Hidden Markov Models and their Applications in Biological Sequence Analysis. Academic Article

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.

authors

• Yoon, Byung-Jun

published proceedings

• Curr Genomics

altmetric score

• 16.75

author list (cited authors)

• Yoon, B.

citation count

• 201

complete list of authors

• Yoon, Byung-Jun

publication date

• January 2009

publisher

• BENTHAM SCIENCE PUBLISHERS  Publisher

published in

• Current Genomics  Journal

keywords

• Context-sensitive Hmm (cshmm)
• Hidden Markov Model (hmm)
• Pair-hmm
• Profile-cshmm
• Profile-hmm
• Sequence Analysis.

PubMed Central ID

• 20190955

Digital Object Identifier (DOI)

• 10.2174/138920209789177575

start page

• 402

end page

• 415

volume

• 10

issue

• 6

URL

• http%3A%2F%2Fdx.doi.org%2F10.2174%2F138920209789177575