CUDASW++: optimizing Smith-Waterman sequence database searches for CUDA-enabled graphics processing units
نویسندگان
چکیده
منابع مشابه
Improving the Mapping of Smith-Waterman Sequence Database Searches onto CUDA-Enabled GPUs
Sequence alignment lies at heart of the bioinformatics. The Smith-Waterman algorithm is one of the key sequence search algorithms and has gained popularity due to improved implementations and rapidly increasing compute power. Recently, the Smith-Waterman algorithm has been successfully mapped onto the emerging general-purpose graphics processing units (GPUs). In this paper, we focused on how to...
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MOTIVATION Sequence database searching is among the most important and challenging tasks in bioinformatics. The ultimate choice of sequence-search algorithm is that of Smith-Waterman. However, because of the computationally demanding nature of this method, heuristic programs or special-purpose hardware alternatives have been developed. Increased speed has been obtained at the cost of reduced se...
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Mutual correlation between segments of DNA or protein sequences can be detected by Smith-Waterman local alignments. We present a statistical analysis of alignment of such sequences, based on a recent scaling theory. A new fidelity measure is introduced and shown to capture the significance of the local alignment, i.e., the extent to which the correlated subsequences are correctly identified. It...
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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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Circle detection has been widely applied in image processing applications. Hough transform, the most popular method of shape detection, normally takes a long time to achieve reasonable results, especially for large images. Such performance makes it almost impossible to conduct real-time image processing with sequential algorithms on community computers. Recently, NVIDIA developed CUDA programmi...
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ژورنال
عنوان ژورنال: BMC Research Notes
سال: 2009
ISSN: 1756-0500
DOI: 10.1186/1756-0500-2-73