CUDA compatible GPU cards as efficient hardware accelerators for Smith-Waterman sequence alignment
نویسندگان
چکیده
منابع مشابه
Parallelizing the Smith-Waterman Local Alignment Algorithm using CUDA
Given two strings S1 = pqaxabcstrqrtp and S2 = xyaxbacsl, the substrings axabcs in S1 and axbacs in S2 are very similar. The problem of finding similar substrings is the local alignment problem. Local alignment is extensively used in computational biology to find regions of similarity in different biological sequences. Similar genetic sequences are identified by computing the local alignment of...
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Algorithm and scoring parameters Eg ”best” Two methods for searching protein and DNA Evolution of protein and DNA sequence is done using database. 1. Local comparison i) Ignoring difference-outside most similar region ii) Find similarity between two sequence 2. Gobal Comparison. More appropriate when homology has been established when Building evolutionary trees comparison methods are preferred...
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GPU parallelism for real applications can achieve enormous performance gain. CPU-GPU Communication is one of the major bottlenecks that limit this performance gain. Among several libraries developed so far to optimize this communication, DyManD (Dynamically Managed Data) provides better communication optimization strategies and achieves better performance on a single GPU. SmithWaterman is a wel...
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ژورنال
عنوان ژورنال: BMC Bioinformatics
سال: 2008
ISSN: 1471-2105
DOI: 10.1186/1471-2105-9-s2-s10