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Enhanced DNA sequence design with learning PSO

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Abstract

DNA computing is a novel computing technology with high storage density and parallelism and promising applications. The reliability of DNA computing relies on data encoded DNA sequences, but designing qualified DNA sequence is a very complex task. To accomplish this task more effectively, a learning particle swarm optimization (LPSO) is proposed. LPSO uses improved refraction opposition-based learning (ROBL) to enhance the local exploitation, improved salation learning (SL) to consolidate the global exploration,Then, Gaussian Mutation (GM) is introduced to improve the population diversity and bring the population closer to the global optimal solution. The feasibility of LPSO is demonstrated by results of DNA encoding sequence optimization experiments, Then the help of three strategies to improve PSO algorithm is discussed through ablation study.

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Data availability

The data used to support the findings of this study are available from the corresponding author upon request.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China (Nos. 62272418, 62102058), Basic public welfare research program of Zhejiang Province (No. LGG18E050011).

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Authors and Affiliations

  1. School of Information Engineering, Jiangxi University of Science and Technology, Ganzhou, 341000, Jiangxi, China

    Huichuang Wu & Zuwei Huang

  2. School of Software Engineering, Jiangxi University of Science and Technology, Nanchang, 330000, Jiangxi, China

    Lin Zhang

  3. School of Computer Science and Technology, Zhejiang Normal University, Jinhua, 321004, China

    Donglin Zhu & Changjun Zhou

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  1. Huichuang Wu
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  2. Donglin Zhu
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  4. Lin Zhang
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Contributions

H.W. and D.Z. wrote the main manuscript text; L.Z. and Z.H. reviewed and edited the manuscript; H.W. and L.Z. Wrote code and collected data. L.Z. and C.Z. are funding acquisition and supervision. All authors reviewed the manuscript.

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Correspondence to Lin Zhang.

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Wu, H., Zhu, D., Huang, Z. et al. Enhanced DNA sequence design with learning PSO. Evol. Intel. 17, 3015–3029 (2024). https://doi.org/10.1007/s12065-024-00924-9

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  • DOI: https://doi.org/10.1007/s12065-024-00924-9

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