The program-size complexity of self-assembled squares (extended abstract)
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
Combinatorial optimization problems in self-assembly
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
Algorithmic self-assembly of dna
Algorithmic self-assembly of dna
Theory and experiments in algorithmic self-assembly
Theory and experiments in algorithmic self-assembly
Strict self-assembly of discrete Sierpinski triangles
Theoretical Computer Science
On the computational complexity of tile set synthesis for DNA self-assembly
IEEE Transactions on Circuits and Systems II: Express Briefs
Synthesis of Tile Sets for DNA Self-Assembly
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
One-dimensional staged self-assembly
DNA'11 Proceedings of the 17th international conference on DNA computing and molecular programming
Synthesizing small and reliable tile sets for patterned DNA self-assembly
DNA'11 Proceedings of the 17th international conference on DNA computing and molecular programming
Theory of algorithmic self-assembly
Communications of the ACM
An introduction to tile-based self-assembly
UCNC'12 Proceedings of the 11th international conference on Unconventional Computation and Natural Computation
One-dimensional staged self-assembly
Natural Computing: an international journal
Synthesizing minimal tile sets for complex patterns in the framework of patterned DNA self-assembly
Theoretical Computer Science
Search methods for tile sets in patterned DNA self-assembly
Journal of Computer and System Sciences
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The Pattern self-Assembly Tile set Synthesis (PATS) problem is to determine a set of coloured tiles that self-assemble to implement a given rectangular colour pattern. We give an exhaustive branch-and-bound algorithm to find tile sets of minimum cardinality for the PATS problem. Our algorithm makes use of a search tree in the lattice of partitions of the ambient rectangular grid, and an efficient bounding function to prune this search tree. Empirical data on the performance of the algorithm shows that it compares favourably to previously presented heuristic solutions to the problem.