• DocumentCode
    1577342
  • Title

    Efficient Parallel Algorithm for Optimal Three-Sequences Alignment

  • Author

    Lin, Chun Yuan ; Huang, Chen Tai ; Chung, Yeh-Ching ; Tang, Chuan Yi

  • Author_Institution
    Dept. of Comput. Sci., NTHU, Taipei
  • fYear
    2007
  • Firstpage
    14
  • Lastpage
    14
  • Abstract
    Sequence alignment is a fundamental problem in the computational biology. Many alignment methods have been proposed in the literature, such as pair-wise sequence alignment (2SA), syntenic alignment, multiple sequence alignment (MSA) and constraint multiple sequence alignment, etc. Three-sequence alignment (3SA) problem has been proposed and discussed in the computational biology and proved that the alignment results from 3SA are better than those from 2SA under some conditions. However, 3SA problem is less discussed over the past decade due to the computer capability. 3SA problem now is worthy to discuss due to the powerful computer and more and more genome and protein sequences. In this paper, an efficient parallel algorithm (P3SA) is proposed to solve 3SA problem. The P3SA method requires 0(n2/p) space complexity and 0(n3/p) time complexity. The experimental results show that P3SA algorithm is applicable and achieves a satisfied speed-up.
  • Keywords
    biology computing; computational complexity; dynamic programming; genetics; parallel algorithms; proteins; sequences; computational biology; dynamic programming; genome sequence; optimal three-sequence alignment problem; parallel algorithm; protein sequence; space complexity; time complexity; Bioinformatics; Biology computing; Computational biology; Computer science; Dynamic programming; Genomics; Parallel algorithms; Proteins; Sequences; Testing; Hirschberg´s technique; biology; computational; dynamic programming; sequence alignment; time and space complexities.;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel Processing, 2007. ICPP 2007. International Conference on
  • Conference_Location
    Xi´an
  • ISSN
    0190-3918
  • Print_ISBN
    978-0-7695-2933-2
  • Type

    conf

  • DOI
    10.1109/ICPP.2007.38
  • Filename
    4343821