Distinguishing string selection problems
Information and Computation
Fast and Practical Algorithms for Planted (l, d) Motif Search
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Efficient Algorithms for the Closest String and Distinguishing String Selection Problems
FAW '09 Proceedings of the 3d International Workshop on Frontiers in Algorithmics
More Efficient Algorithms for Closest String and Substring Problems
SIAM Journal on Computing
Parallel genetic algorithm and parallel simulated annealing algorithm for the closest string problem
ADMA'05 Proceedings of the First international conference on Advanced Data Mining and Applications
A GRASP algorithm for the Closest String Problem using a probability-based heuristic
Computers and Operations Research
Approximations and partial solutions for the consensus sequence problem
SPIRE'11 Proceedings of the 18th international conference on String processing and information retrieval
Configurations and minority in the string consensus problem
SPIRE'12 Proceedings of the 19th international conference on String Processing and Information Retrieval
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The center string (or closest string) problem is a classical computer science problem with important applications in computational biology. Given k input strings and a distance threshold d, we search for a string within Hamming distance d to each input string. This problem is NP-complete. In this paper, we focus on exact methods for the problem that are also fast in application. First, we introduce data reduction techniques that allow us to infer that certain instances have no solution, or that a center string must satisfy certain conditions. Then, we describe a novel search tree strategy that is very efficient in practice. Finally, we present results of an evaluation study for instances from a biological application. We find that data reduction is mandatory for the notoriously difficult case d = dopt - 1.