CUDA is a technology introduced by NVIDIA Corporation, which allows software developers to take advantage of GPU resources relatively easily. This paper presents an approach leading to significant acceleration of the execution of the Smith-Waterman algorithm. The algorithm finds the best local alignment of two sequences, such as amino acid or nucleotide sequences. The results show that it is possible to search bio-informatics databases accurately within a reasonable time.Wraz z wprowadzeniem przez firmę NVIDIA technologii CUDA wykorzystanie potencjału kart graficznych stało się łatwiejsze. W artykule przedstawiono metodę istotnego przyśpieszenia wykonania algorytmu Smitha-Watermana, znajdującego optymalne, lokalne dopasowanie dwóch sekwencj...
Abstract Background To infer homology and subsequentl...
Abstract—This paper describes a multi-threaded parallel design and implementation of the Smith-Water...
Graphics processor a b s t r a c t Finding regions of similarity between two very long data streams ...
Alignment algorithms are used to find similarity between biological sequences, such as DNA and prote...
Background Searching for similarities in protein and DNA databases has become a routine procedure in...
The Smith-Waterman (SW) algorithm has been widely utilized for searching biological sequence databas...
The Smith-Waterman algorithm is a common localsequence alignment method which gives a high accuracy....
Background Smith-Waterman (S-W) algorithm is an optimal sequence alignment method for biological dat...
Sequence alignment is a common and often repeated task in molecular biology. The need for speeding u...
Rapid evolution in sequencing technologies results in generating data on an enormous scale. A focal ...
The idea of using a graphics processing unit (GPU) for more than simply graphic output purposes has ...
With the sequencing of DNA becoming cheaper and the resulting stack of data growing bigger, there is...
Biological sequence alignment is an important and challenging task in bioinformatics. Alignment may ...
This paper describes a multi-threaded parallel design and implementation of the Smith-Waterman (SM) ...
Abstract: Efficient sequence alignment is one of the most important and challenging activities in bi...
Abstract Background To infer homology and subsequentl...
Abstract—This paper describes a multi-threaded parallel design and implementation of the Smith-Water...
Graphics processor a b s t r a c t Finding regions of similarity between two very long data streams ...
Alignment algorithms are used to find similarity between biological sequences, such as DNA and prote...
Background Searching for similarities in protein and DNA databases has become a routine procedure in...
The Smith-Waterman (SW) algorithm has been widely utilized for searching biological sequence databas...
The Smith-Waterman algorithm is a common localsequence alignment method which gives a high accuracy....
Background Smith-Waterman (S-W) algorithm is an optimal sequence alignment method for biological dat...
Sequence alignment is a common and often repeated task in molecular biology. The need for speeding u...
Rapid evolution in sequencing technologies results in generating data on an enormous scale. A focal ...
The idea of using a graphics processing unit (GPU) for more than simply graphic output purposes has ...
With the sequencing of DNA becoming cheaper and the resulting stack of data growing bigger, there is...
Biological sequence alignment is an important and challenging task in bioinformatics. Alignment may ...
This paper describes a multi-threaded parallel design and implementation of the Smith-Waterman (SM) ...
Abstract: Efficient sequence alignment is one of the most important and challenging activities in bi...
Abstract Background To infer homology and subsequentl...
Abstract—This paper describes a multi-threaded parallel design and implementation of the Smith-Water...
Graphics processor a b s t r a c t Finding regions of similarity between two very long data streams ...