Darren J. Wilkinson

forecasting and (2009)

Andrew Simpson, Darren J Wilkinson

Computationally intensive techniques for a fully

Web-services for the biology community: the BASIS project (2009)

Colin S. Gillespie, Carole J. Proctor, Daryl P. Shanley, Darren J. Wilkinson, Richard J. Boys

BASIS is a UK e-Science pilot project which delivers a GRID enabled system that serves the biology of ageing research community by helping to integrate data and hypotheses from diverse biological...

GDAGsim: Sparse matrix algorithms for Bayesian computation (2009)

Darren J Wilkinson

GDAGsim is a software library which can be used to carry out conditional sampling of linear Gaussian directed acyclic graph models, and hence can be used for the implementation of efficient block...

A mathematical model of aging-related and cortisol induced hippocampal dysfunction (2009)

McAuley, Mark T, Kenny, Rose, Kirkwood, Thomas BL, Wilkinson, Darren J, Jones, Janette JL, Miller, Veronica M

Abstract Background The hippocampus is essential for declarative memory synthesis and is a core pathological substrate for Alzheimer's disease (AD), the most common aging-related dementing disease....

A genome wide analysis of the response to uncapped telomeres in budding yeast reveals a novel role for the NAD+biosynthetic gene BNA2in chromosome end protection (2008)

Greenall, Amanda, Lei, Guiyuan, Swan, Daniel C, James, Katherine, Wang, Liming, Peters, Heiko, ...

Abstract Background Telomeres prevent the ends of eukaryotic chromosomes from being recognized as damaged DNA and protect against cancer and ageing. When telomere structure is perturbed, a...

BIOINFORMATICS APPLICATIONS NOTE doi:10.1093/bioinformatics/btk042 Systems biology Tools for the SBML Community (2008)

Colin S. Gillespie, Darren J. Wilkinson, Carole J. Proctor, Daryl P. Shanley, Richard J. Boys

Motivation: SBML is quickly becoming the standard format to exchange biochemical models. The tools presented in this paper are loosely-coupled, and are intended to be incorporated into SBML aware...

Bayes linear covariance matrix adjustment (2008)

Wilkinson, Darren J

In this thesis, a Bayes linear methodology for the adjustment of covariance matrices is presented and discussed. A geometric framework for quantifying uncertainties about covariance matrices is set...

Markov chain Monte Carlo algorithms for SDE parameter estimation (2008)

Andrew Golightly, Darren J. Wilkinson

This chapter considers stochastic differential equations for Systems Biology models derived from the Chemical Langevin Equation (CLE). After outlining the derivation of such models, Bayesian...

The SBML discrete stochastic models test suite (2008)

Evans, Thomas W., Gillespie, Colin S., Wilkinson, Darren J.

Motivation: Stochastic simulation is a very important tool for mathematical modelling. However, it is difficult to check the correctness of a stochastic simulator, since any two realizations from a...

Efficient Bayesian Local Computation for Dynamic Forecasting of Competitive Markets (2007)

J. M. Bernardo, Darren J. Wilkinson

this paper a Bayes linear approach is adopted. Bayes linear methods are an alternative to conventional Bayesian statistics, which acknowledge the difficulties associated with the full modelling,...

Investigating intron structure using hidden Markov models (2007)

Richard J. Boys, Daniel A. Henderson, Darren J. Wilkinson, To The

this paper, we describe a technique which locates homogeneous segments within intron sequences which are compositionally different to the rest of the intron sequence. These segments may be...

Bayesian methods in bioinformatics and computational systems biology (2007)

Wilkinson, Darren J.

Bayesian methods are valuable, inter alia, whenever there is a need to extract information from data that are uncertain or subject to any kind of error or noise (including measurement error and...

BASIS: an internet resource for network modelling (2006)

Gillespie, Colin S., Wilkinson, Darren J., Shanley, Daryl P., Proctor, Carole J., Boys, Richard J., Kirkwood, Thomas B. L.

There is a growing realisation that complex biological processes cannot be understood through the application of ever more reductionist experimental programs alone. Recognising this, we have a...

