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| Content Provider | IEEE Xplore Digital Library | 
|---|---|
| Author | Steinfadt, S. Baker, J.W. | 
| Copyright Year | 2008 | 
| Description | Author affiliation: Dept. of Comput. Sci., Kent State Univ., Kent, OH (Steinfadt, S.; Baker, J.W.) | 
| Abstract | One of the most commonly used tools by computational biologists is some form of sequence alignment. Heuristic alignment algorithms developed for speed and their multiple results such as BLAST [1] and FASTA [2] are not a total replacement for the more rigorous but slower algorithms like Smith- Waterman [3]. The different techniques complement one another. A heuristic can filter dissimilar sequences from a large database such as GenBank [4] and the Smith-Waterman algorithm performs more detailed, in-depth alignment in a way not adequately handled by heuristic methods. An associative parallel Smith-Waterman algorithm has been improved and further parallelized. Analysis between different algorithms, different types of file input, and different input sizes have been performed and are reported here. The newly developed associative algorithm reduces the running time for rigorous pairwise local sequence alignment. | 
| Starting Page | 1 | 
| Ending Page | 8 | 
| File Size | 663948 | 
| Page Count | 8 | 
| File Format | |
| ISBN | 9781424416936 | 
| ISSN | 15302075 | 
| DOI | 10.1109/IPDPS.2008.4536468 | 
| Language | English | 
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) | 
| Publisher Date | 2008-04-14 | 
| Publisher Place | USA | 
| Access Restriction | Subscribed | 
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) | 
| Subject Keyword | Concurrent computing Heuristic algorithms Dynamic programming Parallel processing Biology computing Performance analysis Evolution (biology) Computer science Filters Databases Sequence alignment Associative computing SIMD computing Parallel algorithms | 
| Content Type | Text | 
| Resource Type | Article | 
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