Ramon Grima
Ramon Grima
Professor of Computational Biology, University of Edinburgh, UK
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Cited by
Cited by
Approximation and inference methods for stochastic biochemical kinetics—a tutorial review
D Schnoerr, G Sanguinetti, R Grima
Journal of Physics A: Mathematical and Theoretical 50 (9), 093001, 2017
Phenotypic switching in gene regulatory networks
P Thomas, N Popović, R Grima
Proceedings of the National Academy of Sciences 111 (19), 6994-6999, 2014
A systematic investigation of the rate laws valid in intracellular environments
R Grima, S Schnell
Biophysical chemistry 124 (1), 1-10, 2006
Linear mapping approximation of gene regulatory networks with stochastic dynamics
Z Cao, R Grima
Nature Communications 9 (1), 3305, 2018
An effective rate equation approach to reaction kinetics in small volumes: Theory and application to biochemical reactions in nonequilibrium steady-state conditions
R Grima
The Journal of chemical physics 133, 035101, 2010
How accurate are the nonlinear chemical Fokker-Planck and chemical Langevin equations?
R Grima, P Thomas, AV Straube
The Journal of chemical physics 135 (8), 084103, 2011
Multiscale Modeling in Biology New insights into cancer illustrate how mathematical tools are enhancing the understanding of life from the smallest scale to the grandest
S Schnell, R Grima, P Maini
Am Sci 95 (2), 134-142, 2007
Analytical distributions for detailed models of stochastic gene expression in eukaryotic cells
Z Cao, R Grima
Proceedings of the National Academy of Sciences 117 (9), 4682-4692, 2020
Steady-state fluctuations of a genetic feedback loop: An exact solution
R Grima, DR Schmidt, TJ Newman
Journal of Chemical Physics 137, 035104, 2012
A study of the accuracy of moment-closure approximations for stochastic chemical kinetics
R Grima
Journal of Chemical Physics 136, 154105, 2012
Many-body theory of chemotactic cell-cell interactions
TJ Newman, R Grima
Physical Review E 70 (5), 051916, 2004
The slow-scale linear noise approximation: an accurate, reduced stochastic description of biochemical networks under timescale separation conditions
P Thomas, AV Straube, R Grima
BMC systems biology 6 (1), 39, 2012
Comparison of different moment-closure approximations for stochastic chemical kinetics
D Schnoerr, G Sanguinetti, R Grima
The Journal of chemical physics 143, 185101, 2015
Spontaneous spatiotemporal waves of gene expression from biological clocks in the leaf
B Wenden, DLK Toner, SK Hodge, R Grima, AJ Millar
Proceedings of the National Academy of Sciences 109 (17), 6757-6762, 2012
Modelling reaction kinetics inside cells
R Grima, S Schnell
Essays in biochemistry 45, 41-56, 2008
Neural network aided approximation and parameter inference of non-Markovian models of gene expression
Q Jiang, X Fu, S Yan, R Li, W Du, Z Cao, F Qian, R Grima
Nature communications 12 (1), 1-12, 2021
Stochastic simulation of biomolecular networks in dynamic environments
M Voliotis, P Thomas, R Grima, CG Bowsher
PLoS computational biology 12 (6), e1004923, 2016
Rigorous elimination of fast stochastic variables from the linear noise approximation using projection operators
P Thomas, R Grima, AV Straube
Physical Review E 86, 041110, 2012
The complex chemical Langevin equation
D Schnoerr, G Sanguinetti, R Grima
The Journal of chemical physics 141, 024103, 2014
Arabidopsis cell expansion is controlled by a photothermal switch
H Johansson, HJ Jones, J Foreman, JR Hemsted, K Stewart, R Grima, ...
Nature communications 5, 4848, 2014
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