DNA computing and cryptography

Current DNA-based data storage platforms encode information only in the nucleotide sequence. Here, the authors report a 2DDNA platform that can store data in both sequence context and backbone structure, and has improved image inpainting and enhancement via automatic discoloration detection and deep learning.

Storage technology based on DNA is emerging as an information dense and durable medium. Here the authors use machine learning-based encoding and hybridization probes to execute similarity searches in a DNA database.

The molecular architecture of DNA data storage opens up interesting possibilities and functionalities. Here the authors leverage thermodynamics to control the access of different subsets of data in a file.

Encoding data in DNA is a promising approach to high density data storage. Here the authors present a prototype sequencing-free method that uses the spatial orientation of DNA strands with super-resolution microscopy readout.

DNA has the potential to store vast amounts of data but it is subject to physical decay. In this Perspective, the authors propose that the stability of DNA should be a key consideration in how it is used for data storage.

Large volumes of true random numbers are needed for increasing requirements of secure data encryption. Here the authors use the stochastic nature of DNA synthesis to obtain millions of gigabytes of unbiased randomness.