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Efficient Algorithms for Local Alignment Search

Author

Listed:
  • S. Rajasekaran

    (University of Florida)

  • H. Nick

    (University of Florida)

  • P.M. Pardalos

    (University of Florida)

  • S. Sahni

    (University of Florida)

  • G. Shaw

    (University of Florida)

Abstract

We present efficient algorithms for local alignment search in biological sequences. These algorithms identify maximal segment pairs (MSPs). Our algorithms have the potential of performing better than BLAST (Basic Local Alignment Search Tool) and also are efficiently parallelizable. We employ Fast Fourier Transforms (FFTs). Though several attempts have been made in the past to employ FFTs in sequence analysis, they fail to capture local similarities. Our algorithms employ FFTs in a novel way to identify local similarities. FFT-based techniques have the attractive feature of benefiting from ultrafast special purpose hardware available for digital signal processing.

Suggested Citation

  • S. Rajasekaran & H. Nick & P.M. Pardalos & S. Sahni & G. Shaw, 2001. "Efficient Algorithms for Local Alignment Search," Journal of Combinatorial Optimization, Springer, vol. 5(1), pages 117-124, March.
    • Handle: RePEc:spr:jcomop:v:5:y:2001:i:1:d:10.1023_a:1009893719470
    DOI: 10.1023/A:1009893719470
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    Cited by:

    1. Blum, Christian & Lozano, José A. & Davidson, Pinacho, 2015. "Mathematical programming strategies for solving the minimum common string partition problem," European Journal of Operational Research, Elsevier, vol. 242(3), pages 769-777.

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