Background

Although my background and particular expertise are both in Bayesian statistical inference, I have a broad range of research interests, cutting across mathematics, statistics, probability theory, modelling, computing science, and molecular and systems biology. 

Most of my current research interests involve applications of Bayesian statistics to a variety of challenging problems in Molecular biology, Bioinformatics and Systems Biology. I am especially interested in parameter inference for dynamic biological models, and the use of approximate models and (stochastic) model emulators for rendering computationally prohibitive algorithms for "big data" more tractable. I'm also interested in functional programming for statistical computing and probabilistic programming.

Areas of expertise

• Bayesian statistics
• Big data
• Computational systems biology
• Genomics

Roles and Responsibilities

Internal:

• Co-Director of the EPSRC Centre for Doctoral Training in Cloud Computing for Big Data

External:

• Associate Editor for the SIAM/ASA Journal of Uncertainty Quantification

Google scholar: Click here..

SCOPUS: Click here.

Research

Research Interests

• Bayesian analysis and Bayesian software development
• Dynamic and graphical models, and Markov processes
• Statistical bioinformatics and stochastic modelling in Systems Biology
• Cloud computing technology for big data and computational statistics
• Efficient Bayesian computation and Bayes linear methods

Teaching

MAS8381: Statistics for Big Data

Publications

• Oyebamiji OK, Wilkinson DJ, Pahala-Gedara J, Rushton SP, Li B, Bridgens B, Zuliani P. A Bayesian approach to modelling the impact of hydrodynamic shear stress on biofilm deformation. PLOS ONE 2018, 13(4), e0195484.
• Lee C, Garbett A, Wilkinson DJ. A network epidemic model for online community commissioning data. Statistics and Computing 2018, 28(4), 891-904.
• Law J, Wilkinson DJ. Composable Models for Online Bayesian Analysis of Streaming Data. Statistics and Computing 2018, 28(6), 1119-1137.
• Mitchell AL, Scheremetjew M, Denise H, Potter S, Tarkowska A, Qureshi M, Salazar GA, Pesseat S, Boland MA, Hunter FMI, Ten Hoopen P, Alako B, Amid C, Wilkinson DJ, Curtis TP, Cochrane G, Finn RD. EBI Metagenomics in 2017: Enriching the analysis of microbial communities, from sequence reads to assemblies. Nucleic Acids Research 2018, 46(D1), D726-D735.
• Jayathilake PG, Gupta P, Li B, Madsen C, Oyebamiji O, Gonzalez-Cabaleiro R, Rushton S, Bridgens B, Swailes D, Allen B, McGough AS, Zuliani P, Ofiteru ID, Wilkinson DJ, Chen J, Curtis TP. A mechanistic individual-based model of microbial communities. PLoS One 2017, 12(8), e0181965.
• Oyebamiji OK, Wilkinson DJ, Jayathilake PG, Curtis TP, Rushton SP, Li B, Gupta P. Gaussian process emulation of an individual-based model simulation of microbial communities. Journal of Computational Science 2017, 22, 69-84.
• Holstein EM, Ngo G, Lawless C, Banks P, Greetham M, Wilkinson D, Lydall D. Systematic Analysis of the DNA Damage Response Network in Telomere Defective Budding Yeast. G3: Genes, Genomes, Genetics 2017, 7(7), 2375-2389.
• Heydari JJ, Lawless C, Lydall DA, Wilkinson DJ. Bayesian hierarchical modelling for inferring genetic interactions in yeast. Journal of the Royal Statistics Society: Series C (Applied Statistics) 2016, 65(3), 367-393.
• Oyebamiji OK, Wilkinson DJ. Statistical emulation as a tool for analysing complex multiscale stochastic biological model outputs. In: VIII International Conference on Sensitivity Analysis of Model Output. 2016, The University of Reunion Island, Le Tampon.
