GpABC: a Julia package for approximate Bayesian computation with Gaussian process emulation

Evgeny Tankhilevich, Jonathan Ish-Horowicz, Tara Hameed, Elisabeth Roesch, Istvan Kleijn, Michael PH Stumpf, Fei He

Research output: Contribution to journalArticle

Abstract

Approximate Bayesian computation (ABC) is an important framework within which to infer the structure and parameters of a systems biology model. It is especially suitable for biological systems with stochastic and nonlinear dynamics, for which the likelihood functions are intractable. However, the associated computational cost often limits ABC to models that are relatively quick to simulate in practice. We here present a Julia package, GpABC, that implements parameter inference and model selection for deterministic or stochastic models using i) standard rejection ABC or ABC-SMC, or ii) ABC with Gaussian process emulation. The latter significantly reduces the computational cost.
Original languageEnglish
Pages (from-to)769299
Number of pages1
JournalbioRxiv
DOIs
Publication statusPublished - 18 Sep 2019

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Biological systems
Stochastic models
Costs
Systems Biology

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Tankhilevich, E., Ish-Horowicz, J., Hameed, T., Roesch, E., Kleijn, I., Stumpf, M. PH., & He, F. (2019). GpABC: a Julia package for approximate Bayesian computation with Gaussian process emulation. bioRxiv, 769299. https://doi.org/10.1101/769299

GpABC: a Julia package for approximate Bayesian computation with Gaussian process emulation. / Tankhilevich, Evgeny; Ish-Horowicz, Jonathan; Hameed, Tara; Roesch, Elisabeth; Kleijn, Istvan; Stumpf, Michael PH; He, Fei.

In: bioRxiv, 18.09.2019, p. 769299.

Research output: Contribution to journalArticle

Tankhilevich, E, Ish-Horowicz, J, Hameed, T, Roesch, E, Kleijn, I, Stumpf, MPH & He, F 2019, 'GpABC: a Julia package for approximate Bayesian computation with Gaussian process emulation' bioRxiv, pp. 769299. https://doi.org/10.1101/769299
Tankhilevich E, Ish-Horowicz J, Hameed T, Roesch E, Kleijn I, Stumpf MPH et al. GpABC: a Julia package for approximate Bayesian computation with Gaussian process emulation. bioRxiv. 2019 Sep 18;769299. https://doi.org/10.1101/769299
Tankhilevich, Evgeny ; Ish-Horowicz, Jonathan ; Hameed, Tara ; Roesch, Elisabeth ; Kleijn, Istvan ; Stumpf, Michael PH ; He, Fei. / GpABC: a Julia package for approximate Bayesian computation with Gaussian process emulation. In: bioRxiv. 2019 ; pp. 769299.
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