G-BLASTN: accelerating nucleotide alignment by graphics processors | Zendy

Kaiyong Zhao | Zendy; Xiaowen Chu | Zendy

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G-BLASTN: accelerating nucleotide alignment by graphics processors

Author(s) -

Kaiyong Zhao,

Xiaowen Chu

Publication year - 2014

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btu047

Subject(s) - speedup , computer science , software , pipeline (software) , graphics , cuda , parallel computing , multiple sequence alignment , sequence (biology) , mode (computer interface) , sequence alignment , multi core processor , similarity (geometry) , operating system , artificial intelligence , biology , peptide sequence , biochemistry , genetics , gene , image (mathematics)

Since 1990, the basic local alignment search tool (BLAST) has become one of the most popular and fundamental bioinformatics tools for sequence similarity searching, receiving extensive attention from the research community. The two pioneering papers on BLAST have received over 96 000 citations. Given the huge population of BLAST users and the increasing size of sequence databases, an urgent topic of study is how to improve the speed. Recently, graphics processing units (GPUs) have been widely used as low-cost, high-performance computing platforms. The existing GPU-BLAST is a promising software tool that uses a GPU to accelerate protein sequence alignment. Unfortunately, there is still no GPU-accelerated software tool for BLAST-based nucleotide sequence alignment.

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