Abstract
The computational speed of an algorithm is very important to NP-hard problems. The 3D DNA self-assembly algorithm is faster than 2D, while 2D is faster than traditional algorithms because DNA molecule owns high parallelism and density. In this paper we mainly introduced how the 3D DNA self-assembly solves the SAT problems. Firstly, we introduced a non-deterministic algorithm. Secondly, we designed seed configuration and different types of DNA tiles which are needed in the computation. Lastly, we demonstrated how the 3D DNA self-assembly solves the SAT problem. In this paper, 3D DNA self-assembly algorithm has a constant tile types, and whose computation time is linear.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Wang H (1961) Proving theorems by pattern recognition I. Bell Syst Tech J 40:1–42
Adleman L (1994) Molecular computation of solutions to combinatorial problems. Science 266:1021–1024
Winfree E, Eng T, Rozenberg G (2001) String tile models for DNA computing by self-assembly. Lect Notes Comput Sci 2054:63–88
Mao C, LaBean TH, Reif JH, Seeman NC (2000) Logical computation using algorithmic self-assembly of DNA triple-crossover molecules. Nature 407:493–496
Sakamoto K, Gouzu H, Komiya K (2000) Molecular computation by DNA hairpin formation. Science 288(5469):1223–1226
Braich RS, Chelyapov N, Johnson CR et al (2002) Solution of a 20-variable 3-SAT problem on a DNA computer. Science 296:499–502
Adleman L (2000) Towards a mathematical theory of self-assembly. Technical report, Department of Computer Science, University of Southern California
Brun Y (2007) Arithmetic computation in the tile assembly model: addition and multiplication. Theoret Comput Sci 378(1):17–31
Brun Y (2008) Nondeterministic polynomial time factoring in the tile assembly model. Theoret Compute Sci 395(1):3–23
Brun Y (2008) Solving satisfiability in the tile assembly model with a constant-size tileset. J Algorithms 63:151–166
Jonoska N, Karl S, Saito M (1999) Three dimensional DNA structures in computing. Bio Syst 52:143–153
Minqi L, Jin X et al (2010) 3D DNA self-assembly model for graph vertex coloring. J Comput Theor Nanosci 7:246–253
Rothemund PWK, Winfree E (2000) The program-size complexity of self-assembled squares (extended abstract). In: Proceedings of the 32nd annual ACM symposium on the theory of computing. Portland, pp 459–468
Acknowledgments
This work is supported by the Natural Science Foundation of China (61076103, 61070238), Basic and Frontier Technology Research Program of Henan Province (112300413208), Foundation of Henan Educational Committee (2011A510025), and the Doctoral Science Foundation of Zhengzhou University of Light Industry (2009BSJJ 006).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zhang, X., Fan, R., Wang, Y., Cui, G. (2013). A New Attempt for Satisfiability Problem: 3D DNA Self-Assembly to Solve SAT Problem. In: Yin, Z., Pan, L., Fang, X. (eds) Proceedings of The Eighth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA), 2013. Advances in Intelligent Systems and Computing, vol 212. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37502-6_105
Download citation
DOI: https://doi.org/10.1007/978-3-642-37502-6_105
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-37501-9
Online ISBN: 978-3-642-37502-6
eBook Packages: EngineeringEngineering (R0)