Approximation algorithms for multiple sequence alignment

  • Vineet Bafna
  • Eugene L. Lawler
  • Pavel A. Pevzner
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 807)


We consider the problem of aligning of k sequences of length n. The cost function is sum of pairs, and satisfies triangle inequality. Earlier results on finding approximation algorithms for this problem are due to Gusfield, 1991, who achieved an approximation ratio of 2 − 2/k, and Pevzner, 1992, who improved it to 2 − 3/k. We generalize this approach to assemble an alignment of k sequences from optimally aligned subsets of l<k sequences to obtain an improved performance guarantee. For arbitrary l<k, we devise deterministic and randomized algorithms yielding performance guarantees of 2−l/k. For fixed l, the running times of these algorithms are polynomial in n and k.


Multiple Sequence Alignment Pairwise Alignment Performance Guarantee Center Vertex Computer Science Division 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 1994

Authors and Affiliations

  • Vineet Bafna
    • 1
  • Eugene L. Lawler
    • 2
  • Pavel A. Pevzner
    • 1
  1. 1.Department of CSEThe Pennsylvania State UniversityUniversity Park
  2. 2.Computer Science DivisionUniversity of CaliforniaBerkeley

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