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DNA-Based Data Storage Using Portable Sequencer Dr. Milenkovic has developed a new method for error-free random access data storage through DNA that uses a portable nanopore sequencer. The error correction methods used... Read More Dr. Milenkovic has developed a new method for error-free random access data storage through DNA that uses a portable nanopore sequencer. The error correction methods used in this scheme result in error-free reconstructions of the synthetic DNA strand. This system has an information rate of 0.83 and a storage density of 1.07 x 10^23 bytes/gram.
Native DNA Based Storage and Computing via Single Strand Nicking Prof. Milenkovic from the University of Illinois at Urbana-Champaign has developed a new method for DNA based storage of information. In... Read More Prof. Milenkovic from the University of Illinois at Urbana-Champaign has developed a new method for DNA based storage of information. In this method information is first converted into positive integers based on which single strand of the DNA is nicked at defined positions. This information can be accessed through immunoprecipitation and sequencing of the DNA. This method allows for random access as well as computation of data.
Solid-State Drive This solid-state drive firmware-level solution (TimeSSD) and toolkit (TimeKit) use intrinsic flash properties to retain the history of past storage states for up... Read More This solid-state drive firmware-level solution (TimeSSD) and toolkit (TimeKit) use intrinsic flash properties to retain the history of past storage states for up to several weeks without dedicated data backups. The technology can significantly enhance the security of flash-based storage systems while incurring negligible performance overhead for the majority of common applications. TimeSSD and TimeKits functionalities can provide flexibility and facilitate more efficient, secure system functions such as protecting against malware or encrypted ransomware attacks that corrupt files in storage, recovering user files, retrieving update logs, and providing an evidence chain for storage forensics. Rollback to a previous consistent state may be achieved with minimal software involvement. A proceedings paper further describing the invention can be accessed here. This invention is patent pending.
SemiSynBio: An On-Chip Nanoscale Storage System Using Chimeric DNA Dr. Milenkovic from the University of Illinois has developed an on-chip integrated nanosytem for writing, storage, access, and reading of large data volumes that utilizes... Read More Dr. Milenkovic from the University of Illinois has developed an on-chip integrated nanosytem for writing, storage, access, and reading of large data volumes that utilizes inexpensive chimeric DNA, scalable grids of semiconductor nanotubes, and specialized nanopore sequencers. Using an M13 template for ease-of-synthesis and modified DNA bases to expand the potential alphabet, this system of synthesis for DNA-based data storage is inexpensive and flexible. In addition, selectively addressable semiconductor nanotubes are incorporated into an on-chip nanopore sequencer enabling selective storage/querying/retrieval of information in DNA-based data storage. This development represents a significant advance towards end-to-end automation of DNA-based data storage. Primary Application: Data Storage and Archiving Benefit: Provides a mechanism for selective storage and reading of DNA library, basis for data storage architecture
Image Processing and Error-Correction in DNA via Inpainting and Filtering Dr. Olgica Milenkovic and Dr. Charles Schroeder at the University of Illinois has developed an error-correction method for DNA-based data storage of massive image datasets. Previous methods for... Read More Dr. Olgica Milenkovic and Dr. Charles Schroeder at the University of Illinois has developed an error-correction method for DNA-based data storage of massive image datasets. Previous methods for addressing errors use Reed-Solomon codes at both the individual oligo and pool of oligo level to reconstruct missing strings from redundantly encoded oligos. This method uses deep learning techniques to utilize natural redundancy present in the images to perform inpainting on the missing pixels, reconstructing the missing information, and avoiding the requirement for synthesizing and sequencing redundancy in the oligos.
A New Way of Storing Data using DNA-Based Storage Systems Inventors from the University of Illinois and University of Massachusetts at Amherst have developed a novel way of storing data using chemically modified nucleotides... Read More Inventors from the University of Illinois and University of Massachusetts at Amherst have developed a novel way of storing data using chemically modified nucleotides combined with DNA base pairs. This system of DNA-based storage creates a novel eleven letter alphabet with room for even more letters that allows for a nearly two-fold increase in the storage density of molecular recorders. Furthermore, the inventors have also developed a novel neural network architecture that sequences these alphabets and constructs with an extremely large accuracy. This entire technology drastically improves upon current DNA-based storage systems and provides them with new directions in molecular storage and computing that have the potential to resolve important cost and implementation issues the industry faces today.