| A new approach based on PSO algorithm to find good computational encoding sequences |
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| 引用本文： | Cui Guangzhao1,Niu Yunyun1,Wang Yanfeng1,Zhang Xuncai2 and Pan Linqiang2(1. School of Electrical and Electronic Engineering,Zhengzhou University of Light Industry,Zhengzhou 450002,China, 2. Research Institute of Biomolecular Computer,Huazhong University of Science and Technology,Wuhan 430074,China). A new approach based on PSO algorithm to find good computational encoding sequences[J]. 自然科学进展(英文版), 2007, 17(6): 712-716 |
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| 作者姓名： | Cui Guangzhao1 Niu Yunyun1 Wang Yanfeng1 Zhang Xuncai2 and Pan Linqiang2(1. School of Electrical and Electronic Engineering Zhengzhou University of Light Industry Zhengzhou 450002 China 2. Research Institute of Biomolecular Computer Huazhong University of Science and Technology Wuhan 430074 China) |
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| 作者单位： | 1. School of Electrical and Electronic Engineering，Zhengzhou University of Light Industry，Zhengzhou 450002，China; 2. Research Institute of Biomolecular Computer，Huazhong University of Science and Technology，Wuhan 430074，China |
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| 摘 要： | Computational encoding DNA sequence design is one of the most important steps in molecular computation. A lot of research work has been done to design reliable sequence library. A revised method based on the support system developed by Tanaka et al. is proposed here with different criteria to construct fitness function. Then we adapt particle swarm optimization (PSO) algorithm to our encoding problem. By using the new algorithm, a set of sequences with good quality is generated. The result also shows that our PSO-based approach could rapidly converge at the minimum level for an output of the simulation model. The celerity of the algorithm fits our requirements.
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A new approach based on PSO algorithm to find good computational encoding sequences |
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| Cui Guangzhao,Niu Yunyun,Wang Yanfeng,Zhang Xuncai,Pan Linqiang. A new approach based on PSO algorithm to find good computational encoding sequences[J]. Progress in Natural Science, 2007, 17(6): 712-716 |
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| Authors: | Cui Guangzhao Niu Yunyun Wang Yanfeng Zhang Xuncai Pan Linqiang |
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| Abstract: | Computational encoding DNA sequence design is one of the most important steps in molecular computation. A lot of research work has been done to design reliable sequence library. A revised method based on the support system developed by Tanaka et al. is proposed here with different criteria to construct fitness function. Then we adapt particle swarm optimization (PSO) algorithm to our encoding problem. By using the new algorithm, a set of sequences with good quality is generated. The result also shows that our PSO-based approach could rapidly converge at the minimum level for an output of the simulation model. The celerity of the algorithm fits our requirements. |
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| Keywords: | DNA computing computational encoding DNA sequences PSO algorithm fitness function |
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