Daniel Henderson

E-mail: daniel.henderson(at)ncl.ac.uk

Research interests

• Bayesian modelling and data analysis
• Calibration of complex computer models
• Density estimation and smoothing
• Applications in systems biology

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Recent publications

Henderson, D. A., Boys, R. J., Proctor, C. J. and Wilkinson, D. J. (2010) Linking systems biology models to data: a stochastic kinetic model of p53 oscillations. In A. O'Hagan and M. West (eds.) The Oxford Handbook of Applied Bayesian Analysis, Oxford University Press.

Henderson, D. A., Boys, R. J. and Wilkinson, D. J. (2010) Bayesian calibration of a stochastic kinetic computer model using multiple data sources. Biometrics, 66, 249-256. [Supplementary material]

Jones, M. C. and Henderson, D. A. (2009) Maximum likelihood kernel density estimation: on the potential of convolution sieves. Computational Statistics and Data Analysis, 53, 3726-3733. (The supporting technical report cited in this paper is available here.)

Henderson, D. A., Boys, R. J., Krishnan, K. J., Lawless, C. and Wilkinson, D. J. (2009) Bayesian emulation and calibration of a stochastic computer model of mitochondrial DNA deletions in substantia nigra neurons. Journal of the American Statistical Association, 104, 76-87. [Supplementary material]

Jones, M. C. and Henderson, D. A. (2007) Kernel-type density estimation on the unit interval. Biometrika, 94, 977-984. (The supporting technical report cited in this paper is available here.)

Submitted

Golightly, A., Henderson, D. A. and Sherlock, C. Efficient particle MCMC for exact inference in stochastic biochemical network models through approximation of expensive likelihoods.