Bayesian sequential inference for nonlinear multivariate diffusions (2006)

Andrew Golightly, Darren J. Wilkinson

In this paper, we adapt recently developed simulation-based sequential algorithms to the problem concerning the Bayesian analysis of discretely observed diffusion pro-cesses. The estimation framework...

Tools for the SBML Community (2006)

Gillespie, Colin S., Wilkinson, Darren J., Proctor, Carole J., Shanley, Daryl P., Boys, Richard J., Kirkwood, Thomas B. L.

Motivation: SBML is quickly becoming the standard format to exchange biochemical models. The tools presented in this paper are loosely-coupled, and are intended to be incorporated into SBML aware...

Bayesian Sequential Inference for Nonlinear Multivariate Diffusions (2004)

Andrew Golightly, Darren J. Wilkinson

In this paper, we adapt recently developed simulation-based sequential algorithms to the problem concerning the Bayesian analysis of discretely observed di#usion processes. The estimation framework...

Bayesian Inference for a Discretely Observed Stochastic Kinetic Model (2004)

Richard Boys Darren, Darren J. Wilkinson

this paper we explore how to make Bayesian inference for the kinetic rate constants of regulatory networks, using the stochastic kinetic Lotka-Volterra system as a model. This simple model describes...

Adaptive Metropolis-Hastings samplers for the Bayesian analysis of large linear Gaussian systems (2002)

Stephen Kh Yeung, Darren J Wilkinson

This paper considers the implementation of efficient Bayesian computation for large linear Gaussian models containing many latent variables. A common approach is to implement a simple MCMC procedure...

Conditional simulation from highly structured Gaussian systems, with application to blocking-MCMC for the Bayesian analysis of very large linear models (2000)

Darren J. Wilkinson, Stephen Kh Yeung

This paper examines strategies for simulating exactly from large Gaussian linear models conditional on some Gaussian observations. Local computation strategies based on the conditional independence...

BAYES-LIN: An object-oriented environment for Bayes linear local computation (1997)

Wilkinson, Darren J

BAYES-LIN is an extension of the LISP-STAT object-oriented statistical computing environment, which adds to LISP-STAT some object prototypes appropriate for carrying out local computation via...

BAYES-LIN: An object-oriented environment for Bayes linear local computation (1997)

Darren Wilkinson Copyright, Darren J. Wilkinson

BAYES-LIN is an extension of the LISP-STAT object-oriented statistical computing environment, which adds to LISP-STAT some object prototypes appropriate for carrying out Bayes linear analyses and...

BAYES-LIN: An object-oriented environment for Bayes linear local computation (1997)

Darren J. Wilkinson

BAYES-LIN is an extension of the LISP-STAT object-oriented statistical computing environment, which adds to LISP-STAT some object prototypes appropriate for carrying out local computation via...

Local computation of influence propagation through Bayes linear belief networks (1996)

Wilkinson, Darren J

In recent years there has been interest in the theory of local computation over probabilistic Bayesian graphical models. In this paper, local computation over Bayes linear belief networks is shown to...

Bayes linear variance adjustment for time series (1996)

Wilkinson, Darren J

This paper exhibits quadratic products of linear combinations of observables which identify the covariance structure underlying the univariate locally linear time series dynamic linear model. The...

Bayes linear covariance matrix adjustment (1995)

Wilkinson, Darren J

In this thesis, a Bayes linear methodology for the adjustment of covariance matrices is presented and discussed. A geometric framework for quantifying uncertainties about covariance matrices is set...

Bayes linear covariance matrix adjustment for multivariate dynamic linear models (1995)

Wilkinson, Darren J, Goldstein, Michael

A methodology is developed for the adjustment of the covariance matrices underlying a multivariate constant time series dynamic linear model. The covariance matrices are embedded in a...

Bayes linear adjustment for variance matrices (1995)

Wilkinson, Darren J, Goldstein, Michael

We examine the problem of covariance belief revision using a geometric approach. We exhibit an inner-product space where covariance matrices live naturally --- a space of random real symmetric...