Advertisement

Improved approximation algorithms for tree alignment

  • Lusheng Wang
  • Dan Gusfield
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1075)

Abstract

Multiple sequence alignment is a task at the heart of much of current computational biology [4]. Several different objective functions have been proposed to formalize the task of multiple sequence alignment, but efficient algorithms are lacking in each case. Thus multiple sequence alignment is one of the most critical, essentially unsolved problems in computational biology. In this paper we consider one of the more compelling objective functions for multiple sequence alignment, formalized as the tree alignment problem. Previously in [15], a factor-of-two approximation method was developed for tree alignment, which ran in cubic time (as a function of the number of fixed length strings to be aligned), along with a polynomial time approximation scheme (PTAS) for the problem. However, the PTAS in [15] had a running time which made it impractical to reduce the error bound much below two for small size biological sequences (100 characters long).

In this paper we first develop a factor-of-two approximation algorithm which runs in quadratic time, and then use it to develop a PTAS which has a smaller guaranteed error bound and a vastly improved worst case running time compared to the scheme in [15]. With the new approximation scheme, it is now practical to guarantee an error bound of 1.583 for strings of lengths 200 characters or less.

Key words

tree alignment approximation algorithm and polynomial time approximation scheme 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    S. Altschul and D. Lipman, Trees, stars, and multiple sequence alignment, SIAM Journal on Applied Math. 49, pp. 197–209, 1989Google Scholar
  2. 2.
    S. C. Chan, A. K. C. Wong and D. K. T. Chiu, A survey of multiple sequence comparison methods, Bulletin of Mathematical Biology 54(4), pp. 563–598, 1992.PubMedGoogle Scholar
  3. 3.
    S.K. Gupta, J. D. Kececioglu, and A. A. Schaffer, Making the shortest-paths approach to sum-of-pairs multiple sequence alignment more space efficient in practice, CPM95, pp. 128–143.Google Scholar
  4. 4.
    D. Gusfield, Efficient methods for multiple sequence alignment with guaranteed error bounds, Bulletin of Mathematical Biology 55, pp. 141–154, 1993.PubMedGoogle Scholar
  5. 5.
    J. J. Hein, A new method that simultaneously aligns and reconstructs ancestral sequences for any number of homologous sequences, when the phylogeny is given, Mol. Biol. Evol. 6(6), pp. 649–668, 1989.PubMedGoogle Scholar
  6. 6.
    D. J. Lipman, S. F. Altschul, and J. D. Kececioglu, A tool for multiple sequence alignment. Proc. Natl. Acad. Sci. USA., 86:4412–4415, 1989.PubMedGoogle Scholar
  7. 7.
    R. Ravi and J. Kececioglu, Approximation algorithms for multiple sequence alignment under a fixed evolutionary tree, CPM95, pp. 330–339.Google Scholar
  8. 8.
    D. Sankoff, Minimal mutation trees of sequences, SIAM J. Applied Math. 28(1), pp. 35–42, 1975.Google Scholar
  9. 9.
    D. Sankoff, R. J. Cedergren and G. Lapalme, Frequency of insertion-deletion, transversion, and transition in the evolution of 5S ribosomal RNA, J. Mol. Evol. 7, pp. 133–149, 1976.PubMedGoogle Scholar
  10. 10.
    D. Sankoff and R. Cedergren, Simultaneous comparisons of three or more sequences related by a tree, In D. Sankoff and J. Kruskal, editors, Time warps, string edits, and macromolecules: the theory and practice of sequence comparison, pp. 253–264, Addison Wesley, 1983.Google Scholar
  11. 11.
    D. Sankoff and J. Kruskal, Time warps, string edits, and macromolecules: the theory and practice of sequence comparison, Addison Wesley, 1983Google Scholar
  12. 12.
    R. Ravi and J. kececioglu, Approximation algorithms for multiple sequence alignment under a fixed evolutionary tree, CPM95, pp. 330–339.Google Scholar
  13. 13.
    M.S. Waterman and M.D. Perlwitz, Line geometries for sequence comparisons”, Bull. Math. Biol. 46, pp. 567–577, 1984.Google Scholar
  14. 14.
    L. Wang and T. Jiang, On the complexity of multiple sequence alignment, Journal of Computational Biology, vol. 1, pp. 337–348, 1994.PubMedGoogle Scholar
  15. 15.
    L.Wang, T. Jiang, and E.L. Lawler, Aligning sequences via an evolutionary tree: complexity and approximation, Algorithmica, to appear; also presented at the 26th ACM Symp. on Theory of Computing, 1994.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • Lusheng Wang
    • 1
  • Dan Gusfield
    • 1
  1. 1.Department of Computer ScienceUniversity of CaliforniaDavis

Personalised recommendations