TR
EN
Gene Mining and Privacy by the Emerging High Tech
Abstract
Gene mining is a critical data mining process that enables the identification of genetic predispositions and disease risks by analyzing Deoxyribonucleic Acid-DNA data. Within this process, using emerging high tech such as artificial intelligence (AI) and Quantum Computers-QC emerge as innovative technologies that enhance analytical power. AI algorithms and data mining techniques facilitate the discovery of genetic patterns, while QC enable highly accurate analyses even in complex and large datasets. These advancements allow for a faster, more in-depth and reliable examination of DNA data, providing substantial contributions to genetic research. However, the sensitive nature of DNA data necessitates stringent measures for personal privacy and data security. In this context, Blockchain Technologies-BCT offers an effective solution for the secure storage, anonymization and controlled sharing of DNA data exclusively with authorized entities. The distributed and immutable structure of Blockchain Technology-BCT safeguards data while AI and quantum technologies contribute speed and precision to gene mining. This article examines the contributions of AI, data mining and QC to gene mining and underscores the importance of BCT in preserving personal privacy. This study examines the contributions of AI, QC, and BCT in gene mining, emphasizing the importance of BCT in ensuring data privacy and security. In particular, while providing a high level of security for the protection of personal and sensitive data such as DNA, the integrated use of these technologies plays a critical role in establishing new standards for data privacy.
Keywords
References
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Details
Primary Language
English
Subjects
Software Engineering (Other)
Journal Section
Research Article
Publication Date
June 29, 2025
Submission Date
December 10, 2024
Acceptance Date
May 14, 2025
Published in Issue
Year 2025 Volume: 10 Number: 1
APA
Yıldırım, H., & Ünal, C. (2025). Gene Mining and Privacy by the Emerging High Tech. Sinop Üniversitesi Fen Bilimleri Dergisi, 10(1), 200-233. https://doi.org/10.33484/sinopfbd.1599550
AMA
1.Yıldırım H, Ünal C. Gene Mining and Privacy by the Emerging High Tech. Sinop Uni J Nat Sci. 2025;10(1):200-233. doi:10.33484/sinopfbd.1599550
Chicago
Yıldırım, Hakan, and Cihan Ünal. 2025. “Gene Mining and Privacy by the Emerging High Tech”. Sinop Üniversitesi Fen Bilimleri Dergisi 10 (1): 200-233. https://doi.org/10.33484/sinopfbd.1599550.
EndNote
Yıldırım H, Ünal C (June 1, 2025) Gene Mining and Privacy by the Emerging High Tech. Sinop Üniversitesi Fen Bilimleri Dergisi 10 1 200–233.
IEEE
[1]H. Yıldırım and C. Ünal, “Gene Mining and Privacy by the Emerging High Tech”, Sinop Uni J Nat Sci, vol. 10, no. 1, pp. 200–233, June 2025, doi: 10.33484/sinopfbd.1599550.
ISNAD
Yıldırım, Hakan - Ünal, Cihan. “Gene Mining and Privacy by the Emerging High Tech”. Sinop Üniversitesi Fen Bilimleri Dergisi 10/1 (June 1, 2025): 200-233. https://doi.org/10.33484/sinopfbd.1599550.
JAMA
1.Yıldırım H, Ünal C. Gene Mining and Privacy by the Emerging High Tech. Sinop Uni J Nat Sci. 2025;10:200–233.
MLA
Yıldırım, Hakan, and Cihan Ünal. “Gene Mining and Privacy by the Emerging High Tech”. Sinop Üniversitesi Fen Bilimleri Dergisi, vol. 10, no. 1, June 2025, pp. 200-33, doi:10.33484/sinopfbd.1599550.
Vancouver
1.Hakan Yıldırım, Cihan Ünal. Gene Mining and Privacy by the Emerging High Tech. Sinop Uni J Nat Sci. 2025 Jun. 1;10(1):200-33. doi:10.33484/sinopfbd.1599550
Cited By
Quantum-resilient blockchain framework for privacy-preserving genomic data sharing and analysis
Journal of Information Security and Applications
https://doi.org/10.1016/j.jisa.2025.104245
