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Hidden Markov Models and their Applications in Biological Sequence Analysis
2009
Current Genomics
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 to 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
doi:10.2174/138920209789177575
pmid:20190955
pmcid:PMC2766791
fatcat:h6m33ccye5h27hdzk6z27khpki