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Research / Publications

My profile on Google Scholar is a good way to get an overview of my publication profile. My ORCID ID is 0000-0003-0736-802X, but I do not actively maintain this profile.

Papers in submission

These are papers currently under review for publication. Published and accepted papers are listed below.

• Jow, H., Boys, R. J., Wilkinson, D. J. (2011) Bayesian identification of protein differential expression in multi-group isobaric labelled mass spectrometry data, in submission.
• Heydari, J. J., Lawless, C., Lydall, D. A., Wilkinson, D. J. (2012) Bayesian hierarchical modelling for inferring genetic interactions in yeast, in submission.

Published work

Below is a list of my published (and accepted) work, in reverse chronological order.

2008-2013

• Evans, M. R., Grimm, V., Johst, K., Knuutila, T., de Langhe, R., Lessells, K., Merz, M., O'Malley, M. A., Orzack, S., Weisberg, M., Wilkinson, D. J., Wolkenhauer, O., Benton, T. G. (2013) Do simple models lead to generality in ecology?, Trends in Ecology and Evolution, online now.
• Andrew, E. J., Merchan, S., Lawless, C., Banks, A. P., Wilkinson, D. J., Lydall, D. A. (2013) Evidence that the pentose phosphate pathway is required for resistance to the G-quadruplex binder TMPyP4, PLoS ONE, 8(6): e66242.
• McAuley, M. T., Wilkinson, D. J., Jones, J. L., Kirkwood, T. B. L. (2012) A whole body mathematical model of cholesterol metabolism and its age associated dysregulation, BMC Systems Biology, 6:130.
• Weile, J., James, K., Hallinan, J., Cockell, S. J., Lord, P., Wipat, A., Wilkinson, D. J. (2012) Bayesian integration of networks without gold standards, Bioinformatics, 28(11):1495-1500.
• Gillespie, C. S., Milner, P., Wilkinson, D. J. (2012) Moment closure based parameter inference of stochastic kinetic models, Statistics and Computing, 23(2):287-295.
• Golightly, A., Wilkinson, D. J. (2011) Bayesian parameter inference for stochastic biochemical network models using particle MCMC, Interface Focus, 1(6):807-820.
• Wilkinson, D. J. (2011) Stochastic modelling for systems biology, second edition, Boca Raton, Florida: Chapman and Hall/CRC Press.
• Lei, G., Boys, R. J., Gillespie, C. S., Greenall, A. J., Wilkinson, D. J. (2011) Bayesian inference for sparse VAR(1) models, with application to time course microarray data, Journal of Biometrics and Biostatistics, 2:127.
• Courtot, M., Juty, N., Knupfer, C., Waltemath, D., Zhukova, A., Drager, A., Dumontier, M., Finney, A., Golebiewski, M., Hastings, J., Hoops, S., Keating, S., Kell, D. B., Kerrien, S., Lawson, J., Lister, A., Lu, J., Machne, R., Mendes, P., Pocock, M., Rodriguez, N., Villeger, A., Wilkinson, D. J., Wimalaratne, S., Laibe, C., Hucka, M., Le Novere, N. (2011) Controlled vocabularies and semantics in systems biology, Molecular Systems Biology, 7:543.
• Chang, H., Lawless, C., Addinall, S. G., Oexle, S., Taschuk, M., Wipat, A., Wilkinson, D. J., Lydall, D. A. (2011) Genome-wide analysis to identify pathways affecting telomere initiated senescence in budding yeast, G3: Genes, Genomes, Genetics, 1(3):197-208.
• Milner, P., Gillespie, C. S., Wilkinson, D. J. (2011) Moment closure approximations for stochastic kinetic models with rational rate laws, Mathematical Biosciences, 231(2):99-104.
• Addinall, S. G., Holstein, E., Lawless, C., Yu, M., Chapman, K., Taschuk, M., Young, A., Ciesiolka, A., Lister, A., Wipat, A., Wilkinson, D. J., Lydall, D. A. (2011) Quantitative fitness analysis shows that NMD proteins and many other protein complexes suppress or enhance distinct telomere cap defects, PLoS Genetics, 7(4): e1001362.
• Wilkinson, D. J. (2011) Stochastic dynamical systems, in Handbook of Statistical Systems Biology, M.P.H. Stumpf, D.J. Balding, M. Girolami (eds), Wiley, pp 359-375.
• Weile, J., Pocock, M., Cockell, S. J., Lord, P., Dewar, J., Holstein, E., Wilkinson, D. J., Lydall, D. A., Hallinan, J. S., Wipat, A. (2011) Customisable views on semantically integrated networks for systems biology, Bioinformatics, 27(9):1299-1306.
• Jow, H., Boys, R. J., Wilkinson, D. J. (2011) A Comparative Genomics Approach to the identification of QTL candidate genes, REVSTAT, 9(1):1-17.
