Sequence alignment has become a routine procedure in evolutionary biology in looking for evolutionary relationships between primary sequences of DNA, RNA, and protein. Smith Waterman and Needleman Wunsch algorithms are two algorithms respectively for local alignment and global alignment. Both of them are based on dynamic programming and guarantee optimal results. They have been widely used for the past dozens of years. However, time and space requirement increase exponentially with the number of sequences increase. Here I present a novel approach to improve the performance of sequence alignment by using graphics processing unit which is capable of handling large amount of data in parallel.
| Identifer | oai:union.ndltd.org:siu.edu/oai:opensiuc.lib.siu.edu:theses-1431 |
| Date | 01 January 2008 |
| Creators | He, Jintai |
| Publisher | OpenSIUC |
| Source Sets | Southern Illinois University Carbondale |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses |
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