Multiple alignment, communication cost, and graph matching
SIAM Journal on Applied Mathematics
Approximation algorithms for multiple sequence alignment
Theoretical Computer Science
Algorithms on strings, trees, and sequences: computer science and computational biology
Algorithms on strings, trees, and sequences: computer science and computational biology
The complexity of multiple sequence alignment with SP-score that is a metric
Theoretical Computer Science
CSB '02 Proceedings of the IEEE Computer Society Conference on Bioinformatics
Efficient Constrained Multiple Sequence Alignment with Performance Guarantee
CSB '03 Proceedings of the IEEE Computer Society Conference on Bioinformatics
Bit-Parallel Algorithm for the Constrained Longest Common Subsequence Problem
Fundamenta Informaticae
Solving longest common subsequence and related problems on graphical processing units
Software—Practice & Experience
Regular language constrained sequence alignment revisited
IWOCA'10 Proceedings of the 21st international conference on Combinatorial algorithms
Guided forest edit distance: better structure comparisons by using domain-knowledge
CPM'07 Proceedings of the 18th annual conference on Combinatorial Pattern Matching
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In this paper, we study the constrained sequence alignment problem, which is a generalization of the classical sequence alignment problem with the additional constraint that some characters in the alignment must be positioned at the same columns. The problem finds important applications in Bioinformatics. Our major result is an O(ℓn2)-time and O(ℓn)-space algorithm for constructing an optimal constrained alignment of two sequences where n is the length of the longer sequence and ℓ is the length of the constraint. Our algorithm matches the best known time complexity and reduces the best known space complexity by a factor of n for solving the problem. We also apply our technique to design time and space efficient heuristic and approximation algorithm for aligning multiple sequences.