Hidden Markov Models and their Applications in Biological Sequence Analysis

Title: Hidden Markov Models and their Applications in Biological Sequence Analysis

Volume: 10 Issue: 6

Author(s): Byung-Jun Yoon

Affiliation:

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

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.

Cite this article as:

Yoon Byung-Jun, Hidden Markov Models and their Applications in Biological Sequence Analysis, Current Genomics 2009; 10 (6) . https://dx.doi.org/10.2174/138920209789177575