This paper introduces 2DDNA, a two-dimensional molecular data storage system that encodes information in both the nucleotide sequence and the backbone structure of DNA. It efficiently stores images in synthetic DNA and embeds metadata as nicks in the DNA backbone. Machine learning techniques are used for error correction and image reconstruction, enabling rewriting of metadata and robust data retrieval despite channel errors. Experimental results demonstrate the platform's ability to reconstruct images with minimal degradation and rewrite data, showcasing DNA's potential as a rewritable memory.

Chao Pan, S. Kasra Tabatabaei, S. M. Hossein Tabatabaei Yazdi, Alvaro G. Hernandez, Charles M. Schroeder, Olgica Milenkovic