• Golightly A, Wilkinson DJ. Bayesian inference for Markov jump processes with informative observations. Statistical Applications in Genetics and Molecular Biology 2015, 14(2), 169-188.
• Owen J, Wilkinson DJ, Gillespie CS. Likelihood free inference for Markov processes: a comparison. Statistical Applications in Genetics and Molecular Biology 2015, 14(2), 189–209.
• Narayanan S, Dubarry M, Lawless C, Banks AP, Wilkinson DJ, Whitehall SK, Lydall D. Quantitative Fitness Analysis Identifies exo1∆ and Other Suppressors or Enhancers of Telomere Defects in Schizosaccharomyces pombe. PloS ONE 2015, 10(7), e0132240.
• Owen J, Wilkinson DJ, Gillespie CS. Scalable inference for Markov processes with intractable likelihoods. Statistics and Computing 2015, 25(1), 145-156.
• Jow H, Boys RJ, Wilkinson DJ. Bayesian identification of protein differential expression in multi-group isobaric labelled mass spectrometry data. Statistical Applications in Genetics and Molecular Biology 2014, 13(5), 531-551.
• Heydari J, Lawless C, Lydall DA, Wilkinson DJ. Fast Bayesian parameter estimation for stochastic logistic growth models. Biosystems 2014, 122, 55-72.
• Evans MR, Grimm V, Johst K, Knuutila T, deLanghe R, Lessells K, Merz M, O'Malley MA, Orzack S, Weisberg M, Wilkinson DJ, Wolkenhauer O, Benton TG. Do simple models lead to generality in ecology?. Trends in Ecology and Evolution 2013, 28(10), 578-583.
• Milner P, Gillespie CS, Wilkinson DJ. Moment closure based parameter inference of stochastic kinetic models. Statistics and Computing 2013, 23(2), 287-295.
• Andrew EJ, Merchan S, Lawless C, Banks AP, Wilkinson DJ, Lydall D. Pentose Phosphate Pathway Function Affects Tolerance to the G-Quadruplex Binder TMPyP4. PLoS One 2013, 8(6), e66242.
• McAuley MT, Wilkinson DJ, Jones JJL, Kirkwood TBL. A whole body mathematical model of cholesterol metabolism and its age associated dysregulation. BMC Systems Biology 2012, 6(1), 130.
• Weile J, James K, Hallinan J, Cockell SJ, Lord P, Wipat A, Wilkinson DJ. Bayesian integration of networks without gold standards. Bioinformatics 2012, 28(11), 1495-1500.
• Jow H, Boys RJ, Wilkinson DJ. A comparative genomics approach to the identification of QTL candidate genes. Revstat Statistical Journal 2011, 9(1), 1-17.
• Lei G, Boys RJ, Gillespie CS, Greenall AJ, Wilkinson DJ. Bayesian inference for sparse VAR(1) models, with application to time course microarray data. Journal of Biometrics and Biostatistics 2011, 2(127).
• Golightly A, Wilkinson DJ. Bayesian parameter inference for stochastic biochemical network models using particle Markov chain Monte Carlo. Interface Focus 2011, 1(6), 807-820.
• 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 DB, Kerrien S, Lawson J, Lister A, Lu J, Machne R, Mendes P, Pocock M, Rodriguez N, Villeger A, Wilkinson DJ, Wimalaratne S, Laibe C, Hucka M, LeNovere N. Controlled vocabularies and semantics in systems biology. Molecular Systems Biology 2011, 7, 543.
• 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 DB, Kerrien S, Lawson J, Lister A, Lu J, Machne R, Mendes P, Pocock M, Rodriguez N, Villeger A, Wilkinson DJ, Wimalaratne S, Laibe C, Hucka M, Le Novere N. Controlled vocabularies and semantics in systems biology. Molecular Systems Biology 2011, 7, 543.
• Weile J, Pocock M, Cockell SJ, Lord P, Dewar JM, Holstein EM, Wilkinson D, Lydall D, Hallinan J, Wipat A. Customizable views on semantically integrated networks for systems biology. Bioinformatics 2011, 27(9), 1299-1306.
• Chang H, Lawless C, Addinall SG, Oexle S, Taschuk M, Wipat A, Wilkinson DJ, Lydall D. Genome-Wide Analysis to Identify Pathways Affecting Telomere-Initiated Senescence in Budding Yeast. G3: Genes, Genomes, Genetics 2011, 1(3), 197-208.
