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 :
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