2020 IEEE International Symposium
on Information Theory
21-26 June 2020 • Los Angeles, California, USA
| Paper ID | T.3.3 | ||
| Paper Title | Coding for Efficient DNA Synthesis | ||
| Authors | Andreas Lenz, Technical University of Munich, Germany; Yi Liu, Cyrus Rashtchian, Paul Siegel, University of California, San Diego, United States; Antonia Wachter-Zeh, Technical University of Munich, Germany; Eitan Yaakobi, Technion - Israel Institute of Technology, Israel | ||
| Session | T.3: Information Theory and Biology | ||
| Presentation | Lecture | ||
| Track | Topics in Information Theory | ||
| Manuscript | Click here to download the manuscript | ||
| Virtual Presentation | Click here to watch in the Virtual Symposium | ||
| Abstract | For DNA data storage to become a feasible technology, all aspects of the encoding and decoding pipeline must be optimized. Writing the data into DNA, which is known as DNA synthesis, is currently the most costly part of existing storage systems. As a step toward more efficient synthesis, we study the design of codes that minimize the time and number of required materials needed to produce the DNA strands. We consider a popular synthesis process that builds many strands in parallel in a step-by-step fashion using a fixed supersequence S. The machine iterates through S one nucleotide at a time, and in each cycle, it adds the next nucleotide to a subset of the strands. The synthesis time is determined by the length of S. We show that by introducing redundancy to the synthesized strands, we can significantly decrease the number of synthesis cycles. We derive the maximum amount of information per synthesis cycle assuming S is an arbitrary periodic sequence. To prove our results, we exhibit new connections to cost-constrained codes. | ||
Plan Ahead
2021 IEEE International Symposium on Information Theory
11-16 July 2021 | Melbourne, Victoria, Australia
