OXFORD UNIVERSITY COMPUTING LABORATORY

Kevin Burrage

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Professor Kevin Burrage

Professor in Computational Systems Biology

interests

  

Professional and Social Background

 Kevin Burrage was a Federation Fellow of the Australian Research Council (2003-2008). Until the end of

2007 he was also Professor of Computational Mathematics at the University of Queensland and Director of

the Advanced  Computational Modelling Centre.  He was also founding CEO of the Queensland Parallel

Supercomputing  foundation (now QCIF).


He is married to Pamela and they have two children: Matthew and Lauren, who are both at the University of

Queensland doing the Medical program.

 

Kevin joined Oxford University in early 2008 and is Professor of Computational Systems Biology at the

Computing Laboratory and the Oxford Centre for Integrative Systems Biology.  He is also professorial

research fellow at the Institute for Molecular Bioscience at the University of Queensland  He shares his time

between both institutions. Kevin is also a supernumerary fellow of New College at Oxford University.

 

Contact Details

  

Academic Interests

 I have general interests in

  • Computational Mathematics
  • Computational and Systems Biology
  • Stochastic modelling for the Life Sciences
  • Multiscale modelling and simulation

  

Links to research partners at the University of Queensland

  

Computational and Systems Biology

 Within Systems Biology, I work on

  • Monte Carlo modelling of chemical kinetics on the plasma membrane;
  • Genetic regulatory models incorporating noise and delays with applications to tHes 1 and Her 1/7;
  • Spatial cellular models and particularly granular transport of insulin in the pancreatic Beta cell;
  • Multiscale models incorporating noise at many different temporal and spatial scales;
  • Construction and analysis of interaction networks;
  • The role of small numbers of protein in immunological applications.

  

Selected Publications

 Here is some recent work that I have done in Systems Biology:  Reprints can be got from me via email.

  • S.MacNamara , K. Burrage  and R. B. Sidje (2008): Multiscale modeling of chemical kinetics via the
 master equation, to appear in SIAM J. Multiscale Modelling and Simulation Multiscale Modeling &
 Simulation (Vol.6, No.4).
  • K. Burrage, I. Lenane and G. Lythe (2008): Numerical methods for second order stochastic equations,

SIAM Journal of Scientific Computing,  29, 1, 245-264.

  • T. Marquez-Lago, K. Burrage (2007): Binomial tau-leap spatial stochastic simulation algorithm for

 applications in chemical kinetics, J. Chem. Phys, 127, 1.

  • J. Song, K. Burrage (2007): Predicting disulfide connectivity from protein sequence using multiple
 sequence feature vectors and secondary structure, Bioinformatics.
  • K. Burrage, J. Hancock, A. Leier, D. V. Nicolau, Jr. (2007): Modelling and simulation techniques for

Membrane Biology, Briefings in Bioinformatics, 8(4): 234-244, July 2007.

  • D. V. Nicolau Jr., J. F. Hancock, and K. Burrage (2007): Sources of Anomalous Diffusion on Cell

Membranes: A Monte Carlo Study, Biophysics Journal 92:1975-1987.

  • F. Liu, P. Zhuang, V. Anh, I. Turner and K. Burrage (2007): Stability and Convergence of an Implicit
Method for the Space-Time Fractional Advection-Diffusion Equation, Journal of Applied Mathematics and
Computation.
  • C-M. Chen, F. Liu and K. Burrage (2007): Finite difference method and a new Fourier analysis for the
Fractional Reaction-Diffusion Equation, Journal of Applied Mathematics and Computation.
  • D. Nicolau Jr, K. Burrage, R. G. Parton and J. Hancock (2006): Optimal microdomain characteristics

for nano-scale protein-protein interactions,  Molecular  and Cellular Biology, January 2006, Vol. 26, No. 1,

p. 313-323.

  • T. Tian and K.Burrage (2006): Stochastic models for regulatory networks of the genetic toggle switch,

PNAS, Vol. 103, No. 22, 8372-8377.

  • M. Barrio, K. Burrage, A. Leier and T. Tian (2006): Oscillatory Regulation of Hes1: Discrete

Stochastic Delay Modelling and Simulation, PLOS Computational Biology, September 2006, Volume 2,

Issue 9.

  • T. Tian, S. Xu, J. Gao  and Kevin Burrage (2006): Simulated maximum likelihood method for estimating
kinetic rates in gene expression, Bioinformatics, 2006; doi: 10.1093/bioinformatics/btl552.
  • K. Burrage, L. Hood and  M. A. Ragan (2006): Advanced computing for systems biology, Briefings in

Bioinformatics, 7: 390-398.

  • J. Song, K. Burrage, Z. Yuan and T. Huber (2006), Prediction of cis/trans isomerization in proteins

using psi-BLAST profiles and secondary structure information,  BMC Bioinformatics, March 9, 7:124.

  • J. Song, M. Wang and K. Burrage (2006): Exploring synonymous codon usage preferences of

disulfide-bonded and non-disulfide bonded cysteines in the E. coli Genome, J Theor Biol., Jan 18, 2006.

  • J. Song, and K. Burrage (2006): Predicting residue-wise contact orders in proteins by support vector

regression, BMC Bioinformatics, 7:425, doi:10.1186/1471-2105-7-425.

  • T. Tian, K.Burrage, P. M. Burrage and M. Carletti (2006): Stochastic Delay Differential Equations for

Genetic Regulatory Networks, Special Issue of J. Comp and Applied Maths,

doi:10.1016/j.cam.2006.02.063 .

  • K. Burrage, P.  Burrage, D. J. Higham, P. E. Kloeden, E.Platen (2006): Comments on Numerical

methods for stochastic differential equations: a correction and a warning, Physical Review E, 74, 068701.

  • T. Tian and K. Burrage (2004): Bistability and switching in the lysis lsogeny genetic regulatory network

of Bacteriophage lambda, Journal of Theoretical Biology, 227, 229-237.

  • M. Carletti, K. Burrage and P.M. Burrage (2004): Numerical simulation of stochastic ordinary

differential equations in biomathematical modeling, Mathematics and Computers in Simulation, 64, 271-277.

  • K. Burrage and T. Tian (2004): Poisson Runge-Kutta methods for Chemical Reaction Systems, in

Advances in Scientific Computing and Applications, Y.Lu W. Sun and T. Tang eds, Science Press,

Beijing/New York, 82-96.

  • K. Burrage, T. Tian and P. Burrage (2004): A multi-scaled approach for Chemical Reaction Systems

Modelling Cellular and Tissue Function in Prog. Biophys. Mol. Biol, Vol. 85, Issue 2-3, 217-234.

  • N. Hamilton, K. Burrage, M. Ragan and T. Huber (2004): Protein contact prediction using patterns of

correlation, Proteins: Structure, Function and Bioinformatics, 56, 679-684.

  • T. E. Turner, S. Schnell and K. Burrage (2004): Stochastic modelling of intracellular reactions,

Computational Biology and Chemistry, 28, 3, 165-178.

  • T. Tian and K. Burrage (2004): Binomial leap methods for simulating stochastic chemical kinetics,

J.Chem. Phys., 121, 10356-10364.

  • L.Croft, S. Schandoff, F. Clark, K. Burrage, P. Actander and J.S. Mattick (2000): ISIS the intron

information system reveals the frequency of alternative splicing in the human genome, Nature Genetics,

24(4), 340-1.




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Wolfson Building, Parks Road, Oxford OX1 3QD

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