An optimization approach to multiple sequence alignment

The problem of multiple sequence alignment is recast as an optimization problem using Markov decision theory. One seeks to minimize the expected or average cost of alignment subject to data-derived constraints. In this setting, the problem is equivalent to a linear program which can be solved effici...

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Bibliographic Details
Published inApplied mathematics letters Vol. 16; no. 5; pp. 785 - 790
Main Authors Hunt, F.Y., Kearsley, A.J., Wan, Honghui
Format Journal Article
LanguageEnglish
Published Oxford Elsevier Ltd 01.07.2003
Elsevier
Subjects
Alignment
Applied sciences
Biological and medical sciences
Calculus of variations and optimal control
Exact sciences and technology
Fundamental and applied biological sciences. Psychology
General aspects
Linear programming
Markov processes
Mathematical analysis
Mathematical programming
Mathematics
Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects)
Operational research and scientific management
Operational research. Management science
Probability and statistics
Probability theory and stochastic processes
Sciences and techniques of general use
Sequencing
Linear programming
Sequencing
Alignment
Markov decision
Applied mathematics
DNA
Sequence alignment
Optimization method
Interior point method
Algorithm
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ISSN0893-9659
1873-5452
DOI10.1016/S0893-9659(03)00083-1

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Summary:The problem of multiple sequence alignment is recast as an optimization problem using Markov decision theory. One seeks to minimize the expected or average cost of alignment subject to data-derived constraints. In this setting, the problem is equivalent to a linear program which can be solved efficiently using modern interior-point methods. We present numerical results from an implementation of the algorithm for protein sequence alignment
ISSN:0893-9659
1873-5452
DOI:10.1016/S0893-9659(03)00083-1