TY - GEN
T1 - Design automation of polyomino set that self-assembles into a desired shape
AU - Matsumura, Yuta
AU - Kawamata, Ibuki
AU - Murata, Satoshi
N1 - Publisher Copyright:
© Yuta Matsumura, Ibuki Kawamata, and Satoshi Murata; licensed under Creative Commons License CC-BY.
PY - 2020/9/1
Y1 - 2020/9/1
N2 - The problem of finding the smallest DNA tile set that self-assembles into a desired pattern or shape is a research focus that has been investigated by many researchers. In this paper, we take a polyomino, which is a non-square element composed of several connected square units, as an element of assembly and consider the design problem of the minimal set of polyominoes that self-assembles into a desired shape. We developed a self-assembly simulator of polyominoes based on the agent-based Monte Carlo method, in which the potential energy among the polyominoes is evaluated and the simulation state is updated toward the direction to decrease the total potential. Aggregated polyominoes are represented as an agent, which can move, merge, and split during the simulation. In order to search the minimal set of polyominoes, two-step evaluation strategy is adopted, because of enormous search space including many parameters such as the shape, the size, and the glue types attached to the polyominoes. The feasibility of the proposed method is shown through three examples with different size and complexity.
AB - The problem of finding the smallest DNA tile set that self-assembles into a desired pattern or shape is a research focus that has been investigated by many researchers. In this paper, we take a polyomino, which is a non-square element composed of several connected square units, as an element of assembly and consider the design problem of the minimal set of polyominoes that self-assembles into a desired shape. We developed a self-assembly simulator of polyominoes based on the agent-based Monte Carlo method, in which the potential energy among the polyominoes is evaluated and the simulation state is updated toward the direction to decrease the total potential. Aggregated polyominoes are represented as an agent, which can move, merge, and split during the simulation. In order to search the minimal set of polyominoes, two-step evaluation strategy is adopted, because of enormous search space including many parameters such as the shape, the size, and the glue types attached to the polyominoes. The feasibility of the proposed method is shown through three examples with different size and complexity.
KW - Agent based simulation
KW - Combinatorial optimization
KW - DNA nanostructure
KW - DNA polyomino
KW - DNA tile
KW - Self-assembly
KW - Simulated annealing
UR - http://www.scopus.com/inward/record.url?scp=85092768367&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85092768367&partnerID=8YFLogxK
U2 - 10.4230/LIPIcs.DNA.2020.8
DO - 10.4230/LIPIcs.DNA.2020.8
M3 - Conference contribution
AN - SCOPUS:85092768367
T3 - Leibniz International Proceedings in Informatics, LIPIcs
BT - 26th International Conference on DNA Computing and Molecular Programming, DNA 2020
A2 - Gear, Cody
A2 - Patitz, Matthew J.
PB - Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
T2 - 26th International Conference on DNA Computing and Molecular Programming, DNA 2020
Y2 - 14 September 2020 through 17 September 2020
ER -