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摘要
Designing computational codeword is crucial in DNA computing. However, this is a bothersome task as too many constraints need to be satisfied in terms of definiting of encoding problem. This paper proves that the problem of finding the maximum number of computational codeword in a randomly generated set of DNA sequences is not only NP-hard, but it can also be mapped onto the solution of a graph of maximum clique problem. Thus, utilizing meta-heuristic algorithm to find an optimal or near optimal solution and predestinating whether or not the computational codeword in randomly generated set are required for the following controllable computation. Here we present an improved Hopfield neural network algorithm to solve this problem. The simulation results show that the proposed method is useful for a user to select an appropriate set of candidate DNA sequences to filter and obtain good computational codeword.
