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On locally optimal alignments in genetic sequences

  • Norbert Blum
Conference paper
  • 116 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 577)

Abstract

A substring \(\tilde x\) of a text string x has c-locally minimal distance from a pattern string y, c ε N ∪ {0}, if no other substring x′ of x with smaller edit distance to y exists which overlaps \(\tilde x\) by more than c characters. We show how to compute all substrings of x which have c- locally minimal distance from y and all corresponding alignments in O(m · n) time where n is the length of x and m is the length of y.

Keywords

Minimal Distance Optimal Path Edit Distance Distance Graph Optimal Alignment 
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]
    Aho, A. V., Hopcroft, J. E., and Ullman, J. D. [1974]. The Design and Analysis of Computer Algorithms, Addison-Wesley, Reading, Mass.Google Scholar
  2. [2]
    Blum, N. [1991]. On locally optimal alignments in genetic sequences, Research Report 8567-CS, Dept. of Computer Science, University of Bonn.Google Scholar
  3. [3]
    Masek, W. J., and Paterson, M. S. [1980]. A faster algorithm for computing string-edit distances. Journal of Computer and System Sciences 20, 18–31.Google Scholar
  4. [4]
    Myers, E. W. [1986]. An O(ND) difference algorithm and its variations. Algorithmica 1, 251–266.Google Scholar
  5. [5]
    Needleman, S. B., and Wunsch, C. D. [1970]. A general method applicable to the search for similarities in the amino-acid sequence of two proteins. Journal of Molecular Biology 48, 443–453.Google Scholar
  6. [6]
    Sankoff, D., and Kruskal, J. B. (eds.) [1983]. Time Warps, String Edits, and Macromolecules: The Theory and Practice of Sequence Comparison. Addison-Wesley, Reading, Mass.Google Scholar
  7. [7]
    Sellers, P. H. [1980]. The theory and computation of evolutionary distances: Pattern recognition. Journal of Algorithms 1, 359–373.Google Scholar
  8. [8]
    Ukkonen, E. [1985]. Algorithms for approximate string matching. Information and Control 64, 100–118.Google Scholar
  9. [9]
    Waterman, M. S. [1984]. General methods of sequence comparison. Bulletin of Mathematical Biology 46, 473–500.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • Norbert Blum
    • 1
  1. 1.Informatik IVUniversität BonnBonnF. R. Germany

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