Coding and Algorithms for DNA-Based Data Storage Systems
A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Information Theory, Probability and Statistics".
Deadline for manuscript submissions: 30 November 2024 | Viewed by 208
Special Issue Editors
Interests: bioinformatics and computational biology; graph and hypergraph neural networks; coding theory and applications; molecular storage and computing
Special Issue Information
Dear Colleagues,
Molecular storage, and DNA-based data storage in particular, has emerged as a viable alternative to classical optical and magnetic recorders due to its ultra-high storage density, durability and ease of data replication. Still, practical advances in the field are hampered by the lack of low-cost and parallel synthesis platforms, and the size and time-delays of the read-write connectome and sequencing platforms. To mitigate some of these problems and ensure high levels of data integrity, specialized new coding and machine learning solutions have been proposed for random data access, data sequencing and retrieval. The goal of the Special Issue is to showcase new results in the field of coding theory and computational and learning algorithm design that strengthen the case for archival DNA-based data storage.
Prof. Dr. Olgiça Milenković
Dr. Jin Sima
Guest Editors
Manuscript Submission Information
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Keywords
- coding theory
- computational biology
- DNA-based data storage
- DNA synthesis and sequencing
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