DocumentCode
3520051
Title
Sampling Based Meta-algorithms for Accurate Multiple Sequence Alignment
Author
Thapar, Vishal ; Rajasekaran, Sanguthevar
Author_Institution
Dept. of Comput. Sci., Univ. of Connecticut, Storrs, CT
fYear
2008
fDate
3-5 Nov. 2008
Firstpage
429
Lastpage
432
Abstract
The problem of multiple sequence alignment (MSA) in biology has been studied extensively. In this paper we offer sampling based algorithms for MSA that are more accurate than existing algorithms. The performance of our algorithms has been evaluated using the standard BaliBase dataset [10]. We are able to improve the average alignment SP score for ClustalW [9] and MAFFT [6] by 16.39% and 12.2 %, respectively and the TC score by 55.4% and 46.9%, respectively using sampling. Given that ClustalW and MAFFT are some of the most accurate algorithms for MSA currently and are widely used, our algorithms would be of interest to biologists.
Keywords
biological techniques; biology computing; sampling methods; sequences; BaliBase dataset; ClustalW algorithm; MAFFT algorithm; Multiple Sequence Alignment; metaalgorithms; sampling; Algorithm design and analysis; Benchmark testing; Bioinformatics; Biology computing; Computer science; Measurement standards; Performance analysis; Runtime; Sampling methods; Sequences;
fLanguage
English
Publisher
ieee
Conference_Titel
Bioinformatics and Biomedicine, 2008. BIBM '08. IEEE International Conference on
Conference_Location
Philadelphia, PA
Print_ISBN
978-0-7695-3452-7
Type
conf
DOI
10.1109/BIBM.2008.51
Filename
4684933
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