DocumentCode :
3416435
Title :
DNA Codewords Design Using Ant Colony Optimization Algorithm
Author :
Wang, Xinjin ; Shen, Yongpeng ; Zhang, Xuncai ; Cui, Guangzhao ; Wang, Yanfeng
Author_Institution :
Henan Key Lab. of Inf.-based Electr. Appliances, Zhengzhou Univ. of Light Ind., Zhengzhou, China
Volume :
3
fYear :
2010
fDate :
23-24 Oct. 2010
Firstpage :
494
Lastpage :
499
Abstract :
Before performing the DNA computation, a set of specific DNA sequences are required. However, this is a burdensome task as too many constraints need to be satisfied. In this paper, ant colony algorithm is applied to solve the problem of DNA codewords design. Inspired by the traveling salesman problem, first a city matrix with T rows and S columns is designed, in which every city denotes a DNA sequence. Then the artificial ants begin to search for an optimal route based on the DNA thermodynamic and combinational constraints. At last, the shortest rout with S sequences is the desired set of DNA codewords. The simulation results of the proposed approach shows better convergency and can provide reliable and effective codewords for the controllable DNA computation.
Keywords :
biocomputing; matrix algebra; optimisation; search problems; travelling salesman problems; DNA codeword; DNA sequence; DNA thermodynamic; ant colony optimization algorithm; artificial ants; city matrix; combinational constraints; controllable DNA computation; optimal route; traveling salesman problem; Algorithm design and analysis; Cities and towns; DNA; Encoding; Equations; Mathematical model; Temperature; Ant Colony Optimization Algorithm; DNA Codewords Design; DNA Computation; Genetic Algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence and Computational Intelligence (AICI), 2010 International Conference on
Conference_Location :
Sanya
Print_ISBN :
978-1-4244-8432-4
Type :
conf
DOI :
10.1109/AICI.2010.342
Filename :
5656581
Link To Document :
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