• Milner P, Gillespie CS, Wilkinson DJ. Moment closure approximations for stochastic kinetic models with rational rate laws. Mathematical Biosciences 2011, 231(2), 99-104.
• Wilkinson DJ. Parameter inference for stochastic kinetic models of bacterial gene regulation: A Bayesian Approach to Systems Biology. In: Ninth Valencia International Meeting on Bayesian Statistics. 2011, Benidorm, Spain: Oxford Science Publications.
• Addinall SG, Holstein EM, Lawless C, Yu M, Chapman K, Banks AP, Ngo HP, Maringele L, Taschuk M, Young A, Ciesiolka A, Lister AL, Wipat A, Wilkinson DJ, Lydall D. Quantitative Fitness Analysis Shows That NMD Proteins and Many Other Protein Complexes Suppress or Enhance Distinct Telomere Cap Defects. PLoS Genetics 2011, 7(4), e1001362.
• Wilkinson DJ. Stochastic dynamical systems. In: Stumpf, M; Balding, DJ; Girolami, M, ed. Handbook of Statistical Systems Biology. Wiley-Blackwell Publishing Ltd, 2011, pp.359-375.
• Wilkinson DJ. Stochastic Modelling for Systems Biology. Chapman & Hall/CRC Press, 2011.
• Cockell SJ, Weile J, Lord P, Wipat C, Andriychenko D, Pocock M, Wilkinson D, Young M, Wipat A. An integrated dataset for in silico drug discovery. Journal of Integrative Bioinformatics 2010, 7(3), 116.
• Gillespie CS, Lei G, Boys RJ, Greenall AJ, Wilkinson DJ. Analysing time course microarray data using Bioconductor: a case study using yeast2 Affymetrix arrays. BMC Research Notes 2010, 3(81).
• Henderson DA, Boys RJ, Wilkinson DJ. Bayesian Calibration of a Stochastic Kinetic Computer Model Using Multiple Data Sources. Biometrics 2010, 66(1), 249-256.
• Chen YH, Lawless C, Gillespie CS, Wu J, Boys RJ, Wilkinson DJ. CaliBayes and BASIS: integrated tools for the calibration, simulation and storage of biological simulation models. Briefings in Bioinformatics 2010, 11(3), 278-289.
• Lawless C, Wilkinson DJ, Young A, Addinall SG, Lydall DA. Colonyzer: automated quantification of micro-organism growth characteristics on solid agar. BMC Bioinformatics 2010, 11(1), 287.
• Golightly A, Wilkinson DJ. Discussion to "Particle Markov chain Monte Carlo Methods" by Andrieu, Doucet and Holenstein. Journal of the Royal Statistical Society Series B: Statistical Methodology 2010, 72(3), 322-323.
• Henderson DA, Boys RJ, Proctor CJ, Wilkinson DJ. Linking systems biology models to data: a stochastic kinetic model of p53 oscillations. In: A. O'Hagan and M. West, ed. The Oxford Handbook of Applied Bayesian Analysis. Oxford University Press, 2010, pp.155-187.
• Wilkinson DJ, Golightly A. Markov chain Monte Carlo algorithms for SDE parameter estimation. In: Lawrence, ND; Girolami, M; Rattray, M; Sanguinetti, G, ed. Learning and Inference in Computational Systems Biology. London: MIT Press, 2010, pp.253-276.
• Hucka M, Bergmann F, Hoops S, Keating S, Sahle S, Wilkinson DJ. Systems Biology Markup Language (SBML): Language specification for Level 3 Version 1 Core. Nature Publishing Group: Nature Precedings, 2010. Available at: http://dx.doi.org/10.1038/npre.2010.4123.1.
• Jow H, Bhattacharjee M, Boys RJ, Wilkinson DJ. The Integration of Genetic Maps Using Bayesian Inference. Journal of Computational Biology 2010, 17(6), 825-840.
• McAuley MT, Kenny RA, Kirkwood TBL, Wilkinson DJ, Jones JJL, Miller VM. A mathematical model of aging-related and cortisol induced hippocampal dysfunction. BMC Neuroscience 2009, 10(1), 26.
• Henderson DA, Boys RJ, Krishnan KJ, Lawless C, Wilkinson DJ. Bayesian Emulation and Calibration of a Stochastic Computer Model of Mitochondrial DNA Deletions in Substantia Nigra Neurons. Journal of the American Statistical Association 2009, 104(485), 76-87.
