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Current Genomics

Editor-in-Chief

ISSN (Print): 1389-2029
ISSN (Online): 1875-5488

Hidden Markov Models and their Applications in Biological Sequence Analysis

Author(s): Byung-Jun Yoon

Volume 10, Issue 6, 2009

Page: [402 - 415] Pages: 14

DOI: 10.2174/138920209789177575

Price: $65

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.

Keywords: Hidden Markov model (HMM), pair-HMM, profile-HMM, context-sensitive HMM (csHMM), profile-csHMM, sequence analysis, scleroderma


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