Browse By Person: Burrage, Pamela
|Up a level|
Group by: Item Type | Date
Number of items: 31.
Burrage, Kevin, Burrage, Pamela, Leier, Andre, Marquez-Lago, Tatiana, & Nicolau Jr., Dan (2011) Stochastic simulation for spatial modelling of dynamic process in a living cell. In Koeppl, H., Densmore, D., Setti, G., & di Bernardo, M. (Eds.) Design and Analysis of Biomolecular Circuits: Engineering Approaches to Systems and Synthetic Biology. Springer Science+Business Media, pp. 43-62.
Barrio, Manuel, Burrage, Kevin, Burrage, Pamela, Leier, Andre, & Marquez-Lago, Tatiana (2010) Computational approaches for modelling intrinsic noise and delays in genetic regulatory networks. In Das, Sanjoy, Caragea, Doina, Welch, Stephen, & Hsu, William H. (Eds.) Handbook of Research on Computational Methodologies in Gene Regulatory Networks. IGI Global, Hershey PA, pp. 169-197.
Burrage, Kevin, Burrage, Pamela, Hamilton, N., & Tian, Tianhai (2006) Computer-intensive simulations for cellular models. In Zomaya, Albert Y. (Ed.) Parallel Computing for Bioinformatics and Computational Biology: Models, Enabling Technologies, and Case Studies. John Wiley & Sons, New Jersey, United States, pp. 79-119.
Drovandi, Christopher C., Cusimano, Nicole, Psaltis, Steven, Lawson, Brodie A. J., Pettitt, Anthony N., Burrage, Pamela, et al. (2016) Sampling methods for exploring between-subject variability in cardiac electrophysiology experiments. Journal of the Royal Society Interface, 13(121), Article no. 20160214.
Barrio, Manuel, Burrage, Kevin, & Burrage, Pamela (2015) Stochastic linear multistep methods for the simulation of chemical kinetics. The Journal of Chemical Physics, 142, 064101-1.
Psaltis, Steven, Farrell, Troy, Burrage, Kevin, Burrage, Pamela, McCabe, Peter, Moroney, Timothy, et al. (2015) Mathematical modelling of gas production and compositional shift of a CSG (coal seam gas) field: Local model development. Energy, 88, pp. 621-635.
Burrage, Kevin, Burrage, Pamela, Donovan, Diane, & Thompson, Bevan (2015) Populations of models, experimental designs and coverage of parameter space by Latin Hypercube and Orthogonal Sampling. Procedia Computer Science, 51, pp. 1762-1771.
Burrage, Pamela & Burrage, Kevin (2014) Structure-preserving Runge-Kutta methods for stochastic Hamiltonian equations with additive noise. Numerical Algorithms, 65(3), pp. 519-532.
Cusimano, Nicole, Burrage, Kevin, & Burrage, Pamela (2013) Fractional models for the migration of biological cells in complex spatial domains. The ANZIAM Journal, 54, C250-C270.
Burrage, Kevin & Burrage, Pamela (2012) Low rank Runge-Kutta methods, symplecticity and stochastic Hamiltonian problems with additive noise. Journal of Computational and Applied Mathematics, 236(16), pp. 3920-3930.
Deleyrolle, Loic, Ericksson, Geoffery, Morrison, Brian, Lopez, J. Alejandro, Burrage, Kevin, Burrage, Pamela, et al. (2011) Determination of somatic and cancer stem cell self-renewing symmetric division rate using sphere assays. PLoS One, 6(1), pp. 1-11.
Leier, Andre, Marquez-Lago, Tatiana, Burrage, Kevin, & Burrage, Pamela (2008) Modeling intrinsic noise and delays in chemical kinetics of coupled autoregulated oscillating cells. International Journal for Multiscale Computational Engineering, 6(1), pp. 77-86.
Tian, Tianhai, Burrage, Kevin, Burrage, Pamela, & Carletti, Margherita (2007) Stochastic delay differential equations for genetic regulatory networks. Journal of Computational and Applied Mathematics, 205(2), pp. 696-707.
Burrage, Kevin, Burrage, Pamela, Higham, Desmond, Kloeden, Peter, & Platen, Eckhard (2006) Comment on 'Numerical methods for stochastic differential equations'. Physical Review E (Statistical, Nonlinear, and Soft Matter Physics), 74(6), pp. 1-2.
