• DocumentCode
    3091788
  • Title

    A parallel Smith-Waterman algorithm based on divide and conquer

  • Author

    Zhang, Fa ; QIAO, Xiang-Zhen ; Liu, Zhi-Yong

  • Author_Institution
    Inst. of Comput. Technol., Acad. Sinica, Beijing, China
  • fYear
    2002
  • fDate
    23-25 Oct. 2002
  • Firstpage
    162
  • Lastpage
    169
  • Abstract
    Biological sequence comparison is an important tool for researchers in molecular biology. There are several algorithms for sequence comparison. The Smith-Waterman algorithm, based on dynamic programming, is one of the most fundamental algorithms in bioinformatics. However, the existing parallel Smith-Waterman algorithm needs large memory space. As the data of biological sequences expand rapidly, the memory requirement of the existing parallel Smith-Waterman algorithm has becoming a critical problem. For resolving this problem, we develop a new parallel Smith-Waterman algorithm using the method of divide and conquer, named PSW-DC. Memory space required in the new parallel algorithm is reduced significantly in comparison with existing ones. A key technique, named the C&E method, is developed for implementation of the new parallel Smith-Waterman algorithm.
  • Keywords
    biology computing; divide and conquer methods; dynamic programming; molecular biophysics; parallel algorithms; sequences; C&E method; PSW-DC; bioinformatics; biological sequence comparison; divide and conquer; dynamic programming; memory space; molecular biology; parallel Smith-Waterman algorithm; Biology computing; Computers; Concurrent computing; Data analysis; Databases; Dynamic programming; Heuristic algorithms; High performance computing; Parallel algorithms; Sequences;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Algorithms and Architectures for Parallel Processing, 2002. Proceedings. Fifth International Conference on
  • Conference_Location
    Beijing, China
  • Print_ISBN
    0-7695-1512-6
  • Type

    conf

  • DOI
    10.1109/ICAPP.2002.1173568
  • Filename
    1173568