IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v10y2019i1d10.1038_s41467-019-13232-z.html
   My bibliography  Save this article

Pathways to cellular supremacy in biocomputing

Author

Listed:
  • Lewis Grozinger

    (Newcastle University)

  • Martyn Amos

    (Northumbria University)

  • Thomas E. Gorochowski

    (University of Bristol
    University of Bristol)

  • Pablo Carbonell

    (Manchester Institute of Biotechnology and School of Chemistry, University of Manchester)

  • Diego A. Oyarzún

    (University of Edinburgh
    University of Edinburgh)

  • Ruud Stoof

    (Newcastle University)

  • Harold Fellermann

    (Newcastle University)

  • Paolo Zuliani

    (Newcastle University)

  • Huseyin Tas

    (Centro Nacional de Biotecnologí­a (CNB-CSIC), Campus de Cantoblanco)

  • Angel Goñi-Moreno

    (Newcastle University)

Abstract

Synthetic biology uses living cells as the substrate for performing human-defined computations. Many current implementations of cellular computing are based on the “genetic circuit” metaphor, an approximation of the operation of silicon-based computers. Although this conceptual mapping has been relatively successful, we argue that it fundamentally limits the types of computation that may be engineered inside the cell, and fails to exploit the rich and diverse functionality available in natural living systems. We propose the notion of “cellular supremacy” to focus attention on domains in which biocomputing might offer superior performance over traditional computers. We consider potential pathways toward cellular supremacy, and suggest application areas in which it may be found.

Suggested Citation

  • Lewis Grozinger & Martyn Amos & Thomas E. Gorochowski & Pablo Carbonell & Diego A. Oyarzún & Ruud Stoof & Harold Fellermann & Paolo Zuliani & Huseyin Tas & Angel Goñi-Moreno, 2019. "Pathways to cellular supremacy in biocomputing," Nature Communications, Nature, vol. 10(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-13232-z
    DOI: 10.1038/s41467-019-13232-z
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-019-13232-z
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-019-13232-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yang Gao & Yuchen Zhou & Xudong Ji & Austin J. Graham & Christopher M. Dundas & Ismar E. Miniel Mahfoud & Bailey M. Tibbett & Benjamin Tan & Gina Partipilo & Ananth Dodabalapur & Jonathan Rivnay & Ben, 2024. "A hybrid transistor with transcriptionally controlled computation and plasticity," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    2. Ahmed A. Agiza & Kady Oakley & Jacob K. Rosenstein & Brenda M. Rubenstein & Eunsuk Kim & Marc Riedel & Sherief Reda, 2023. "Digital circuits and neural networks based on acid-base chemistry implemented by robotic fluid handling," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    3. John P. Marken & Richard M. Murray, 2023. "Addressable and adaptable intercellular communication via DNA messaging," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    4. Judee A. Sharon & Chelsea Dasrath & Aiden Fujiwara & Alessandro Snyder & Mace Blank & Sam O’Brien & Lauren M. Aufdembrink & Aaron E. Engelhart & Katarzyna P. Adamala, 2023. "Trumpet is an operating system for simple and robust cell-free biocomputing," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    5. Alex J. H. Fedorec & Neythen J. Treloar & Ke Yan Wen & Linda Dekker & Qing Hsuan Ong & Gabija Jurkeviciute & Enbo Lyu & Jack W. Rutter & Kathleen J. Y. Zhang & Luca Rosa & Alexey Zaikin & Chris P. Bar, 2024. "Emergent digital bio-computation through spatial diffusion and engineered bacteria," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    6. Yuanli Gao & Lei Wang & Baojun Wang, 2023. "Customizing cellular signal processing by synthetic multi-level regulatory circuits," Nature Communications, Nature, vol. 14(1), pages 1-14, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-13232-z. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.