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A Lagrangian relaxation approach for the multiple sequence alignment problem

Author

Listed:
  • Ernst Althaus

    (Max-Planck Institut für Informatik)

  • Stefan Canzar

    (Max-Planck Institut für Informatik)

Abstract

We present a branch-and-bound (bb) algorithm for the multiple sequence alignment problem (MSA), one of the most important problems in computational biology. The upper bound at each bb node is based on a Lagrangian relaxation of an integer linear programming formulation for MSA. Dualizing certain inequalities, the Lagrangian subproblem becomes a pairwise alignment problem, which can be solved efficiently by a dynamic programming approach. Due to a reformulation w.r.t. additionally introduced variables prior to relaxation we improve the convergence rate dramatically while at the same time being able to solve the Lagrangian problem efficiently. Our experiments show that our implementation, although preliminary, outperforms all exact algorithms for the multiple sequence alignment problem. Furthermore, the quality of the alignments is among the best computed so far.

Suggested Citation

  • Ernst Althaus & Stefan Canzar, 2008. "A Lagrangian relaxation approach for the multiple sequence alignment problem," Journal of Combinatorial Optimization, Springer, vol. 16(2), pages 127-154, August.
    • Handle: RePEc:spr:jcomop:v:16:y:2008:i:2:d:10.1007_s10878-008-9139-z
    DOI: 10.1007/s10878-008-9139-z
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    References listed on IDEAS

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