Many bioinformatics applications, such as the optimal pairwise biological sequence
comparison, demand a great quantity of computing resource, thus are excellent candidates …

Regular expression pattern matching is the foundation and core engine of many network
functions, such as network intrusion detection, worm detection, traffic analysis, web …

This paper proposes and evaluates CUDAlign 4.0, a parallel strategy to obtain the optimal
alignment of huge DNA sequences in multi-GPU platforms, using the exact Smith–Waterman …

In Genome Projects, biological sequences are aligned thousands of times, in a daily basis.
The Smith-Waterman algorithm is able to retrieve the optimal local alignment with quadratic …

For biological applications, sequence alignment is an important strategy to analyze DNA
and protein sequences. Multiple sequence alignment is an essential methodology to study …

As an optimal method for sequence alignment, the Smith-Waterman (SW) algorithm is widely
used. Unfortunately, this algorithm is computationally demanding, especially for long …

We propose SW#, a new CUDA graphical processor unit-enabled and memory-efficient
implementation of dynamic programming algorithm, for local alignment. It can be used as …

Computing edit distance for very long strings has been hampered by quadratic time
complexity with respect to string length. The WFA algorithm reduces the time complexity to a …

Cross-species chromosome alignments can reveal ancestral relationships and may be used
to identify the peculiarities of the species. It is thus an important problem in Bioinformatics …

Multiple sequence alignment (MSA) constitutes an extremely powerful tool for many
biological applications including phylogenetic tree estimation, secondary structure …