A DNA-based solution to the graph isomorphism problem using Adleman-Lipton model with stickers

Since the experimental demonstration of its feasibility, DNA-based computing has been applied to a number of decision or combinatorial optimization problems. The graph isomorphism problem belongs to the class of NP problems, and has been conjectured intractable, although probably not NP-complete. In this paper, we demonstrate the power of DNA-based computing by showing the graph isomorphism problem can be efficiently solved under this computation model. By generating the solution space using stickers, we present DNA-based algorithms to solve the problem using polynomial number of basic biological operations.