• 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