DocumentCode
2995257
Title
Parallelization of BLAST with MapReduce for Long Sequence Alignment
Author
Yang, Xiao-liang ; Liu, Yu-long ; Yuan, Chun-feng ; Huang, Yi-hua
Author_Institution
Dept. of Comput. Sci. & Technol., Nanjing Univ., Nanjing, China
fYear
2011
fDate
9-11 Dec. 2011
Firstpage
241
Lastpage
246
Abstract
Sequence alignment is of great importance in biology research. BLAST is a sequence alignment tool used extensively by researchers. However the continuously increasing amount of sequence data to be processed presents many challenges to it. This paper gives a simple and effective approach to parallelizing BLAST using the MapReduce technique. The MapReduce-BLAST shows very good performance and scales nearly linearly to the database size and query length. This results from both the power of MapReduce and the inherent parallel characteristics of the BLAST algorithm. Sequence alignment algorithms based on techniques similar with BLAST´s seed-and-extend approach are very suitable for being parallelized with MapReduce.
Keywords
bioinformatics; data handling; database management systems; parallel processing; query processing; BLAST parallelization; MapReduce technique; bioinformatics; biology research; database size; long sequence alignment algorithm; query length; sequence data; Automata; Bioinformatics; DNA; Databases; Graphics processing unit; Proteins; Scalability; BLAST; Hadoop; MapReduce; long sequence alignment; parallelization;
fLanguage
English
Publisher
ieee
Conference_Titel
Parallel Architectures, Algorithms and Programming (PAAP), 2011 Fourth International Symposium on
Conference_Location
Tianjin
Print_ISBN
978-1-4577-1808-3
Type
conf
DOI
10.1109/PAAP.2011.36
Filename
6128510
Link To Document