Research Article
Open Access
RFS-codec: A Novel Encoding Approach to Store Image Data in DNA
1
Department of Information and Computer Sciences, University of Hawaii at Manoa, Honolulu, HI 96822, United States
* Corresponding Author:
Abdur Rasool,
[email protected]
Volume 1, Issue 1
2025
Received: 15 May 2025
Accepted: 22 June 2025
Published: 30 June 2025
Article Information
Published in
Journal of Artificial Intelligence in Bioinformatics
Volume/Issue
Volume 1, Issue 1, 2025
Pages
41-50
Cited by
7 (Crossref)
3 (Scopus)
Abstract
DNA data storage is a promising technology that utilizes computer simulation and offers high-density and durable digital information storage. It is challenging to store massive image data in a small amount of DNA without losing the original data since nonspecific hybridization errors occur frequently and severely affect the durability of stored data. This work proposes a novel approach (RFS-codec) comprising an image fraction strategy and an innovative codec method to split and encode image data into DNA storage, respectively. The fraction strategy contributes by delivering a cost-effective solution for image storage in DNA. The codec method offers an encryption mechanism to convert binary data into DNA bases by avoiding hybridization errors and satisfying the critical bio-coding constraints responsible for DNA storage durability. The robustness of RFS-codec is computed with GC and homopolymer constraints. Experimentally, different image data are efficiently encoded and decoded successfully with 1.8 bit/nt average density. RFS-codec's results demonstrate substantial advantages in constructing cost-effective, scalable, and durable DNA data storage.
Graphical Abstract
Keywords
DNA data storage
image fraction
codec approach
bio-coding constraints
Data Availability Statement
Data will be made available on request.
Funding
This work was supported without any funding.
Conflicts of Interest
The author declare no conflicts of interest.
Ethical Approval and Consent to Participate
Not applicable.
References
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Cited By (6)
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Expert Systems with Applications, 2026 , 299 .
[CrossRef] -
Xue Li, Yanfen Zheng, Qi Shao, Jiadong Wang, Wei Li, Bin Wang, Shihua Zhou, Ben Cao, Pan Zheng. Highly biased DNA sequence reconstruction in DNA storage with multi-scale attention mechanism and contrast learning.
Synthetic and Systems Biotechnology, 2026 , 12 .
[CrossRef] -
Jiadong Wang, Bin Wang, Shihua Zhou, Ben Cao, Wei Li, Pan Zheng. DNACSE: Enhancing Genomic LLMs with Contrastive Learning for DNA Barcode Identification.
Journal of Chemical Information and Modeling, 2026 , 66 (2).
[CrossRef] -
Xiang Liu, Yanfen Zheng, Xue Li, Bin Wang, Shihua Zhou, Ben Cao, Pan Zheng. An end-to-end DNA storage coding method based on a low-complexity multiple biological constraints loss and RL-inspired differentiable solver.
Expert Systems with Applications, 2026 , 315 .
[CrossRef] -
Qian Liu, Jie Zhang, Jingsong Cui, Dong-Po Song, Hao Qi. Toward Portable DNA Data Storage: A Paper-Based System for Rewritable and Random Access.
ACS Applied Materials & Interfaces, 2026 , 18 (16).
[CrossRef] -
Lina Tan, Yi Li, Yan Zeng, Peng Chen. An Adaptive JPEG Steganography Algorithm Based on the UT-GAN Model.
Electronics, 2025 , 14 (20).
[CrossRef]
* Citation data provided by Crossref Cited-by.
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APA Style
Rasool, A. (2025). RFS-codec: A Novel Encoding Approach to Store Image Data in DNA. Journal of Artificial Intelligence in Bioinformatics, 1(1), 41–50. https://doi.org/10.62762/JAIB.2025.146324
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TY - JOUR AU - Rasool, Abdur PY - 2025 DA - 2025/06/30 TI - RFS-codec: A Novel Encoding Approach to Store Image Data in DNA JO - Journal of Artificial Intelligence in Bioinformatics T2 - Journal of Artificial Intelligence in Bioinformatics JF - Journal of Artificial Intelligence in Bioinformatics VL - 1 IS - 1 SP - 41 EP - 50 DO - 10.62762/JAIB.2025.146324 UR - https://www.icck.org/article/abs/JAIB.2025.146324 KW - DNA data storage KW - image fraction KW - codec approach KW - bio-coding constraints AB - DNA data storage is a promising technology that utilizes computer simulation and offers high-density and durable digital information storage. It is challenging to store massive image data in a small amount of DNA without losing the original data since nonspecific hybridization errors occur frequently and severely affect the durability of stored data. This work proposes a novel approach (RFS-codec) comprising an image fraction strategy and an innovative codec method to split and encode image data into DNA storage, respectively. The fraction strategy contributes by delivering a cost-effective solution for image storage in DNA. The codec method offers an encryption mechanism to convert binary data into DNA bases by avoiding hybridization errors and satisfying the critical bio-coding constraints responsible for DNA storage durability. The robustness of RFS-codec is computed with GC and homopolymer constraints. Experimentally, different image data are efficiently encoded and decoded successfully with 1.8 bit/nt average density. RFS-codec's results demonstrate substantial advantages in constructing cost-effective, scalable, and durable DNA data storage. SN - 3068-7535 PB - Institute of Central Computation and Knowledge LA - English ER -
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@article{Rasool2025RFScodec,
author = {Abdur Rasool},
title = {RFS-codec: A Novel Encoding Approach to Store Image Data in DNA},
journal = {Journal of Artificial Intelligence in Bioinformatics},
year = {2025},
volume = {1},
number = {1},
pages = {41-50},
doi = {10.62762/JAIB.2025.146324},
url = {https://www.icck.org/article/abs/JAIB.2025.146324},
abstract = {DNA data storage is a promising technology that utilizes computer simulation and offers high-density and durable digital information storage. It is challenging to store massive image data in a small amount of DNA without losing the original data since nonspecific hybridization errors occur frequently and severely affect the durability of stored data. This work proposes a novel approach (RFS-codec) comprising an image fraction strategy and an innovative codec method to split and encode image data into DNA storage, respectively. The fraction strategy contributes by delivering a cost-effective solution for image storage in DNA. The codec method offers an encryption mechanism to convert binary data into DNA bases by avoiding hybridization errors and satisfying the critical bio-coding constraints responsible for DNA storage durability. The robustness of RFS-codec is computed with GC and homopolymer constraints. Experimentally, different image data are efficiently encoded and decoded successfully with 1.8 bit/nt average density. RFS-codec's results demonstrate substantial advantages in constructing cost-effective, scalable, and durable DNA data storage.},
keywords = {DNA data storage, image fraction, codec approach, bio-coding constraints},
issn = {3068-7535},
publisher = {Institute of Central Computation and Knowledge}
}
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Copyright © 2025 by the Author(s). Published by Institute of Central Computation and Knowledge. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.
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