Burrage, P., Herdiana, R, & Burrage, K. (2004) Adaptive stepsize based on control theory for stochastic differential equations. Journal of Computational and Applied Mathematics, 170(2), pp. 317-336.
Burrage, Kevin, Burrage, Pamela, & Tian, Tianhai (2004) Numerical methods for strong solutions of stochastic differential equations : an overview. Royal Society of London. Proceedings A. Mathematical, Physical and Engineering Sciences, 460(2041), pp. 373-402.
Carletti, Margherita, Burrage, Kevin, & Burrage, Pamela (2004) Numerical simulation of stochastic ordinary differential equations in biomathematical modelling. Mathematics and Computers in Simulation, 64(2), pp. 271-277.
Burrage, Kevin, Tian, Tianhai, & Burrage, Pamela (2004) A multi-scaled approach for simulating chemical reaction systems. Progress in Biophysics & Molecular Biology, 85(2-3), pp. 217-234.
Burrage, Pamela & Burrage, Kevin (2003) A variable stepsize implementation for stochastic differential equations. SIAM Journal on Scientific Computing (SISC), 24(3), pp. 848-864.
Burrage, Pamela, Burrage, Kevin, & Mitsui, Takemitsui (2000) Numerical solutions of stochastic differential equations – implementation and stability issues. Journal of Computational and Applied Mathematics, 125(1 Feb), pp. 171-182.
Burrage, Kevin, Burrage, Pamela, & Brugnano, L (2000) Adams-Type Methods for the Numerical Solution of Stochastic Ordinary Differential Equations. Bit (Lisse), 40(3), pp. 451-470.
Burrage, Kevin & Burrage, Pamela (2000) Order conditions of stochastic Runge-Kutta methods by B-series. SIAM Journal on Numerical Analysis, 38(5), pp. 1626-1646.
Burrage, Kevin & Burrage, Pamela (1999) High strong order methods for non-commutative stochastic ordinary differential equation systems and the Magnus formula. Physica D Nonlinear Phenomena, 133(1 Apr), pp. 34-48.
Burrage, Kevin & Burrage, Pamela (1998) General order conditions for stochastic Runge-Kutta methods for both commuting and non-commuting stochastic ordinary differential equation systems. Applied Numerical Mathematics, 28, pp. 161-177.
Burrage, Kevin, Burrage, Pamela, & Belward, John (1997) A bound on the maximum strong order of stochastic Runge-Kutta methods for stochastic ordinary differential equations. BIT Numerical Mathematics, 37(4), pp. 771-780.
Burrage, Kevin & Burrage, Pamela (1996) High strong order explicit Runge-Kutta methods for stochastic ordinary differential equations. Applied Numerical Mathematics, 22(1-3), pp. 81-101.
Moroney, Timothy, Czaplinski, Iwona, Burrage, Pamela, & Yang, Qianqian (2016) How (well) are we assisting our students in becoming 21st century STEM graduates? In The Australian Conference on Science and Mathematics Education, 28-30 September 2016, The University of Queensland, Brisbane, Qld.
Czaplinski, Iwona, Mallet, Dann G., Burrage, Pamela, & Psaltis, Steven (2015) Preparing engineering graduates for the knowledge economy through blended delivery of mathematics. In HERDSA 2015 Conference: Learning for Life and Work in a Complex World, 6-9 July 2015, Melbourne, Vic.
Burrage, Kevin, Burrage, Pamela M., Donovan, Diane M., McCourt, Thomas A., & Thompson, Harold B. (2014) Estimates on the coverage of parameter space using populations of models. In Mmopelwa, G., Ogwu, F., Anderson, G., Seboni, N., & Tanko, M. (Eds.) 5th IASTED African Conference on Environment and Water Resource Management, 1 - 3 September 2014, Gaborone, Botswana.
Burrage, Pamela, Burrage, Kevin, Kurowski, Krzysztof, Lorenc, M., Nicolau, Dan, Swain, Martin, et al. (2009) A parallel plasma membrane simulation. In Mazza, T (Ed.) Proceedings of the 2009 International Workshop on High Performance Computational Systems Biology, 14 - 16 October, 2009, Italy.
Burrage, Kevin, Burrage, Pamela, Leier, Andre, & Marquez-Lago, Tatiana (2008) Stochastic delay models for molecular clocks and somite formation. In Abbott, D, Aste, T, Batchelor, M, Dewar, R, Di Matteo, T, & Guttmann, T (Eds.) Proceedings: Complex Systems II ( SPIE 6802), 5- 7 December, 2007, Australia.