Programmable Control of Nucleation for Algorithmic Self-Assembly
SIAM Journal on Computing
Search methods for tile sets in patterned DNA self-assembly
Journal of Computer and System Sciences
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Self-assembling DNA complexes have been intensively studied in recent years aiming to achieve bottom-up construction of nanoscale objects. Among them a DNA complex called the DNA tile is known for its high programmability. DNA tiles can form 2-D crystals with programmable patterns via self-assembly. In order to create a wide range of complex objects by algorithmic self-assembly, we need a methodology to predict its behavior. To estimate the behavior, we can use thermodynamic simulations based on the Monte Carlo method. However, the previous simulation model assumed some simplified conditions and was not able to adequately explain the results of crystal growth experiments. Here, we propose the realistic tile assembly model, in which we are able to simulate the detailed conditions of the experimental protocols. By this model, the results of experiments (e.g., error rates, growth rate, and the formation and melting temperatures) are reproduced with high reliability. We think this model is useful to predict the behavior of DNA self-assembly and to design various types of DNA complexes.