Finding similar regions in many strings
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
Efficient approximation algorithms for the Hamming center problem
Proceedings of the tenth annual ACM-SIAM symposium on Discrete algorithms
A Linear-Time Algorithm for the 1-Mismatch Problem
WADS '97 Proceedings of the 5th International Workshop on Algorithms and Data Structures
Banishing Bias from Consensus Sequences
CPM '97 Proceedings of the 8th Annual Symposium on Combinatorial Pattern Matching
Distinguishing string selection problems
Information and Computation
On the Optimality of the Dimensionality Reduction Method
FOCS '06 Proceedings of the 47th Annual IEEE Symposium on Foundations of Computer Science
On the Structure of Small Motif Recognition Instances
SPIRE '08 Proceedings of the 15th International Symposium on String Processing and Information Retrieval
Efficient Algorithms for the Closest String and Distinguishing String Selection Problems
FAW '09 Proceedings of the 3d International Workshop on Frontiers in Algorithmics
Exact Solutions for Closest String and Related Problems
ISAAC '01 Proceedings of the 12th International Symposium on Algorithms and Computation
More Efficient Algorithms for Closest String and Substring Problems
SIAM Journal on Computing
On the hardness of counting and sampling center strings
SPIRE'10 Proceedings of the 17th international conference on String processing and information retrieval
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
A three-string approach to the closest string problem
Journal of Computer and System Sciences
Slightly superexponential parameterized problems
Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete Algorithms
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We present the first parameterized enumeration algorithm for the neighbour string problem, where a neighbour string of n input strings, each of length ℓ, is a string that differs from input si in no more than di positions. The problem is NP-complete even when the di's are equal; this is the well-known closest string problem. Our new approach gives us the ability to tune the running time to optimize the algorithm for varying relative values of n and d= max idi. For strings over an alphabet Σ, we can choose a tuning constant λ to obtain an algorithm that runs in time O(nℓ+(nd)f(λ)(|Σ|−1)d 5(1+λ)d), where f is a function that decreases with increasing λ. When Σ={0,1}, the dependency on d is an asymptotic improvement over the previous best parameterized time bound of O(nℓ+nd3 6.7308d) for finding a single solution.