Hidden Markov Models and their Applications in Biological Sequence Analysis

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Type: Journal Publication

Web: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2766791/?tool=pubmed


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.


Cited as: Byung-Jun Yoon, "Hidden Markov Models and their Applications in Biological Sequence Analysis", Curr Genomics. 2009 September; 10(6): 402–415

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