• Wilkinson DJ. Stochastic modelling for quantitative description of heterogeneous biological systems. Nature Reviews: Genetics 2009, 10(2), 122-133.
• Greenall A, Lei GY, Swan DC, James K, Wang LM, Peters H, Wipat A, Wilkinson DJ, Lydall D. A genome wide analysis of the response to uncapped telomeres in budding yeast reveals a novel role for the NAD(+) biosynthetic gene BNA2 in chromosome end protection. Genome Biology 2008, 9(10), R146.
• Addinall SG, Downey M, Yu M, Zubko MK, Dewar J, Leake A, Hallinan J, Shaw O, James K, Wilkinson DJ, Wipat A, Durocher D, Lydall DA. A Genome-wide Suppressor and Enhancer Analysis of cdc13-1 Reveals Varied Cellular Processes Influencing Telomere Capping in Saccharomyces cerevisiae. Genetics 2008, 180(4), 2251-2266.
• Boys RJ, Wilkinson DJ, Kirkwood TBL. Bayesian inference for a discretely observed stochastic kinetic model. Statistics and Computing 2008, 18(2), 125-135.
• Golightly A, Wilkinson D. Bayesian inference for nonlinear multivariate diffusion models observed with error. Computational Statistics & Data Analysis 2008, 52(3), 1674-1693.
• Hucka M, Hoops S, Keating S, Le Novere N, Sahle S, Wilkinson DJ. Systems Biology Markup Language (SBML) Level 2: Structures and facilities for model definitions. Nature Publishing Group, 2008. Available at: http://dx.doi.org/10.1038/npre.2008.2715.1.
• Evans TW, Gillespie CS, Wilkinson DJ. The SBML discrete stochastic models test suite. Bioinformatics 2008, 24(2), 285-286.
• Wilkinson DJ. Bayesian methods in bioinformatics and computational systems biology. Briefings in Bioinformatics 2007, 8(2), 109-116.
• Proctor CJ, Lydall D, Boys RJ, Gillespie CS, Shanley D, Wilkinson DJ, Kirkwood TBL. Modelling the checkpoint response to telomere uncapping in budding yeast. Journal of the Royal Society Interface 2007, 4(12), 73-90.
• Gillespie CS, Wilkinson DJ, Shanley DP, Proctor CJ, Boys RJ, Kirkwood TBL. BASIS: an internet resource for network modelling. Journal of Integrative Bioinformatics 2006, 3(2), [12].
• Golightly A, Wilkinson DJ. Bayesian sequential inference for nonlinear multivariate diffusions. Statistics and Computing 2006, 16(4), 323-338.
• Golightly A, Wilkinson DJ. Bayesian sequential inference for stochastic kinetic biochemical network models. Journal of Computational Biology 2006, 13(3), 838-851.
• Kirkwood TBL, Boys RJ, Gillespie CS, Proctor CJ, Shanley DP, Wilkinson DJ. Computer modeling in the study of aging. In: Masoro, E.J., Austad, S.N, ed. Handbook of The Biology of Aging. London, UK: Academic Press, 2006, pp.334-356.
• Wilkinson DJ. Stochastic Modelling for Systems Biology. London, UK: Chapman & Hall/CRC, 2006.
• Gillespie C, Wilkinson D, Proctor CJ, Shanley D, Boys RJ, Kirkwood TBL. Tools for the SBML community. Bioinformatics 2006, 22(5), 628-629.
• Golightly A, Wilkinson DJ. Bayesian inference for stochastic kinetic models using a diffusion approximation. Biometrics 2005, 61(3), 781-894.
• Kirkwood TBL, Boys RJ, Gillespie CS, Proctor CJ, Shanley DP, Wilkinson DJ. Computer Modeling in the Study of Aging. In: Austad, S.N., Masoro, E.J, ed. Handbook of the Biology of Aging. Amsterdam; Boston: Academic Press, 2005, pp.334-359.
• Proctor CJ, Soti C, Boys RJ, Gillespie CS, Shanley DP, Wilkinson DJ, Kirkwood TBL. Modelling the actions of chaperones and their role in ageing. Mechanisms of Ageing and Development 2005, 126(1), 119-131.
• Wilkinson DJ. Parallel Bayesian Computation. In: Kontoghiorghes, E.J, ed. Handbook of Parallel Computing and Statistics. Boca Raton, Florida; London, UK: Marcel Dekker/CRC Press, 2005, pp.481-512.