• Wilkinson, D. J. (2011) Parameter inference for stochastic kinetic models of bacterial gene regulation: a Bayesian approach to systems biology (with discussion), in J.-M. Bernardo et al (eds) Bayesian Statistics 9, OUP, pp679-706.
• Lawless, C., Wilkinson, D. J., Addinall, S. G., Lydall, D. A. (2010) Colonyzer: automated quantification of characteristics of microorganism colonies growing on solid agar, BMC Bioinformatics, 11:287. [Colonyzer website]
• Jow, H., Bhattacharjee, M., Boys, R. J., Wilkinson, D. J. (2010) The integration of genetic maps using Bayesian inference, Journal of Computational Biology, 17(6):825-840.
• Cockell, S. J., Weile, J., Lord, P., Wipat, C., Andriychenko, D., Hallinan, J., Pocock, M. R., Wilkinson, D. J., Young, M. P., Wipat, A. (2010) An integrated data set for in silico drug discovery, Integrative Bioinformatics, 7(3):116.
• Lei, G., Gillespie, C. S., Boys, R. J., Greenall, A. J., Wilkinson, D. J. (2010) Analysing yeast time course microarray data using BioConductor: a case study using yeast2 Affymetrix arrays, BMC Research Notes, 3:81.
• Golightly, A., Wilkinson, D. J. (2010) Discussion of "Particle Markov chain Monte Carlo methods" by Andrieu, Doucet and Holenstein, Journal of the Royal Statistical Society, Series B, 72(3):322.
• Chen, Y., Lawless, C., Gillespie, C. S., Wu, J., Boys, R. J., Wilkinson, D. J. (2010) CaliBayes and BASIS: integrated tools for the calibration, simulation and storage of biological simulation models, Briefings in Bioinformatics, 11(3):278-289.
• Wilkinson, D. J., Golightly, A. (2010) Markov chain Monte Carlo algorithms for SDE parameter estimation, in N. D. Lawrence et al (eds), Learning and Inference for Computational Systems Biology, MIT Press, pp.253-275.
• Henderson, D. A., Boys, R. J., Proctor, C. J., 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.) Oxford Handbook of Applied Bayesian Analysis, Oxford University Press, pp.155-187.
• Hucka, M., Bergmann, F., Hoops, S., Keating, S., Sahle, S., and Wilkinson, D. J. (2010) The Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 1 Core. Nature Precedings doi:10.1038/npre.2010.4959.1
• Henderson, D. A., Boys, R. J., Wilkinson, D. J. (2010) Bayesian calibration of a stochastic kinetic computer model using multiple data sources, Biometrics, 66(1):249-256.
• Henderson, D. A., Boys, R. J., Krishnan, K. J., Lawless, C., 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(485):76-87.
• Mc Auley, M., Kenny, R. A., Kirkwood, T. B. L., Wilkinson, D. J., Jones, J. L., and Miller, V. (2009) A mathematical model of aging-related and cortisol induced hippocampal dysfunction, BMC Neuroscience, 10:26.
• Wilkinson, D. J. (2009) Stochastic modelling for quantitative description of heterogeneous biological systems, Nature Reviews Genetics, 10(2):122-133.
• Hucka, M., Hoops, S., Keating, S., Le Novere, N., Sahle, S., and Wilkinson, D. J. (2008) Systems Biology Markup Language (SBML) Level 2: Structures and Facilities for Model Definitions. Nature Precedings doi:10.1038/npre.2008.2715.1
• Addinall, S. G., Downey, M., Yu, M., Zukbo, M. K., Greenall, A. J., Wilkinson, D. J., James, K., Leake, A., Dewar, J., Shaw, O., Hallinan, J., Boone, C., Wipat, A., Durocher, D., Lydall, D. (2008) A genome-wide suppressor and enhancer analysis of cdc13-1 reveals varied cellular processes impacting telomere capping, Genetics, 180:2251-2266.
• Greenall, A., Lei, G., Swan, D. C., James, K., Wang, L., Peters, H., Wipat, A., Wilkinson, D. J., Lydall, D. A. (2008) A genome wide analysis of the response to uncapped telomeres in budding yeast reveals a novel role for NAD+ biosynthetic gene BNA2 in chromosome end protection, Genome Biology, 9:R146.
• Boys, R. J., Wilkinson, D. J., Kirkwood, T. B. L. (2008) Bayesian inference for a discretely observed stochastic kinetic model, Statistics and Computing, 18(2):125-135.
• Evans, T. W., Gillespie, C. S., Wilkinson, D. J. (2008) The SBML discrete stochastic models test suite, Bioinformatics, 24:285-286 [DSMTS website].
• Golightly, A., Wilkinson, D. J. (2008) Bayesian inference for nonlinear multivariate diffusion models observed with error, Computational Statistics and Data Analysis, 52(3):1674-1693.

