DNA based storage is a novel technology, where digital information is stored in synthetic DNA molecules. The recent advance in DNA sequencing methods and decrease in sequencing costs have paved the way for storage methods based on DNA. The natural stability of DNA molecules, (the genetic information from fossils is maintained over tens of thousands of years) motivate their use for long-term archival storage. Furthermore, because the information is stored on molecular levels, such storage systems have extremely high data densities. Recent experiments report data densities of 2 PB/gram, which corresponds to the capacity of a thousand conventional hard disk drives in one gram of DNA.
In this talk we present error-correcting codes for the storage of data in synthetic DNA. We investigate a storage model where data is represented by an unordered set of M sequences, each of length L. Errors within that model are a loss of whole sequences and point errors inside the sequences, such as insertions, deletions and substitutions. We derive Gilbert-Varshamov lower bounds and sphere packing upper bounds on achievable cardinalities of error-correcting codes within this storage model. We further propose explicit code constructions than can correct errors in such a storage system that can be encoded and decoded efficiently. Comparing the sizes of these codes to the upper bounds, we show that many of the constructions are close to optimal.