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Comparison of coding DNA

  • Christian N. S. Pedersen
  • Rune Lyngsø
  • Jotun Hein
Session IV
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1448)

Abstract

We discuss a model for the evolutionary distance between two coding DNA sequences which specializes to the DNA/protein model proposed in Hein [4]. We discuss the DNA/protein model in details and present a quadratic time algorithm that computes an optimal alignment of two coding DNA sequences in the model under the assumption of affine gap cost. The algorithm solves a conjecture in [4] and we believe that the constant factor of the running time is sufficiently small to make the algorithm feasible in practice.

Keywords

Alignment Algorithm Optimal Alignment Table Entry Level Cost Eleven Type 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    L. Arvestad. Aligning coding DNA in the presence of frame-shift errors. In Proceedings of the 8th Annual Symposium of Combinatorial Pattern Matching (CPM 97), volume 1264 of Lecture Notes in Computer Science, pages 180–190, 1997.Google Scholar
  2. 2.
    R. Durbin, R. Eddy, A. Krogh, and G. Mitchison. Biological Sequence Analysis: Probalistic Models of Proteins and Nucleic Acids. Cambrigde University Press, 1998.Google Scholar
  3. 3.
    O. Gotoh. An improved algorithm for matching biological sequences. Journal of Molecular Biology, 162:705–708, 1981.Google Scholar
  4. 4.
    J. Hein. An algorithm combining DNA and protein alignment. Journal of Theoretical Biology, 167:169–174, 1994.Google Scholar
  5. 5.
    J. Hein and J. Støvlbaek. Genomic alignment. Journal of Molecular Evolution, 38:310–316, 1994.Google Scholar
  6. 6.
    J. Hein and J. Støvlbæk. Combined DNA and protein alignment. Methods in Enzymology, 266:402–418, 1996.Google Scholar
  7. 7.
    D. S. Hirschberg. A linear space algortihm for computing maximal common subseqeunce. Communication of the ACM, 18(6):341–343, 1975.Google Scholar
  8. 8.
    Y. Hua, T. Jiang, and B. Wu. Aligning DNA sequences to minimize the change in protein. Accepted for CPM 98.Google Scholar
  9. 9.
    S. B. Needleman and C. D. Wunsch. A general method applicable to the search for similarities in the amino acid seqeunce of two proteins. Journal of Molecular Biology, 48:433–443, 1970.Google Scholar
  10. 10.
    H. Peltola, H. Söderlund, and E. Ukkonen. Algorithms for the search of amino acid patterns in nucleic acid sequences. Nuclear Acids Research, 14(1):99–107, 1986.Google Scholar
  11. 11.
    D. Sankoff. Matching sequences under deletion /insertion constraints. In Proceedings of the National Acadamy of Science USA, volume 69, pages 4–6, 1972.Google Scholar
  12. 12.
    P. H. Sellers. On the theory and computation of evolutionary distance. SIAM Journal of Applied Mathematics, 26:787–793, 1974.Google Scholar
  13. 13.
    R. A. Wagner and M. J. Fisher. The string to string correction problem. Journal of the ACM, 21:168–173, 1974.Google Scholar
  14. 14.
    Z. Zhang, W. R. Pearson, and W. Miller. Aligning a DNA sequence with a protein sequence. Journal of Computational Biology, 4(3):339–349, Fall 1997.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Christian N. S. Pedersen
    • 1
  • Rune Lyngsø
    • 1
  • Jotun Hein
    • 2
  1. 1.BRICS, Department of Computer ScienceUniversity of AarhusÅrhus CDenmark
  2. 2.Department of Ecology and GeneticsUniversity of AarhusÅrhus CDenmark

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