Suppr超能文献

隐马尔可夫模型及其在生物序列分析中的应用。

Hidden Markov Models and their Applications in Biological Sequence Analysis.

机构信息

Department of Electrical & Computer Engineering, Texas A&M University, College Station, TX 77843-3128, USA.

出版信息

Curr Genomics. 2009 Sep;10(6):402-15. doi: 10.2174/138920209789177575.

Abstract

Hidden Markov models (HMMs) have been extensively used in biological sequence analysis. In this paper, we give a tutorial review of HMMs and their applications in a variety of problems in molecular biology. We especially focus on three types of HMMs: the profile-HMMs, pair-HMMs, and context-sensitive HMMs. We show how these HMMs can be used to solve various sequence analysis problems, such as pairwise and multiple sequence alignments, gene annotation, classification, similarity search, and many others.

摘要

隐马尔可夫模型(HMMs)在生物序列分析中得到了广泛的应用。在本文中,我们对 HMMs 及其在分子生物学中各种问题中的应用进行了教程式的回顾。我们特别关注三种类型的 HMMs: 轮廓 HMMs、对 HMMs 和上下文敏感 HMMs。我们展示了如何使用这些 HMMs 来解决各种序列分析问题,如两两和多序列比对、基因注释、分类、相似性搜索等等。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c7ed/2766791/3166bc741bcc/CG-10-402_F1.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验