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Synthetic analog computation in living cells

Author

Listed:
  • Ramiz Daniel

    (Analog Circuits and Biological Systems Group, Research Lab of Electronics, Massachusetts Institute of Technology
    Synthetic Biology Group, Research Lab of Electronics, Massachusetts Institute of Technology
    Synthetic Biology Center, Massachusetts Institute of Technology)

  • Jacob R. Rubens

    (Synthetic Biology Group, Research Lab of Electronics, Massachusetts Institute of Technology
    Synthetic Biology Center, Massachusetts Institute of Technology
    MIT Microbiology Program, Massachusetts Institute of Technology)

  • Rahul Sarpeshkar

    (Analog Circuits and Biological Systems Group, Research Lab of Electronics, Massachusetts Institute of Technology
    Synthetic Biology Center, Massachusetts Institute of Technology
    MIT Microbiology Program, Massachusetts Institute of Technology
    Massachusetts Institute of Technology)

  • Timothy K. Lu

    (Synthetic Biology Group, Research Lab of Electronics, Massachusetts Institute of Technology
    Synthetic Biology Center, Massachusetts Institute of Technology
    MIT Microbiology Program, Massachusetts Institute of Technology
    Massachusetts Institute of Technology)

Abstract

Synthetic analog gene circuits can be engineered to execute logarithmically linear sensing, addition, ratiometric and power-law computations in living cells using just three transcription factors.

Suggested Citation

  • Ramiz Daniel & Jacob R. Rubens & Rahul Sarpeshkar & Timothy K. Lu, 2013. "Synthetic analog computation in living cells," Nature, Nature, vol. 497(7451), pages 619-623, May.
    • Handle: RePEc:nat:nature:v:497:y:2013:i:7451:d:10.1038_nature12148
    DOI: 10.1038/nature12148
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    Citations

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    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. Shivang Hina-Nilesh Joshi & Chentao Yong & Andras Gyorgy, 2022. "Inducible plasmid copy number control for synthetic biology in commonly used E. coli strains," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    3. Nadine Bongaerts & Zainab Edoo & Ayan A. Abukar & Xiaohu Song & Sebastián Sosa-Carrillo & Sarah Haggenmueller & Juline Savigny & Sophie Gontier & Ariel B. Lindner & Edwin H. Wintermute, 2022. "Low-cost anti-mycobacterial drug discovery using engineered E. coli," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    4. Luna Rizik & Loai Danial & Mouna Habib & Ron Weiss & Ramez Daniel, 2022. "Synthetic neuromorphic computing in living cells," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    5. 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.
    6. Evgeni V Nikolaev & Eduardo D Sontag, 2016. "Quorum-Sensing Synchronization of Synthetic Toggle Switches: A Design Based on Monotone Dynamical Systems Theory," PLOS Computational Biology, Public Library of Science, vol. 12(4), pages 1-33, April.
    7. Tai-Yin Chiu & Hui-Ju K Chiang & Ruei-Yang Huang & Jie-Hong R Jiang & François Fages, 2015. "Synthesizing Configurable Biochemical Implementation of Linear Systems from Their Transfer Function Specifications," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-27, September.

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