The well-known Smith–Waterman algorithm is a high-sensitivity method for local sequence alignment. Unfortunately, the Smith–Waterman algorithm has quadratic time complexity, which makes it computationally demanding for large protein databases. In this paper, we present OSWALD, a portable, fully functional and general implementation to accelerate Smith–Waterman database searches in heterogeneous platforms based on Altera’s FPGA. OSWALD exploits OpenMP multithreading and SIMD computing through SSE and AVX2 extensions on the host while taking advantage of pipeline and vectorial parallelism by way of OpenCL on the FPGAs. Performance evaluations on two different heterogeneous architectures with real amino acid datasets show that OSWALD is compet...
Background Smith-Waterman (S-W) algorithm is an optimal sequence alignment method for biological dat...
Rapid evolution in sequencing technologies results in generating data on an enormous scale. A focal ...
BackgroundBioinformatic workflows frequently make use of automated genome assembly and protein clust...
The well-known Smith–Waterman algorithm is a high-sensitivity method for local sequence alignment. U...
The well-known Smith–Waterman algorithm is a high-sensitivity method for local sequence alignment. U...
The well-known Smith-Waterman (SW) algorithm is a high-sensitivity method for local alignments. Unfo...
With the greater importance of parallel architectures such as GPUs or Xeon Phi accelerators, the sci...
Background: The Smith-Waterman (SW) algorithm is the best choice for searching similar regions betwe...
Background: The Smith-Waterman (SW) algorithm is the best choice for searching similar regions betwe...
Detecting similarities between (RNA, DNA, and protein) sequences is an important part of bioinformat...
Biosequence alignment recently received an amazing support from both commodity and dedicated hardwar...
Abstract Background To infer homology and subsequentl...
The well-known Smith-Waterman (SW) algorithm is a high-sensitivity method for local alignments. Howe...
The well-known Smith–Waterman (SW) algorithm is the most commonly used method for local sequence ali...
Smith-Waterman is a dynamic programming algorithm that plays a key role in the modern genomics pipel...
Background Smith-Waterman (S-W) algorithm is an optimal sequence alignment method for biological dat...
Rapid evolution in sequencing technologies results in generating data on an enormous scale. A focal ...
BackgroundBioinformatic workflows frequently make use of automated genome assembly and protein clust...
The well-known Smith–Waterman algorithm is a high-sensitivity method for local sequence alignment. U...
The well-known Smith–Waterman algorithm is a high-sensitivity method for local sequence alignment. U...
The well-known Smith-Waterman (SW) algorithm is a high-sensitivity method for local alignments. Unfo...
With the greater importance of parallel architectures such as GPUs or Xeon Phi accelerators, the sci...
Background: The Smith-Waterman (SW) algorithm is the best choice for searching similar regions betwe...
Background: The Smith-Waterman (SW) algorithm is the best choice for searching similar regions betwe...
Detecting similarities between (RNA, DNA, and protein) sequences is an important part of bioinformat...
Biosequence alignment recently received an amazing support from both commodity and dedicated hardwar...
Abstract Background To infer homology and subsequentl...
The well-known Smith-Waterman (SW) algorithm is a high-sensitivity method for local alignments. Howe...
The well-known Smith–Waterman (SW) algorithm is the most commonly used method for local sequence ali...
Smith-Waterman is a dynamic programming algorithm that plays a key role in the modern genomics pipel...
Background Smith-Waterman (S-W) algorithm is an optimal sequence alignment method for biological dat...
Rapid evolution in sequencing technologies results in generating data on an enormous scale. A focal ...
BackgroundBioinformatic workflows frequently make use of automated genome assembly and protein clust...