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. © 2010 Springer-Verlag.
CITATION STYLE
Hufsky, F., Kuchenbecker, L., Jahn, K., Stoye, J., & Böcker, S. (2010). Swiftly computing center strings. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6293 LNBI, pp. 325–336). https://doi.org/10.1007/978-3-642-15294-8_27
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