Abstract
The tile assembly model is a novel biological computing model where information is encoded in DNA tiles. It is an efficient way to solve NP-complete problems due to its scalability and parallelism. In this paper, we apply the tile assembly model to solve the minimum and exact set cover problems, which are well-known NP-complete problems. To solve the minimum set cover problem, we design a MinSetCover system composed of three parts, i.e., the seed configuration subsystem, the nondeterministic choice subsystem, and the detection subsystem. Moreover, we improve the MinSetCover system and propose a MinExactSetCover system for solving the problem of exact cover by 3-sets. Finally we analyze the computation complexity and perform a simulation experiment to verify the effectiveness and correctness of the proposed systems.
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References
Chang WL, Lin KW, Chen JC et al (2012) Molecular solutions of the RSA public-key cryptosystem on a DNA-based computer. J Supercomput 61(3):642–672
Chang WL (2012) Fast parallel DNA-based algorithm for molecular computation: quadratic congruence and factoring integers. IEEE Trans Nanobiosci 11(1):62–69
Chang WL, Huang SC, Lin WC et al (2011) Fast parallel DNA-based algorithms for molecular computation: discrete logarithm. J Supercomput 56:129–163
Jin X, Xiaoli Q, Yan Y et al (2011) An unenumerative DNA computing model for vertex coloring problem. IEEE Trans Nanobiosci 10(2):94–98
Li K, Zou S, Xu J (2008) Fast parallel molecular algorithms for DNA-based computation: solving the elliptic curve discrete logarithm problem over GF(2n). J Biomed Biotechnol 1:1–10
Zhou Xu, Li Kenli et al (2011) A novel approach for the classical Ramsey number problem on DNA-based super-computing. Match Commun Math Comput Chem 66(1):347–370
Daniel M, Alfonso R-P, Petr S (2011) On the scalability of biocomputing algorithms: the case of the maximum clique problem. Theor Comput Sci 412(51):7075–7086
Bakar RAB, Watada J, Pedrycz W (2008) DNA approach to solve clustering problem based on a mutual order. Biosystems 91(1):1–12
Ikno K, Junzo W, Wutikd P et al (2012) Pattern clustering with statistical methods using a DNA-based algorithm. IEEE Trans Nanobiosci 11(2):100–110
Ikno K, Junzo W (2009) Decision making with an interpretive structural modeling method using a DNA-based algorithm. IEEE Trans Nanobiosci 8(2):181–191
Winfree E (1998) Design and self-assembly of two-dimensional DNA crystals. Nature 394(8):1223–1226
Adleman LM, Cheng Q, Goel A et al (2001) Running time and program size for self-assembled squares. In: Proceedings of the thirty-third annual ACM symposium on theory of computing, STOC 2001, Hersonissos, Greece. ACM, pp 740–748
Summers S (2012) Reducing tile complexity for the self-assembly of scaled shapes through temperature programming. Algorithmica 63:1–20
Woods D, Chen HL, Goodfriend S et al (2013) Active self-assembly of algorithmic shapes and patterns in polylogarithmic time. In: Innovations in theoretical computer science, ITCS 2013, Berkeley, California, January 10–12
Brun Y (2006) Arithmetic computation in the tile assembly model: addition and multiplication. Theor Comput Sci 378:17–31
Brun Y (2008) Solving NP-complete problems in the tile assembly model. Theor Comput Sci 395(1):31–46
Brun Y (2008) Nondeterministic polynomial time factoring in the tile assembly model. Theor Comput Sci 395(1):3–23
Brun Y (2008) Solving satisfiability in the tile assembly model with a constant-size tile set. J Algorithms 63(4):151–166
Zhang XC, Niu Y et al (2009) Application of DNA self-assembly on graph coloring problem. J Comput Theor Nanosci 6(5):1067–1074
Cheng Z, Huang YF et al (2009) Algorithm of solving the subset-product problem based on DNA tile self-assembly. J Comput Theor Nanosci 6(5):1161–1169
Guangzhao C, Cuiling L et al (2009) Application of DNA self-assembly on maximum clique problem. Adv Intell Soft Comput 116:359–368
Jie L, Lei Y, Kenli L (2008) An \(O\)(1.414\(^{n})\) volume molecular solutions for the exact cover problem on DNA-based supercomputing. J Inf Comput Sci 5(1):153–162
Chang WL, Guo M (2003) Solving the set-cover problem and the problem of exact cover by 3-sets in the Adleman–Lipton model. BioSystems 72(2):263–275
Fan Wu, Li Kenli, Sallam Ahmed et al (2013) A molecular solution for minimum vertex cover problem in tile assembly model. J Supercomput 66:148–169
Winfree E The xgrow simulator. http://dna.caltech.edu/Xgrow/
Tsai CC, Huang HC, Lin SC (2011) FPGA-based parallel DNA algorithm for optimal configurations of an omnidirectional mobile service robot performing fire extinguishment. IEEE Trans Ind Electron 58(3):1016–1026
Lulu Q, Erik W, Bruck J (2011) Neural network computation with DNA strand displacement cascades. Nature 475:368–372
Acknowledgments
This research is supported by the key Project of National Natural Science Foundation of China under grant 61133005, the Project of National Natural Science Foundation of China under grant 61173013 and 61202109, the Project of the Office of Education in Zhejiang Province under grant Y201226110.
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Zhou, X., Zhou, Y., Li, K. et al. Molecular solutions for minimum and exact cover problems in the tile assembly model. J Supercomput 69, 976–1005 (2014). https://doi.org/10.1007/s11227-014-1222-x
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DOI: https://doi.org/10.1007/s11227-014-1222-x