2026-10-09T21:04:13Z https://admin.olos.swiss/oai-info/oai-provider/oai

oai:olos.swiss:olos:ec67214c-c0c4-4057-99b4-c4279cc956a0 2026-10-02T14:27:25Z doi-registration orgunit

DNAMIC CODEC Poster for MoleculArXiv Autumn School 2025 El Kharroubi, Michaël Burgi, Pierre-Yves Cazeaux, Hugues OLOS.swiss, OLOS 2025 Issued: 2025-11-14T00:00:00Z Created: 2026-10-02T14:02:26Z Updated: 2026-10-02T14:27:13Z Accepted: 2026-10-02T14:27:13Z doi:10.34914/olos:vkknnbjfrzddlovbgy5h77jmwa https://olos.swiss/portal//archives/ec67214c-c0c4-4057-99b4-c4279cc956a0 ark:99999/fk9vkknnbjfrzddlovbgy5h77jmwa Digital Preservation Archiving OAIS DNA Storage DNA CODEC DNAMIC CODEC poster Poster for MoleculArXiv Autumn School on DNA Data Storage 10 - 14 November 2025 IESC, Cargèse, Corsica, France The DNAMIC project, part of the European Path Finder challenge for DNA-based digital data storage, aims to develop an autonomous, end-to-end DNA data storage solution based on a microfactory. Our main application is long-term data archiving, using the OAIS-compliant OLOS system (olos.swiss). This initiative brings together experts from academia and the private sector across Europe. At the University of Geneva, our team is focusing on the design of a CODEC that encodes binary data in DNA and decodes it back into binary while integrating it into the OLOS framework. Our CODEC is based on a codon wheel to convert bits into nucleotides and avoid homopolymers greater than three while maintaining a balanced GC ratio. Each strand is 243 nucleotides long, including metadata, payload, and primers. To improve data integrity, we implemented the Reed-Solomon ECC scheme both within and between multiple strands. Additionally, we use a classical clustering, alignment, and consensus mechanism to identify and correct synchronization errors. We have successfully validated a preliminary version of our CODEC using six files (for a total of about 1 MB) synthesized by Twist Bioscience and sequenced by our partners at Genomika. Currently, our efforts are focused on optimizing the decoding part by: - using a locality-sensitive hash clustering algorithm, implementing a sorting system to reduce cluster size, and assessing the use of 2D Reed-Solomon ECC or tag-based approach to handle InDel errors; - porting the algorithms to parallel architectures such as GPUs and FPGAs. The aim is to extend file storage to the terabyte scale, i.e., to decode 1 TB in less than 12 hours. [8b017350-e7ba-4b7f-acfb-ef6a3829681c] DLCM Cazeaux, Hugues De Dios Fuente, Alicia Burgi, Pierre-Yves [swissuniversities] swissuniversities Dataset application/pdf image/png text/xml PUBLIC https://www.dlcm.ch/access-level/final BLUE https://www.dlcm.ch/data-tag LICENSE https://www.dlcm.ch/data-use-policy Creative Commons Public Domain Dedication https://creativecommons.org/publicdomain/zero/1.0/