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Formal Verification of Genetic Circuits

Formal Verification of Genetic Circuits

  • Chris J. Myers18 
  • Conference paper
  • 3463 Accesses

  • 1 Citations

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 7358)

Abstract

Researchers are beginning to be able to engineer synthetic genetic circuits for a range of applications in the environmental, medical, and energy domains [1]. Crucial to the success of these efforts is the development of methods and tools to verify the correctness of these designs. This verification though is complicated by the fact that genetic circuit components are inherently noisy making their behavior asynchronous, analog, and stochastic in nature [2]. Therefore, rather than definite results, researchers are often interested in the probability of the system reaching a given state within a certain amount of time. Usually, this involves simulating the system to produce some time series data and analyzing this data to discern the state probabilities. However, as the complexity of models of genetic circuits grow, it becomes more difficult for researchers to reason about the different states by looking only at time series simulation results of the models. To address this problem, techniques from the formal verification community, such as stochastic model checking, can be leveraged [3,4]. This tutorial will introduce the basic biology concepts needed to understand genetic circuits, as well as, the modeling and analysis techniques currently being employed. Finally, it will give insight into how formal verification techniques can be applied to genetic circuits.

Keywords

  • State Probability
  • Time Series Data
  • Formal Language
  • Computer Hardware
  • IEEE Symposium

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This work is supported by the National Science Foundation under Grants CCF-0916105 and CCF-0916042.

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References

  1. Lucks, J., Arkin, A.: The hunt for the biological transistor. IEEE Spectrum 48(3), 38–43 (2011)

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  2. Elowitz, M.B., Levine, A.J., Siggia, E.D., Swain, P.S.: Stochastic gene expression in a single cell. Science 297(5584), 1183–1186 (2002)

    CrossRef  Google Scholar 

  3. Madsen, C., Myers, C., Patterson, T., Roehner, N., Stevens, J., Winstead, C.: Design and test of genetic circuits using iBioSim. IEEE Design and Test of Computers 29(3) (May/June 2012)

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  4. Madsen, C., Myers, C., Roehner, N., Winstead, C., Zhang, Z.: Utilizing stochastic model checking to analyze genetic circuits. In: IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (2012)

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Author information

Authors and Affiliations

  1. University of Utah, USA

    Chris J. Myers

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  1. Chris J. Myers
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Editor information

Editors and Affiliations

  1. Dept. of Computer Science, University of Illinois at Urbana-Champaign, 3226 Siebel Center, 201 N. Goodwin Avenue, 61801-2302, Urbana, IL, USA

    P. Madhusudan

  2. Dept. of Electrical Engineering and Computer Science, University of California, Berkeley, 253 Cory Hall # 1770, 94720-1770, Berkeley, CA, USA

    Sanjit A. Seshia

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© 2012 Springer-Verlag Berlin Heidelberg

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Myers, C.J. (2012). Formal Verification of Genetic Circuits. In: Madhusudan, P., Seshia, S.A. (eds) Computer Aided Verification. CAV 2012. Lecture Notes in Computer Science, vol 7358. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31424-7_5

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  • DOI: https://doi.org/10.1007/978-3-642-31424-7_5

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  • Print ISBN: 978-3-642-31423-0

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