A5006137960- DNA and Biological Computing
- Advanced biosensing and bioanalysis techniques
- Cellular Automata and Applications
- Chaos-based Image/Signal Encryption
- Algorithms and Data Compression
- Genomics and Phylogenetic Studies
- Machine Learning in Bioinformatics
- Advanced Image and Video Retrieval Techniques
- RNA and protein synthesis mechanisms
- Advanced Data Storage Technologies
Guangzhou University
2022-2024
Abstract Synchronization (insertions–deletions) errors are still a major challenge for reliable information retrieval in DNA storage. Unlike traditional error correction codes (ECC) that add redundancy the stored information, multiple sequence alignment (MSA) solves this problem by searching conserved subsequences. In paper, we conduct comprehensive simulation study on capability of typical MSA algorithm, MAFFT. Our results reveal its exhibits phase transition when there around 20% errors....
Abstract DNA, or deoxyribonucleic acid, is a powerful molecule that plays fundamental role in storing and processing genetic information of all living organisms. In recent years, scientists have harnessed hybridization powers between DNA molecules to perform various computing tasks storage. Unlike specific hybridization, non-specific provides natural way measure similarity the objects represented by different sequences. We utilize such property build an instance-based learning model which...
Rapid development in synthetic technologies has boosted DNA as a potential medium for large-scale data storage. Meanwhile, how to implement security the storage system is still an unsolved problem.
DNA storage is widely considered as a promising solution to the data explosion problem. However, synthesis, PCR and sequencing processes usually result in erroneous reads involving base insertions, deletions, substitutions. Specially this situation even more serious 3rd generation of technologies. Different from previous error-correction multiple sequence alignment methods, we first transform into noisy mage, then construct conditional generative adversarial network produce "smooth" image...
As one main form of multimedia data, images play a critical role in various applications. In this paper, representation-based architecture is proposed which takes advantage the outstanding representation and image-generation abilities deep learning (DL). This includes two DL models: an autoencoder U-Net network achieve representation, construction, refinement from noisy reads DNA storage. Simulation experiments demonstrate that it can reconstruct moderate quality scenarios where...
Abstract With the rapid development of DNA (Deoxyribonucleic Acid) storage technologies, storing digital images in is feasible. Meanwhile, information security system still a problem to solve. Therefore, this paper, we propose storage-oriented image encryption algorithm utilizing processing mechanisms molecule biology. The basic idea perform pixel replacement by gene hybridization, and implement dual diffusion mutation. ciphertext can be synthesized stored after encryption. Experimental...
Abstract DNA, or deoxyribonucleic acid, is a powerful molecule that plays fundamental role in the storing and processing genetic information of all living organisms. In recent years, scientists over world have devoted to taking advantage its high density, energy efficiency long durability solve challenges technology. Here, we propose build an instance-based learning model by DNA molecules. The handwriting digit images MNIST dataset are encoded sequences using deep encoder. And reversal...
Abstract Rapid development in synthetic technologies has boosted DNA as a potential medium for large-scale data storage. Meanwhile, how to implement security storage system is still an unsolved problem. In this paper, we propose image encryption method based on the modulation-based architecture. The key idea take advantage of unpredictable modulation signals encrypt highly error-prone channel. Numerical results demonstrate that our feasible and effective with excellent against various...