DocumentCode
2915462
Title
N-SAMSAM : A simple and faster algorithm for solving approximate matching in DNA sequences
Author
Ni, Bing ; Wong, M.H. ; Leung, K.S.
Author_Institution
Dept. of Comput. Sci. & Eng., Chinese Univ. of Hong Kong, Hong Kong
fYear
2008
fDate
1-6 June 2008
Firstpage
2592
Lastpage
2598
Abstract
This work proposes a novel algorithm to do approximate matching in a database consisting of multiple sequences. We apply Agrep algorithm in an indexing structure, the r-cut numerical substring array (r-NSA). The structure basically indexes all the substrings of length r. The advantage of using the r-NSA is two-fold: (1) The space requirement of the r-NSA is much smaller than that of the other existing indexing structures, such as the generalized suffix tree. (2) We propose an algorithm to apply Agrep in the r-NSA, in which the substrings are processed sequentially. Since the common substrings are processed only once, the cost of our algorithm is smaller than that of the full scanning search by Agrep. Consequently, the matching time of our algorithm is also reduced. We design experiments to validate and compare the performance of our algorithm against the full scanning search by Agrep. We define the speed-up of our algorithm as the time required by the full scanning search by Agrep over that of our algorithm. We use eight sets of real DNA sequences in our experiments, and the results show that our algorithm achieves significant speed-up. We also investigate the speed-up of difference data sets, and analyze their differences in detail.
Keywords
biology computing; database management systems; pattern matching; proteins; DNA sequences; approximate matching; data sets; generalized suffix tree; indexing structure; multiple sequences; Algorithm design and analysis; Computer errors; Costs; DNA; Data analysis; Databases; Genetic mutations; Indexing; Information retrieval; Sequences;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-1822-0
Electronic_ISBN
978-1-4244-1823-7
Type
conf
DOI
10.1109/CEC.2008.4631146
Filename
4631146
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