Approximation algorithms for multiple sequence alignment
Theoretical Computer Science
Proof verification and the hardness of approximation problems
Journal of the ACM (JACM)
The NPO-completeness of the longest Hamiltonian cycle problem
Information Processing Letters
The complexity of multiple sequence alignment with SP-score that is a metric
Theoretical Computer Science
Complexity and Approximation: Combinatorial Optimization Problems and Their Approximability Properties
Current Topics in Computational Molecular Biology
Current Topics in Computational Molecular Biology
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Algorithms and complexity for annotated sequence analysis
Algorithms and complexity for annotated sequence analysis
Efficient algorithms for regular expression constrained sequence alignment
CPM'06 Proceedings of the 17th Annual conference on Combinatorial Pattern Matching
Regular expression constrained sequence alignment
CPM'05 Proceedings of the 16th annual conference on Combinatorial Pattern Matching
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Imposing constraints is a way to incorporate information into the sequence alignment procedure. In this paper, a general model for constrained alignment is proposed so that analyses admitted are more flexible and that different pattern definitions can be treated in a simple unified way. We give a polynomial time algorithm for pairwise constrained alignment for the generalized formulation, and prove the inapproximability of the problem when the number of sequences can be arbitrary. In addition, previous works deal only with the case that the patterns in the constraint have to occur in the output alignment in the same order as that specified by the input. It is of both theoretical and practical interest to investigate the case when the order is no longer limited. We show that the problem is not approximable even when the number of sequences is two. We also give the NPO-completeness results for the problems with bounds imposed on the objective function value.