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A Tabu Search Approach to Multiple Sequence Alignment

Sequence alignment methods are used to detect and quantify similarities between different DNA and protein sequences that may have evolved from a common ancestor. Effective sequence alignment methodologies also provide insight into the structure function of a sequence and are the first step in constructing evolutionary trees. In this dissertation, we use a tabu search approach to multiple sequence alignment. A tabu search is a heuristic approach that uses adaptive memory features to align multiple sequences. The adaptive memory feature, a tabu list, helps the search process avoid local optimal solutions and explores the solution space in an efficient manner. We develop two main tabu searches that progressively align sequences. A randomly generated bifurcating tree guides the alignment. The objective is to optimize the alignment score computed using either the sum of pairs or parsimony scoring function. The use of a parsimony scoring function provides insight into the homology between sequences in the alignment. We also explore iterative refinement techniques such as a hidden Markov model and an intensification heuristic to further improve the alignment. This approach to multiple sequence alignment provides improved alignments as compared to several other methods.

Identiferoai:union.ndltd.org:NCSU/oai:NCSU:etd-05312008-191232
Date05 August 2008
CreatorsLightner, Carin Ann
ContributorsDr. Simon M. Hsiang, Dr. Elmor Peterson, Dr. Henry L. W. Nuttle, Dr. Shu-Cherng Fang
PublisherNCSU
Source SetsNorth Carolina State University
LanguageEnglish
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://www.lib.ncsu.edu/theses/available/etd-05312008-191232/
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