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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.
