ArticleFrontiers in genetics2021
CLGBO: An Algorithm for Constructing Highly Robust Coding Sets for DNA Storage.
Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- TC-HUR: A Tri-Phase Cauchy-Assisted Hunger Games Search and Unified Runge-Kutta Optimizer for Robust DNA Data Storage.International journal of molecular sciences · 2026Article
- Study on DNA Storage Encoding Based IAOA under Innovation Constraints.Current issues in molecular biology · 2023Article
- Article
- Adaptive coding for DNA storage with high storage density and low coverage.NPJ systems biology and applications · 2022Article
- Article
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3 authors.
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Abstract
In the era of big data, new storage media are urgently needed because the storage capacity for global data cannot meet the exponential growth of information. Deoxyribonucleic acid (DNA) storage, where primer and address sequences play a crucial role, is one of the most promising storage media because of its high density, large capacity and durability. In this study, we describe an enhanced gradient-based optimizer that includes the Cauchy and Levy mutation strategy (CLGBO) to construct DNA coding sets, which are used as primer and address libraries. Our experimental results show that the lower bounds of DNA storage coding sets obtained using the CLGBO algorithm are increased by 4.3-13.5% compared with previous work. The non-adjacent subsequence constraint was introduced to reduce the error rate in the storage process. This helps to resolve the problem that arises when consecutive repetitive subsequences in the sequence cause errors in DNA storage. We made use of the CLGBO algorithm and the non-adjacent subsequence constraint to construct larger and more highly robust coding sets.
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