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access icon openaccess Deterministic inference for stochastic systems using multiple shooting and a linear noise approximation for the transition probabilities

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References

    1. 1)
    2. 2)
    3. 3)
    4. 4)
      • C. Zimmer , S. Sahle .
        4. Zimmer, C., Sahle, S.: ‘Parameter estimation for stochastic models of biochemical reactions’, J. Comput. Sci. Syst. Biol., 2012, 6, pp. 1121.
        . J. Comput. Sci. Syst. Biol. , 11 - 21
    5. 5)
    6. 6)
    7. 7)
    8. 8)
    9. 9)
      • D.A. Henderson , R.J. Boys , C.J. Proctor , D.J. Wilkinson .
        9. Henderson, D.A., Boys, R.J., Proctor, C.J., Wilkinson, D.J.: ‘Linking systems biology models to data: a stochastic kinetic model of p53 oscillations’. The Oxford Handbook of Applied Bayesian Analysis, 2010, pp. 155187.
        . The Oxford Handbook of Applied Bayesian Analysis , 155 - 187
    10. 10)
    11. 11)
    12. 12)
      • T. Toni , D. Welch , N. Strelkowa , A. Ipsen , M.P.H. Stumpf .
        12. Toni, T., Welch, D., Strelkowa, N., Ipsen, A., Stumpf, M.P.H.: ‘Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems’, J. R. Soc., 2008, 6, pp. 187202.
        . J. R. Soc. , 187 - 202
    13. 13)
      • A. Andreychenko , L. Mikeev , D. Spieler , V. Wolf .
        13. Andreychenko, A., Mikeev, L., Spieler, D., Wolf, V.: ‘Approximate maximum likelihood estimation for stochastic chemical kinetics’, EURASIP J. Bioinf. Syst. Biol., 2012, 9.
        . EURASIP J. Bioinf. Syst. Biol.
    14. 14)
    15. 15)
      • C.S. Gillespie , A. Golightly .
        15. Gillespie, C.S., Golightly, A.: ‘Bayesian inference for generalized stochastic population growth models with application to aphids’, Appl. Stat., 2009, 59, (2), pp. 341357.
        . Appl. Stat. , 2 , 341 - 357
    16. 16)
      • L. Mikeev , V. Wolf .
        16. Mikeev, L., Wolf, V.: ‘Parameter estimation for stochastic hybrid models of biochemical reaction networks’. HSCC 12, Beijing, 2012.
        . HSCC 12
    17. 17)
    18. 18)
      • S. Engblom .
        18. Engblom, S.: ‘A discrete spectral method for the chemical master equation’. Technical Report, 2006–036, Uppsala University, 2008.
        .
    19. 19)
    20. 20)
    21. 21)
    22. 22)
      • H. Anderson , T. Britton . (2000)
        22. Anderson, H., Britton, T.: ‘Stochastic epidemic models and their statistical analysis’. vol. 151of Lecture notes in statistics (Springer, Heidelberg, 2000).
        .
    23. 23)
    24. 24)
    25. 25)
    26. 26)
    27. 27)
    28. 28)
      • N.G. van Kampen . (2007)
        28. van Kampen, N.G.: ‘Stochastic processes in physics and chemistry’ (Elsevier, Amsterdam, 2007).
        .
    29. 29)
    30. 30)
      • R. Straube , A. von Kamp .
        30. Straube, R., von Kamp, A.: ‘LiNA – a graphical MATLAB tool for analyzing intrinsic noise in biochemical reaction networks’. online tutorial. 2013. Available at http://www2.mpi-magdeburg.mpg.de/projects/LiNA/Tutorial_LiNA_v1.pdf.
        .
    31. 31)
      • J. Pahle , J.D. Challenger , P. Mendes , A.J. McKane .
        31. Pahle, J., Challenger, J.D., Mendes, P., McKane, A.J.: ‘Biochemical fluctuations, optimisation and the linear noise approximation’, BMC Syst. Biol., 2012, 86, p. 6.
        . BMC Syst. Biol. , 6
    32. 32)
    33. 33)
      • H.G. Bock . (1981)
        33. Bock, H.G.: ‘Numerical treatment of inverse problems in chemical reaction kinetics’, in Ebert, K.H., Deuhard, P., Jäger, W., (Eds.): ‘Modelling of chemical reaction systems’ (Springer, Heidelberg, 1981), vol. 18, pp. 102125. Available at http://www.iwr.uni-heidelberg.de/groups/agbock/FILES/Bock1981.pdf.
        .
    34. 34)
    35. 35)
    36. 36)
    37. 37)
    38. 38)
      • 38. Mathematica: Version 8.0. Wolfram Research, Inc. 2010; Champaign, IL.
        .
    39. 39)
      • 39. Mathematica: Version 9.0. Wolfram Research, Inc. 2012; Champaign, IL.
        .
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