• Gillespie CS, Proctor CJ, Shanley DP, Wilkinson DJ, Boys RJ, Kirkwood TBL. Web-services for the biology community: the BASIS project. In: UK e-Science All Hands Meeting. 2005, Nottingham, UK.
• Gillespie C, Proctor CJ, Boys R, Shanley D, Wilkinson D, Kirkwood T. A mathematical model of ageing in yeast. Journal of Theoretical Biology 2004, 229(2), 189-196.
• Wilkinson DJ, Yeung SKH. A sparse matrix approach to Bayesian computation in large linear models. Computational Statistics and Data Analysis 2004, 44(3), 493-516.
• Wilkinson DJ. Discussion to Papaspiliopoulos, O., Roberts, G. O. and Skold, M., 'Non-centered parameterisation for hierarchical models and data augmentation'. In: Bernardo, J.M., Dawid, A.P., Berger, J.O., West, M., Heckerman, D., Bayarri, M.J., Smith, A.F.M, ed. Bayesian Statistics 7: Proceedings of the Seventh Valencia International Meeting. Oxford, UK: Oxford University Press, 2003, pp.323-324.
• Garside LM, Wilkinson DJ. Dynamic lattice-Markov spatio-temporal models for environmental data. In: Bernardo, J.M., Dawid, A.P., Berger, J.O., West, M., Heckerman, D., Bayarri, M.J., Smith, A.F.M, ed. Bayesian Statistics 7: Proceedings of the Seventh Valencia International Meeting. Oxford, UK: Oxford University Press, 2003, pp.535-542.
• Garside LM, Wilkinson DJ. Dynamic lattice-Markov spatio-temporal models for environmental data. In: Bayesian Statistics: 7th Valencia International Meeting on Bayesian Statistics. 2003, Valencia, Spain: Oxford University Press.
• Kirkwood TBL, Boys RJ, Gillespie CJ, Proctor CJ, Shanley DP, Wilkinson DJ. Towards an e-biology of ageing: Integrating theory and data. Nature Reviews Molecular Cell Biology 2003, 4(3), 243-249.
• Wilkinson DJ, Yeung SKH. Adaptive Metropolis-Hastings samplers for the Bayesian analysis of large linear Gaussian systems. Comp. Sci. and Stats 2002, 33, 128-138.
• Simpson A, Wilkinson DJ. Computationally Intensive Techniques for a Fully Bayesian, Decision Theoretic Approach to Financial Forecasting and Portfolio Selection. Computing Science and Statistics 2002, 33, 472-483.
• Wilkinson DJ, Yeung SKH. Conditional simulation from highly structured Gaussian systems, with application to blocking-MCMC for the Bayesian analysis of very large linear models. Statistics and Computing 2002, 12(3), 287-300.
• Goldstein M, Wilkinson DJ. Restricted prior inference for complex uncertainty structures. Annals of Mathematics and Artificial Intelligence 2001, 32(1-4), 315-334.
• Goldstein M, Wilkinson DJ. Bayes linear analysis for graphical models: The geometric approach to local computation and interpretive graphics. Statistics and Computing 2000, 10(4), 311-324.
• Boys RJ, Henderson DA, Wilkinson DJ. Detecting homogeneous segments in DNA sequences by using hidden Markov models. Journal of the Royal Statistical Society. Series C: Applied Statistics 2000, 49(2), 269-285.
• Glazebrook KD, Wilkinson DJ. Index-based policies for discounted multi-armed bandits on parallel machines. Annals of Applied Probability 2000, 10(3), 877-896.
• Simpson A, Wilkinson DJ. Multivariate DLMs for Forecasting Financial Time series, with Application to the Management of Portfolios. In: 14th Proceedings in Computational Statistics 2000 - COMPSTAT. 2000, Utrecht, The Netherlands: Physica-Verlag.
• Wilkinson DJ. Bayes linear variance adjustment for locally linear DLMs. Journal of Forecasting, 16, 329-342 1997.
• Wilkinson DJ, Goldstein M. Bayes linear adjustment for variance matrices. Bayesian Statistics 5, Oxford University Press. Edited by Bernardo JM, Berger JO, Dawid AP and Smith AFM. Proceedings of 5th Valencia International Meeting 1994, , 791-799 1996.