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161 related items for PubMed ID: 23502346

  • 1. On optimality of kernels for approximate Bayesian computation using sequential Monte Carlo.
    Filippi S, Barnes CP, Cornebise J, Stumpf MP.
    Stat Appl Genet Mol Biol; 2013 Mar 26; 12(1):87-107. PubMed ID: 23502346
    [Abstract] [Full Text] [Related]

  • 2. Optimizing threshold-schedules for sequential approximate Bayesian computation: applications to molecular systems.
    Silk D, Filippi S, Stumpf MP.
    Stat Appl Genet Mol Biol; 2013 Oct 01; 12(5):603-18. PubMed ID: 24025688
    [Abstract] [Full Text] [Related]

  • 3. Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems.
    Toni T, Welch D, Strelkowa N, Ipsen A, Stumpf MP.
    J R Soc Interface; 2009 Feb 06; 6(31):187-202. PubMed ID: 19205079
    [Abstract] [Full Text] [Related]

  • 4. Likelihood free inference for Markov processes: a comparison.
    Owen J, Wilkinson DJ, Gillespie CS.
    Stat Appl Genet Mol Biol; 2015 Apr 06; 14(2):189-209. PubMed ID: 25720092
    [Abstract] [Full Text] [Related]

  • 5. Bayesian inference for fitting cardiac models to experiments: estimating parameter distributions using Hamiltonian Monte Carlo and approximate Bayesian computation.
    Nieto Ramos A, Fenton FH, Cherry EM.
    Med Biol Eng Comput; 2023 Jan 06; 61(1):75-95. PubMed ID: 36322242
    [Abstract] [Full Text] [Related]

  • 6. Bayesian parameter estimation for the Wnt pathway: an infinite mixture models approach.
    Koutroumpas K, Ballarini P, Votsi I, Cournède PH.
    Bioinformatics; 2016 Sep 01; 32(17):i781-i789. PubMed ID: 27587701
    [Abstract] [Full Text] [Related]

  • 7. Approximate Bayesian computation (ABC) gives exact results under the assumption of model error.
    Wilkinson RD.
    Stat Appl Genet Mol Biol; 2013 May 06; 12(2):129-41. PubMed ID: 23652634
    [Abstract] [Full Text] [Related]

  • 8. GpABC: a Julia package for approximate Bayesian computation with Gaussian process emulation.
    Tankhilevich E, Ish-Horowicz J, Hameed T, Roesch E, Kleijn I, Stumpf MPH, He F.
    Bioinformatics; 2020 May 01; 36(10):3286-3287. PubMed ID: 32022854
    [Abstract] [Full Text] [Related]

  • 9. The metabolic network of Clostridium acetobutylicum: Comparison of the approximate Bayesian computation via sequential Monte Carlo (ABC-SMC) and profile likelihood estimation (PLE) methods for determinability analysis.
    Thorn GJ, King JR.
    Math Biosci; 2016 Jan 01; 271():62-79. PubMed ID: 26561777
    [Abstract] [Full Text] [Related]

  • 10. pyABC: distributed, likelihood-free inference.
    Klinger E, Rickert D, Hasenauer J.
    Bioinformatics; 2018 Oct 15; 34(20):3591-3593. PubMed ID: 29762723
    [Abstract] [Full Text] [Related]

  • 11. Comparing two sequential Monte Carlo samplers for exact and approximate Bayesian inference on biological models.
    Daly AC, Cooper J, Gavaghan DJ, Holmes C.
    J R Soc Interface; 2017 Sep 15; 14(134):. PubMed ID: 28931636
    [Abstract] [Full Text] [Related]

  • 12. al3c: high-performance software for parameter inference using Approximate Bayesian Computation.
    Stram AH, Marjoram P, Chen GK.
    Bioinformatics; 2015 Nov 01; 31(21):3549-51. PubMed ID: 26142186
    [Abstract] [Full Text] [Related]

  • 13. Estimating parameters of a stochastic cell invasion model with fluorescent cell cycle labelling using approximate Bayesian computation.
    Carr MJ, Simpson MJ, Drovandi C.
    J R Soc Interface; 2021 Sep 01; 18(182):20210362. PubMed ID: 34547212
    [Abstract] [Full Text] [Related]

  • 14. Bayesian parameter inference and model selection by population annealing in systems biology.
    Murakami Y.
    PLoS One; 2014 Sep 01; 9(8):e104057. PubMed ID: 25089832
    [Abstract] [Full Text] [Related]

  • 15. A comparison of approximate versus exact techniques for Bayesian parameter inference in nonlinear ordinary differential equation models.
    Alahmadi AA, Flegg JA, Cochrane DG, Drovandi CC, Keith JM.
    R Soc Open Sci; 2020 Mar 01; 7(3):191315. PubMed ID: 32269786
    [Abstract] [Full Text] [Related]

  • 16. A comparison of Monte Carlo-based Bayesian parameter estimation methods for stochastic models of genetic networks.
    Mariño IP, Zaikin A, Míguez J.
    PLoS One; 2017 Mar 01; 12(8):e0182015. PubMed ID: 28797087
    [Abstract] [Full Text] [Related]

  • 17. Searching for efficient Markov chain Monte Carlo proposal kernels.
    Yang Z, Rodríguez CE.
    Proc Natl Acad Sci U S A; 2013 Nov 26; 110(48):19307-12. PubMed ID: 24218600
    [Abstract] [Full Text] [Related]

  • 18. An automatic adaptive method to combine summary statistics in approximate Bayesian computation.
    Harrison JU, Baker RE.
    PLoS One; 2020 Nov 26; 15(8):e0236954. PubMed ID: 32760106
    [Abstract] [Full Text] [Related]

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