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Towards practical, high-capacity, low-maintenance information storage in synthesized DNA

Author

Listed:
  • Nick Goldman

    (European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK)

  • Paul Bertone

    (European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK)

  • Siyuan Chen

    (Agilent Technologies, Genomics–LSSU, 5301 Stevens Creek Boulevard, Santa Clara, California 95051, USA)

  • Christophe Dessimoz

    (European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK)

  • Emily M. LeProust

    (Agilent Technologies, Genomics–LSSU, 5301 Stevens Creek Boulevard, Santa Clara, California 95051, USA)

  • Botond Sipos

    (European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK)

  • Ewan Birney

    (European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK)

Abstract

An efficient and scalable strategy with robust error correction is reported for encoding a record amount of information (including images, text and audio files) in DNA strands; a ‘DNA archive’ has been synthesized, shipped from the USA to Germany, sequenced and the information read.

Suggested Citation

  • Nick Goldman & Paul Bertone & Siyuan Chen & Christophe Dessimoz & Emily M. LeProust & Botond Sipos & Ewan Birney, 2013. "Towards practical, high-capacity, low-maintenance information storage in synthesized DNA," Nature, Nature, vol. 494(7435), pages 77-80, February.
  • Handle: RePEc:nat:nature:v:494:y:2013:i:7435:d:10.1038_nature11875
    DOI: 10.1038/nature11875
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    Citations

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    Cited by:

    1. Abdur Rasool & Qiang Qu & Yang Wang & Qingshan Jiang, 2022. "Bio-Constrained Codes with Neural Network for Density-Based DNA Data Storage," Mathematics, MDPI, vol. 10(5), pages 1-21, March.
    2. Shekaari, Ashkan & Jafari, Mahmoud, 2019. "Statistical mechanical modeling of a DNA nanobiostructure at the base-pair level," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 518(C), pages 80-88.
    3. Chao Pan & S. Kasra Tabatabaei & S. M. Hossein Tabatabaei Yazdi & Alvaro G. Hernandez & Charles M. Schroeder & Olgica Milenkovic, 2022. "Rewritable two-dimensional DNA-based data storage with machine learning reconstruction," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    4. Punnag Padhy & Mohammad Asif Zaman & Michael Anthony Jensen & Yao-Te Cheng & Yogi Huang & Mo Wu & Ludwig Galambos & Ronald Wayne Davis & Lambertus Hesselink, 2024. "Dielectrophoretic bead-droplet reactor for solid-phase synthesis," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    5. Cheng Kai Lim & Jing Wui Yeoh & Aurelius Andrew Kunartama & Wen Shan Yew & Chueh Loo Poh, 2023. "A biological camera that captures and stores images directly into DNA," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    6. Afsaneh Sadremomtaz & Robert F. Glass & Jorge Eduardo Guerrero & Dennis R. LaJeunesse & Eric A. Josephs & Reza Zadegan, 2023. "Digital data storage on DNA tape using CRISPR base editors," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    7. Jingwei Hong & Abdur Rasool & Shuo Wang & Djemel Ziou & Qingshan Jiang, 2024. "VSD: A Novel Method for Video Segmentation and Storage in DNA Using RS Code," Mathematics, MDPI, vol. 12(8), pages 1-21, April.
    8. Christopher N. Takahashi & David P. Ward & Carlo Cazzaniga & Christopher Frost & Paolo Rech & Kumkum Ganguly & Sean Blanchard & Steve Wender & Bichlien H. Nguyen & Jake A. Smith, 2024. "Evaluating the risk of data loss due to particle radiation damage in a DNA data storage system," Nature Communications, Nature, vol. 15(1), pages 1-9, December.

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