Department of Electrical & Computer Engineering, Texas A&M University, College Station, TX 77843-3128, USA.
Curr Genomics. 2009 Sep;10(6):402-15. doi: 10.2174/138920209789177575.
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.
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。
