A Lagrangian relaxation approach for the multiple sequence alignment problem

Ernst Althaus and Stefan Canzar ()
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Ernst Althaus: Max-Planck Institut für Informatik
Stefan Canzar: Max-Planck Institut für Informatik

Journal of Combinatorial Optimization, 2008, vol. 16, issue 2, No 5, 127-154

Abstract: 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.

Keywords: Sequence comparison; Lagrangian relaxation; Branch and bound (search for similar items in EconPapers)
Date: 2008
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DOI: 10.1007/s10878-008-9139-z

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