Speeding up subset seed algorithm for intensive protein sequence comparison

Author

Nguyen, Van Hoa ; Lavenier, Dominique

Author_Institution

IRISA/INRIA, Rennes

fYear

2008

fDate

13-17 July 2008

Firstpage

57

Lastpage

63

Abstract

Sequence similarity search is a common and repeated task in molecular biology. The rapid growth of genomic databases leads to the need of speeding up the treatment of this task. In this paper, we present a subset seed algorithm for intensive protein sequence comparison. We have accelerated this algorithm by using indexing technique and fine grained parallelism of GPU and SIMD instructions. We have implemented two programs: iBLASTP, iTBLASTN. The GPU (SIMD) implementation of the two programs achieves a speed up ranging from 5.5 to 10 (4 to 5.6) compared to the BLASTP and TBLASTN of the BLAST program family, with comparable sensitivity.

Keywords

biology computing; genetics; molecular biophysics; parallel processing; proteins; BLAST program family; GPU instruction; SIMD instruction; genomic database; iBLASTP program; iTBLASTN program; intensive protein sequence; molecular biology; subset seed algorithm; Acceleration; Bioinformatics; Biotechnology; DNA; Databases; Genomics; Indexing; Parallel processing; Protein sequence; Sequences;

fLanguage

English

Publisher

ieee

Conference_Titel

Research, Innovation and Vision for the Future, 2008. RIVF 2008. IEEE International Conference on

Conference_Location

Ho Chi Minh City

Print_ISBN

978-1-4244-2379-8

Electronic_ISBN

978-1-4244-2380-4

Type

conf

DOI

10.1109/RIVF.2008.4586333

Filename

4586333