2001-2007

• Wilkinson, D. J. (2007) Bayesian methods in bioinformatics and computational systems biology, Briefings in Bioinformatics, 8(2), 109-116.
• Proctor, C. J., Lydall, D. A., Boys, R. J., Gillespie, C. S., Shanley, D. P., Wilkinson, D. J., Kirkwood, T. B. L. (2007) Modelling the checkpoint response to telomere uncapping in budding yeast, Journal of the Royal Society Interface, 4(12):73-90.
• Wilkinson, D. J. (2007) Invited discussion to "Fast Bayesian shape matching using geometric algorithms" by S. C. Schmidler. Bayesian Statistics 8, Oxford Science Publications: Oxford, 471-490.
• Gillespie, C. S., Wilkinson, D. J., Shanley, D. P., Proctor, C. J., Boys, R. J., Kirkwood, T. B. L. (2006) BASIS: An internet resource for network modelling, Journal of Integrative Bioinformatics, 3(2):26.
• Golightly, A., Wilkinson, D. J. (2006) Bayesian sequential inference for nonlinear multivariate diffusions, Statistics and Computing, 16:323-338.
• Wilkinson, D. J. (2006) Stochastic modelling for systems biology, Boca Raton, Florida: Chapman and Hall/CRC Press.
• Golightly, A., Wilkinson, D. J. (2006) Bayesian sequential inference for stochastic kinetic biochemical network models, Journal of Computational Biology, 13(3):838-851.
• Gillespie, C. S., Wilkinson, D. J., Proctor, C. J., Shanley, D. P., Boys, R. J., Kirkwood, T. B. L. (2006) Tools for the SBML community, Bioinformatics, 22(5):628-629.
• Golightly, A., Wilkinson, D. J. (2005) Bayesian inference for stochastic kinetic models using a diffusion approximation, Biometrics, 61(3):781-788.
• Kirkwood, T. B. L., Boys, R. J., Gillespie, C. S., Proctor, C. J., Shanley, D. P., Wilkinson, D. J. (2005) Computer Modeling in the Study of Aging, in S. N. Austad, E. J. Masoro (eds.) Handbook of the Biology of Aging, Sixth Edition, Academic Press, 334-357.
• Wilkinson, D. J. (2005) Parallel Bayesian Computation, Chapter 16 in E. J. Kontoghiorghes (ed.) Handbook of Parallel Computing and Statistics, Marcel Dekker/CRC Press, 481-512.
• Gillespie, C. S., Proctor, C. J., Shanley, D. P., Wilkinson, D. J., Boys, R. J., Kirkwood T. B. L. (2005) Web-services for the biology community: the BASIS project, Proceedings of the UK e-Science All Hands Meeting, Nottingham, UK, 491-493.
• Proctor, C. J., Soti, C., Boys, R. J., Gillespie, C. S., Shanley, D. P., Wilkinson, D. J., Kirkwood, T. B. L. (2005) Modelling the actions of chaperones and their role in ageing, Mechanisms of Ageing and Development, 126(1):119-131.
• Gillespie, C. S., Proctor, C. J., Boys, R. J., Shanley, D. P., Wilkinson, D. J., Kirkwood, T. B. L. (2004) A mathematical model of ageing in yeast, Journal of Theoretical Biology, 229(2):189-196.
• Wilkinson, D. J., Yeung, S. K. H. (2004) A sparse matrix approach to Bayesian computation in large linear models, Computational Statistics and Data Analysis, 44(3):493-516.
• Kirkwood, T. B. L., Boys, R. J., Gillespie, C. S., Proctor, C. J., Shanley, D. P., Wilkinson, D. J. (2003) Towards an e-biology of ageing: integrating theory and data, Nature Reviews Molecular Cell Biology, 4(3): 243-249.
• Garside, L. M., Wilkinson, D. J. (2003) Dynamic lattice-Markov spatio-temporal models for environmental data, Bayesian Statistics 7, Oxford Science Publications: Oxford, 535-542.
• Wilkinson, D. J. (2003) Discussion to "Non-centered parameterisations for hierarchical models and data augmentation" by Papaspiliopoulos, Roberts and Skold. Bayesian Statistics 7, Oxford Science Publications: Oxford, 323-324.
• Wilkinson, D. J., Yeung, S. K. H. (2002) Conditional simulation from highly structured Gaussian systems, with application to blocking-MCMC for the Bayesian analysis of very large linear models, Statistics and Computing, 12(3): 287-300.
• Yeung, S. K. H., Wilkinson, D. J. (2002) Adaptive Metropolis-Hastings samplers for the Bayesian analysis of large linear Gaussian systems, Computing Science and Statistics, 33: 128-138.
• Simpson, A., Wilkinson, D. J. (2002) Computationally intensive techniques for a fully Bayesian, decision theoretic approach to financial forecasting and portfolio selection, Computing Science and Statistics, 33: 472-483.
• Wilkinson, D. J. (2002) GDAGsim: Sparse matrix algorithms for Bayesian computation, Computing Science and Statistics, 33: 154-162.
• Goldstein, M., Wilkinson, D. J. (2001) Restricted prior inference for complex uncertainty structures, Annals of Mathematics and Artificial Intelligence, 32: 315-334.

