| A new approach based on PSO algorithm to find good computational encoding sequences |
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| 作者姓名： | Cui Guangzhao Niu Yunyun Wang Yanfeng Zhang Xuncai and Pan Linqiang |
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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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| 基金项目： | Supported by National Natural Science Foundation of China (Grant Nos 60573190 ,30370356)，Henan Province Scientific Foundation (GrantNos 511011600 ,211050900 ,2004922025) |
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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 |
| |
| Authors: | Cui Guangzhao Niu Yunyun Wang Yanfeng Zhang Xuncai and Pan Linqiang |
| |
| 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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