DNA VERİ DEPOLAMA: YÜKSEK YOĞUNLUKLU, UZUN VADELİ DİJİTAL DEPOLAMAYA YENİ BİR YAKLAŞIM

Öz

Paylaşılan veri hacmi 2025 yılına kadar 175 zettabayta ulaşabilir ve bu da depolama çözümleri için sorunlara yol açabilir. Geleneksel teknikleri kullanan depolama yöntemleri, veri kaybı ve kısa sistem dayanıklılığı ve yüksek harcama oranları gibi zorluklarla karşılaşır. Doğal depolama molekülü DNA, asgari bakım ihtiyaçları ile birlikte birinci sınıf dayanıklılıkla birlikte mükemmel yoğunluk sağlar. Teknoloji hala yüksek maliyet ve yavaş kodlama prosedürlerinin iki temel sınırlamasıyla uğraşmaktadır. DNA depolama araştırması, pratik ve ölçeklenebilir depolama çözümleri elde etmek için üç iyileştirme alanına odaklanır. Araştırma, DNA veri depolamanın şu anda nasıl var olduğunu ve mevcut engelleri ve teknolojinin gelecekte alabileceği yolu inceler.

Anahtar Kelimeler

• maliyet etkinliği
• veri yoğunluğu
• veri alma
• DNA veri depolama
• hibrit depolama sistemleri.

DNA Data Storage: A Novel Approach to High Density, Long Term Digital Storage

Öz

Shared data volume may hit 175 zettabytes by 2025 thus causing problems for storage solutions. Storage methods using conventional techniques encounter challenges such as data loss and short system durability and high expenditure rates. The natural storage molecule DNA provides excellent density alongside premium durableness together with minimal upkeep needs. The technology still deals with two core limitations of high expense and sluggish encoding procedures. DNA storage research focuses on three areas of improvement to achieve practical and scalable storage solutions. The research examines how DNA data storage exists at present as well as the existing obstacles and future course the technology may take.

Anahtar Kelimeler

• cost-effectiveness
• data density
• data retrieval
• DNA data storage
• hybrid storage systems.

Kaynakça

1. [1] Lai Q, Hua H. Secure medical image encryption scheme for Healthcare IoT using novel hyperchaotic map and DNA cubes. Expert Systems With Applications 2024;264:125854. https://doi.org/10.1016/j.eswa.2024.125854.
2. [2] Liu B, Wang F, Fan C, Li Q. Data readout techniques for DNA‐Based information storage. Advanced Materials 2025;37:e2412926. https://doi.org/10.1002/adma.202412926.
3. [3] Mitra A, Mitra P, Mahadani P, Trivedi S, Banerjee D, Das M. Application of character based DNA barcode: a novel approach towards identification of fruit fly (Diptera: Tephritidae) species from cucurbit crops. BMC Genomics 2025;26:70. https://doi.org/10.1186/s12864-025-11261-1.
4. [4] Xu X, Wang W, Ping Z. Biotechnological tools boost the functional diversity of DNA-based data storage systems. Computational and Structural Biotechnology Journal 2025;27:624–30. https://doi.org/10.1016/j.csbj.2025.02.002.
5. [5] Wang S, Mao X, Wang F, Zuo X, Fan C. Data storage using DNA. Advanced Materials 2023;36:e2307499. https://doi.org/10.1002/adma.202307499.
6. [6] Yang S, Bögels BWA, Wang F, Xu C, Dou H, Mann S, et al. DNA as a universal chemical substrate for computing and data storage. Nature Reviews Chemistry 2024;8:179–94. https://doi.org/10.1038/s41570-024-00576-4.
7. [7] Yu M, Tang X, Li Z, Wang W, Wang S, Li M, et al. High-throughput DNA synthesis for data storage. Chemical Society Reviews 2024;53:4463–89. https://doi.org/10.1039/d3cs00469d.
8. [8] Mao C, Wang S, Li J, Feng Z, Zhang T, Wang R, et al. Metal–Organic frameworks in microfluidics enable fast Encapsulation/Extraction of DNA for automated and integrated data storage. ACS Nano 2023;17:2840–50. https://doi.org/10.1021/acsnano.2c11241.

9. [9] Doricchi A, Platnich CM, Gimpel A, Horn F, Earle M, German Lanzavecchia, et al. Emerging Approaches to DNA data Storage: Challenges and Prospects. ACS Nano 2022;16:17552–71. https://doi.org/10.1021/acsnano.2c06748.
10. [10] Masanet E, Shehabi A, Lei N, Smith S, Koomey J. Recalibrating global data center energy-use estimates. Science 2020;367:984–6. https://doi.org/10.1126/science.aba3758.
11. [11] Organick L, Ang SD, Chen Y-J, Lopez R, Yekhanin S, Makarychev K, et al. Random access in large-scale DNA data storage. Nature Biotechnology 2018;36:242–8. https://doi.org/10.1038/nbt.4079.
12. [12] Erlich Y, Zielinski D. DNA Fountain enables a robust and efficient storage architecture. Science 2017;355:950–4. https://doi.org/10.1126/science.aaj2038.
13. [13] Seeman NC, Sleiman HF. DNA nanotechnology. Nature Reviews Materials 2017;3. https://doi.org/10.1038/natrevmats.2017.68.
14. [14] Grass RN, Heckel R, Puddu M, Paunescu D, Stark WJ. Robust Chemical Preservation of Digital Information on DNA in Silica with Error‐Correcting Codes. Angewandte Chemie International Edition 2015;54:2552–5. https://doi.org/10.1002/anie.201411378.
15. [15] Yazdi SMHT, Gabrys R, Milenkovic O. Portable and Error-Free DNA-Based data storage. Scientific Reports 2017;7:5011. https://doi.org/10.1038/s41598-017-05188-1.
16. [16] Kosuri S, Church GM. Large-scale de novo DNA synthesis: technologies and applications. Nature Methods 2014;11:499–507. https://doi.org/10.1038/nmeth.2918.
17. [17] Goldman N, Bertone P, Chen S, Dessimoz C, LeProust EM, Sipos B, et al. Towards practical, high-capacity, low-maintenance information storage in synthesized DNA. Nature 2013;494:77–80. https://doi.org/10.1038/nature11875.
18. [18] Church GM, Gao Y, Kosuri S. Next-Generation Digital Information Storage in DNA. Science 2012;337:1628. https://doi.org/10.1126/science.1226355.
19. [19] Mardis ER. The impact of next-generation sequencing technology on genetics. Trends in Genetics 2008;24:133–41. https://doi.org/10.1016/j.tig.2007.12.007.
20. [20] Kasianowicz JJ, Robertson JWF, Chan ER, Reiner JE, Stanford VM. Nanoscopic porous sensors. Annual Review of Analytical Chemistry 2008;1:737– 66. https://doi.org/10.1146/annurev.anchem.1.031207.112818.
21. [21] Rothemund PWK. Folding DNA to create nanoscale shapes and patterns. Nature 2006;440:297–302. https://doi.org/10.1038/nature04586.