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Bulletin of Mathematical Biology

, Volume 46, Issue 4, pp 553–566 | Cite as

Algorithms for computing evolutionary similarity measures with length independent gap penalties

  • M. L. Fredman
Article

Abstract

We give algorithms for computing the extent of similarity between two or three sequences of letters. The similarity measures we consider include a penalty for inserting gaps within the sequence in order to enhance similarity. The magnitude of the penalty for gaps is assumed to be independent of their size in order to accommodate certain biological applications. Our algorithm for three sequence comparisons, which is based on solving a system of recursive equations, improves upon the efficiency of existing methods. Although the system of recursive equations utilized by the algorithm is quite complicated as it stands, it has none the less been simplified by appeal to combinatorial considerations.

Keywords

Similarity Measure Dynamic Programming Algorithm Normal Sequence Recursive Equation 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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Literature

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Copyright information

© Society for Mathematical Biology 1984

Authors and Affiliations

  • M. L. Fredman
    • 1
  1. 1.Department of Electrical Engineering and Computer SciencesUniversity of CaliforniaSan Diego, La JollaU.S.A.

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