Reprogrammable biological logic gate that exploits noise

Anna Dari; Adi R. Bulsara; William L. Ditto; Xiao Wang

doi:10.1109/BioCAS.2011.6107796

Reprogrammable biological logic gate that exploits noise

Anna Dari, Adi R. Bulsara, William L. Ditto, Xiao Wang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Scopus citations

Abstract

Computation underlies the genetic regulatory network activities. Previous studies have designed and engineered systems that can perform single logic gate functionalities, trying to avoid external and internal random fluctuations. In this work, we demonstrate the possibility to exploit noise when it cannot be eliminated. In particular, we adapt the LSR paradigm to a single-gene network derived from the bacteriophage λ and to a more robust two-gene network derived from the yeast S. cerevisiae. Our results demonstrate that in both cases there is an optimal amount of noise where the biological logic gate can be externally reprogrammed (i.e. switch from the AND to the OR gate) and perform well according to the truth table.

Original language	English (US)
Title of host publication	2011 IEEE Biomedical Circuits and Systems Conference, BioCAS 2011
Pages	337-340
Number of pages	4
DOIs	https://doi.org/10.1109/BioCAS.2011.6107796
State	Published - Dec 1 2011
Event	2011 IEEE Biomedical Circuits and Systems Conference, BioCAS 2011 - San Diego, CA, United States Duration: Nov 10 2011 → Nov 12 2011

Publication series

Name	2011 IEEE Biomedical Circuits and Systems Conference, BioCAS 2011

Other

Other	2011 IEEE Biomedical Circuits and Systems Conference, BioCAS 2011
Country/Territory	United States
City	San Diego, CA
Period	11/10/11 → 11/12/11

ASJC Scopus subject areas

Hardware and Architecture
Biomedical Engineering
Electrical and Electronic Engineering

Access to Document

10.1109/BioCAS.2011.6107796

Cite this

Dari, A, Bulsara, AR, Ditto, WL & Wang, X 2011, Reprogrammable biological logic gate that exploits noise. in 2011 IEEE Biomedical Circuits and Systems Conference, BioCAS 2011., 6107796, 2011 IEEE Biomedical Circuits and Systems Conference, BioCAS 2011, pp. 337-340, 2011 IEEE Biomedical Circuits and Systems Conference, BioCAS 2011, San Diego, CA, United States, 11/10/11. https://doi.org/10.1109/BioCAS.2011.6107796

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abstract = "Computation underlies the genetic regulatory network activities. Previous studies have designed and engineered systems that can perform single logic gate functionalities, trying to avoid external and internal random fluctuations. In this work, we demonstrate the possibility to exploit noise when it cannot be eliminated. In particular, we adapt the LSR paradigm to a single-gene network derived from the bacteriophage λ and to a more robust two-gene network derived from the yeast S. cerevisiae. Our results demonstrate that in both cases there is an optimal amount of noise where the biological logic gate can be externally reprogrammed (i.e. switch from the AND to the OR gate) and perform well according to the truth table.",

author = "Anna Dari and Bulsara, {Adi R.} and Ditto, {William L.} and Xiao Wang",

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N2 - Computation underlies the genetic regulatory network activities. Previous studies have designed and engineered systems that can perform single logic gate functionalities, trying to avoid external and internal random fluctuations. In this work, we demonstrate the possibility to exploit noise when it cannot be eliminated. In particular, we adapt the LSR paradigm to a single-gene network derived from the bacteriophage λ and to a more robust two-gene network derived from the yeast S. cerevisiae. Our results demonstrate that in both cases there is an optimal amount of noise where the biological logic gate can be externally reprogrammed (i.e. switch from the AND to the OR gate) and perform well according to the truth table.

AB - Computation underlies the genetic regulatory network activities. Previous studies have designed and engineered systems that can perform single logic gate functionalities, trying to avoid external and internal random fluctuations. In this work, we demonstrate the possibility to exploit noise when it cannot be eliminated. In particular, we adapt the LSR paradigm to a single-gene network derived from the bacteriophage λ and to a more robust two-gene network derived from the yeast S. cerevisiae. Our results demonstrate that in both cases there is an optimal amount of noise where the biological logic gate can be externally reprogrammed (i.e. switch from the AND to the OR gate) and perform well according to the truth table.

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Reprogrammable biological logic gate that exploits noise

Abstract

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