1996-2000

• Goldstein, M., Wilkinson, D. J. (2000) Bayes linear analysis for graphical models: The geometric approach to local computation and interpretive graphics. Statistics and Computing, 10(4): 311-324.
• Glazebrook, K. D., Wilkinson, D. J. (2000) Index-based policies for discounted multi-armed bandits on parallel machines. The Annals of Applied Probability, 10: 877-896.
• Simpson, A., Wilkinson, D. J. (2000) Multivariate DLMs for financial time series, with application to the management of portfolios. In J. G. Bethlehem and P. G. M. van der Heijden (eds.) Proceedings in Computational Statistics 2000, Physica Verlag, Heidelberg, 457-462.
• Boys, R. J., Henderson, D. A., Wilkinson, D. J. (2000) Detecting homogeneous segments in DNA sequences by using hidden Markov models. Journal of the Royal Statistical Society, Series C, 49(2): 269-285.
• Wilkinson, D. J. (1998) An object-oriented approach to local computation in Bayes linear belief networks. In P. J. Green and R. W. Payne (eds.) Proceedings in Computational Statistics 1998, Physica Verlag, Heidelberg, 491-496.
• Wilkinson, D. J. (1997) Bayes linear variance adjustment for locally linear DLMs. Journal of Forecasting, 16(5): 329-342.
• Wilkinson, D. J., Goldstein, M. (1996) Bayes linear adjustment for variance matrices. In J. M. Bernardo et al (eds.) Bayesian Statistics 5, Proceedings of the fifth Valencia international meeting, June 1994, OUP, Oxford, 791-799.