• DocumentCode
    1004224
  • Title

    Improved Approximation Algorithms for Reconstructing the History of Tandem Repeats

  • Author

    Chen, Zhi-Zhong ; Wang, Lusheng

  • Author_Institution
    Dept. of Math. Sci., Tokyo Denki Univ., Hatoyama, Japan
  • Volume
    6
  • Issue
    3
  • fYear
    2009
  • Firstpage
    438
  • Lastpage
    453
  • Abstract
    Some genetic diseases in human beings are dominated by short sequences repeated consecutively called tandem repeats. Once a region containing tandem repeats is found, it is of great interest to study the history of creating the repeats. The computational problem of reconstructing the duplication history of tandem repeats has been studied extensively in the literature. Almost all previous studies focused on the simplest case where the size of each duplication block is 1. Only recently we succeeded in giving the first polynomial-time approximation algorithm with a guaranteed ratio for a more general case where the size of each duplication block is at most 2; the algorithm achieves a ratio of 6 and runs in O(n11) time. In this paper, we present two new polynomial-time approximation algorithms for this more general case. One of them achieves a ratio of 5 and runs in O(n9) time, while the other achieves a ratio of 2.5+ isin for any constant isin > 0 but runs slower.
  • Keywords
    diseases; genetics; genomics; polynomial approximation; duplication history reconstruction; genetic diseases; genomes; guaranteed ratio; polynomial-time approximation algorithms; tandem repeats; Approximation Algorithms; Computational biology; Computations on discrete structures; Duplication History of Tandem Repeats; Trees; approximation algorithms.; Algorithms; Computational Biology; Evolution, Molecular; Models, Genetic; Tandem Repeat Sequences;
  • fLanguage
    English
  • Journal_Title
    Computational Biology and Bioinformatics, IEEE/ACM Transactions on
  • Publisher
    ieee
  • ISSN
    1545-5963
  • Type

    jour

  • DOI
    10.1109/TCBB.2008.122
  • Filename
    4685890