着序列数据库的快速增长，这种计算方法通常用于确定未注释序列的功能和结构，研究序列之间的关系，以及构建系统发育树。我们介绍了最流行的基于blast的序列相似性搜索工具家族。我们解释了与序列比对相关的基本概念，并演示了如何使用BLASTP、PSI-BLAST和BLASTN的网站版本搜索当前的数据库。我们还描述了独立的BLAST+工具。此外，本单元还讨论了这些工具的输入、参数设置和输出。最后，我们介绍了序列相似性搜索的最新进展，重点介绍了快速MMseqs2方法。©2018 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。
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
