A fundamental problem in coding theory concerns the computation of the maximum cardinality of a set S of length n code words over an alphabet of size q, such that every pair of code words has Hamming distance at least d, and the set of additional constraints U on S is satisfied. This problem has application in several areas, one of which is the design of DNA codes where q = 4 and the alphabet is {A, C, G, T}. We describe a new constraint model for this problem and demonstrate that it improves on previous solutions (computes better lower bounds) for various instances of the problem. Our approach is based on a clustering of DNA words into small sets of words. Solutions are then obtained as the union of such clusters. Our approach is SAT based: we specify constraints on clusters of DNA words and solve these using a Boolean satisfiability solver.
CITATION STYLE
Codish, M., Frank, M., & Lagoon, V. (2017). The DNA word design problem: A new constraint model and new results. In IJCAI International Joint Conference on Artificial Intelligence (Vol. 0, pp. 585–591). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2017/82
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