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Semi-quantitative Abstraction and Analysis of Chemical Reaction Networks (Extended Abstract)

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Computational Methods in Systems Biology (CMSB 2019)

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Abstract

Chemical Reaction Networks (CRNs) are a versatile language widely used for modelling and analysis of biochemical systems [4] as well as for high-level programming of molecular devices [1, 14].

This work has been accepted to the 31st International Conference on Computer-Aided Verification (CAV’19). The full version of the paper is available at [3]. The work has been supported by the Czech Science Foundation grant No. GA19-24397S, the IT4Innovations excellence in science project No. LQ1602, and the German Research Foundation (DFG) project KR 4890/2-1 “Statistical Unbounded Verification”.

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References

  1. Cardelli, L.: Two-domain DNA strand displacement. Math. Struct. Comput. Sci. 23(02), 247–271 (2013)

    Article  MathSciNet  Google Scholar 

  2. Cardelli, L., Kwiatkowska, M., Laurenti, L.: A Stochastic hybrid approximation for chemical kinetics based on the linear noise approximation. In: Bartocci, E., Lio, P., Paoletti, N. (eds.) CMSB 2016. LNCS, vol. 9859, pp. 147–167. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-45177-0_10

    Chapter  Google Scholar 

  3. Češka, M., Křetínský, J.: Semi-quantitative abstraction and analysis of chemical reaction networks. Tech. Rep. abs/1905.09914 (2019)

  4. Chellaboina, V., Bhat, S.P., Haddad, W.M., Bernstein, D.S.: Modeling and analysis of mass-action kinetics. IEEE Control Syst. Mag. 29(4), 60–78 (2009)

    Article  MathSciNet  Google Scholar 

  5. Gandhi, S.J., Zenklusen, D., Lionnet, T., Singer, R.H.: Transcription of functionally related constitutive genes is not coordinated. Nat. Struct. Mol. Biol. 18(1), 27 (2011)

    Article  Google Scholar 

  6. Giacobbe, M., Guet, C.C., Gupta, A., Henzinger, T.A., Paixão, T., Petrov, T.: Model checking gene regulatory networks. In: Baier, C., Tinelli, C. (eds.) TACAS 2015. LNCS, vol. 9035, pp. 469–483. Springer, Heidelberg (2015). https://doi.org/10.1007/978-3-662-46681-0_47

    Chapter  Google Scholar 

  7. Gillespie, D.T.: Exact stochastic simulation of coupled chemical reactions. J. Phys. Chem. 81(25), 2340–2361 (1977)

    Article  Google Scholar 

  8. Golding, I., Paulsson, J., Zawilski, S.M., Cox, E.C.: Real-time kinetics of gene activity in individual bacteria. Cell 123(6), 1025–1036 (2005)

    Article  Google Scholar 

  9. Goutsias, J.: Quasiequilibrium approximation of fast reaction kinetics in stochastic biochemical systems. J. Chem. Phys. 122(18), 184102 (2005)

    Article  Google Scholar 

  10. Hasenauer, J., Wolf, V., Kazeroonian, A., Theis, F.: Method of conditional moments (MCM) for the chemical master equation. J. Math. Biol. 69(3), 1–49 (2013)

    MATH  Google Scholar 

  11. Heath, J., Kwiatkowska, M., Norman, G., Parker, D., Tymchyshyn, O.: Probabilistic model checking of complex biological pathways. Theor. Comput. Sci. 391(3), 239–257 (2008)

    Article  MathSciNet  Google Scholar 

  12. Lakin, M.R., Parker, D., Cardelli, L., Kwiatkowska, M., Phillips, A.: Design and analysis of DNA strand displacement devices using probabilistic model checking. J. R. Soc. Interface 9(72), 1470–1485 (2012)

    Article  Google Scholar 

  13. Salis, H., Kaznessis, Y.: Accurate hybrid stochastic simulation of a system of coupled chemical or biochemical reactions. J. Chem. Phys. 122(5), 054103 (2005)

    Article  Google Scholar 

  14. Soloveichik, D., Seelig, G., Winfree, E.: DNA as a universal substrate for chemical kinetics. Proc. Nat. Acad. Sci. U.S.A. 107(12), 5393–5398 (2010)

    Article  Google Scholar 

  15. Van Kampen, N.G.: Stochastic Processes in Physics and Chemistry, vol. 1. Elsevier, Amsterdam (1992)

    MATH  Google Scholar 

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Correspondence to Milan Češka .

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Češka, M., Křetínský, J. (2019). Semi-quantitative Abstraction and Analysis of Chemical Reaction Networks (Extended Abstract). In: Bortolussi, L., Sanguinetti, G. (eds) Computational Methods in Systems Biology. CMSB 2019. Lecture Notes in Computer Science(), vol 11773. Springer, Cham. https://doi.org/10.1007/978-3-030-31304-3_22

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  • DOI: https://doi.org/10.1007/978-3-030-31304-3_22

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