BO-DNA: Biologically optimized encoding model for a highly-reliable DNA data storage
DNA data storage is a promising technology that utilizes computer simulation, and synthetic biology, offering high-density and reliable digital information storage. It is challenging to store massive data in a small amount of DNA without losing the original data since nonspecific hybridization error...
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| Published in | Computers in biology and medicine Vol. 165; p. 107404 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Oxford
Elsevier Ltd
01.10.2023
Elsevier Limited |
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| Abstract | DNA data storage is a promising technology that utilizes computer simulation, and synthetic biology, offering high-density and reliable digital information storage. It is challenging to store massive data in a small amount of DNA without losing the original data since nonspecific hybridization errors occur frequently and severely affect the reliability of stored data. This study proposes a novel biologically optimized encoding model for DNA data storage (BO-DNA) to overcome the reliability problem. BO-DNA model is developed by a new rule-based mapping method to avoid data drop during the transcoding of binary data to premier nucleotides. A customized optimization algorithm based on a tent chaotic map is applied to maximize the lower bounds that help to minimize the nonspecific hybridization errors. The robustness of BO-DNA is computed by four bio-constraints to confirm the reliability of newly generated DNA sequences. Experimentally, different medical images are encoded and decoded successfully with 12%–59% improved lower bounds and optimally constrained-based DNA sequences reported with 1.77bit/nt average density. BO-DNA's results demonstrate substantial advantages in constructing reliable DNA data storage.
•Tackling data reliability lost due to nonspecific hybridization errors in DNA data storage.•Introducing novel rule-based mapping to avoid data drop during the transcoding.•Constructing customized optimization algorithms to improve lower bounds on optimized DNA codes.•Developing bio-constrained threshold to confirm the DNA sequence's reliability.•Reporting 12%–59% improved lower bounds with 1.77 average density ensuring DNA storage reliability. |
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| AbstractList | DNA data storage is a promising technology that utilizes computer simulation, and synthetic biology, offering high-density and reliable digital information storage. It is challenging to store massive data in a small amount of DNA without losing the original data since nonspecific hybridization errors occur frequently and severely affect the reliability of stored data. This study proposes a novel biologically optimized encoding model for DNA data storage (BO-DNA) to overcome the reliability problem. BO-DNA model is developed by a new rule-based mapping method to avoid data drop during the transcoding of binary data to premier nucleotides. A customized optimization algorithm based on a tent chaotic map is applied to maximize the lower bounds that help to minimize the nonspecific hybridization errors. The robustness of BO-DNA is computed by four bio-constraints to confirm the reliability of newly generated DNA sequences. Experimentally, different medical images are encoded and decoded successfully with 12%–59% improved lower bounds and optimally constrained-based DNA sequences reported with 1.77bit/nt average density. BO-DNA's results demonstrate substantial advantages in constructing reliable DNA data storage. DNA data storage is a promising technology that utilizes computer simulation, and synthetic biology, offering high-density and reliable digital information storage. It is challenging to store massive data in a small amount of DNA without losing the original data since nonspecific hybridization errors occur frequently and severely affect the reliability of stored data. This study proposes a novel biologically optimized encoding model for DNA data storage (BO-DNA) to overcome the reliability problem. BO-DNA model is developed by a new rule-based mapping method to avoid data drop during the transcoding of binary data to premier nucleotides. A customized optimization algorithm based on a tent chaotic map is applied to maximize the lower bounds that help to minimize the nonspecific hybridization errors. The robustness of BO-DNA is computed by four bio-constraints to confirm the reliability of newly generated DNA sequences. Experimentally, different medical images are encoded and decoded successfully with 12%–59% improved lower bounds and optimally constrained-based DNA sequences reported with 1.77bit/nt average density. BO-DNA's results demonstrate substantial advantages in constructing reliable DNA data storage. •Tackling data reliability lost due to nonspecific hybridization errors in DNA data storage.•Introducing novel rule-based mapping to avoid data drop during the transcoding.•Constructing customized optimization algorithms to improve lower bounds on optimized DNA codes.•Developing bio-constrained threshold to confirm the DNA sequence's reliability.•Reporting 12%–59% improved lower bounds with 1.77 average density ensuring DNA storage reliability. |
| ArticleNumber | 107404 |
| Author | Rasool, Abdur Chen, Hui Hong, Jingwei Jiang, Qingshan Qu, Qiang |
| Author_xml | – sequence: 1 givenname: Abdur orcidid: 0000-0001-5334-9001 surname: Rasool fullname: Rasool, Abdur email: rasool@siat.ac.cn organization: Shenzhen Key Laboratory for High Performance Data Mining, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China – sequence: 2 givenname: Jingwei orcidid: 0000-0002-6982-8397 surname: Hong fullname: Hong, Jingwei organization: Shenzhen Key Laboratory for High Performance Data Mining, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China – sequence: 3 givenname: Qingshan orcidid: 0000-0002-8040-0308 surname: Jiang fullname: Jiang, Qingshan email: qs.jiang@siat.ac.cn organization: Shenzhen Key Laboratory for High Performance Data Mining, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China – sequence: 4 givenname: Hui orcidid: 0000-0002-5703-9454 surname: Chen fullname: Chen, Hui organization: Shenzhen Polytechnic University, Shenzhen, 518055, Guangdong, China – sequence: 5 givenname: Qiang orcidid: 0000-0001-5814-8460 surname: Qu fullname: Qu, Qiang email: qiang@siat.ac.cn organization: Shenzhen Key Laboratory for High Performance Data Mining, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China |
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| Keywords | Reliable storage Biocomputing Optimized encoding Bio-constrained codes DNA data storage |
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| SubjectTerms | Algorithms Binary data Bio-constrained codes Biocomputing Constraints Data storage Density Deoxyribonucleic acid Design DNA DNA data storage Efficiency Error correction & detection Errors Gene sequencing Heuristic Hybridization Information storage Lower bounds Medical imaging Medical research Methods Nucleotide sequence Nucleotides Optimization Optimization algorithms Optimized encoding Reliability Reliable storage Simulation |
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| Title | BO-DNA: Biologically optimized encoding model for a highly-reliable DNA data storage |
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