218 citations · 371 across the 5 of their papers we have counts for
5 papers
Bayesian inference for stochastic oscillatory systems using the phase-corrected Linear Noise Approximation
Ben Swallow, David A. Rand, Giorgos Minas
Likelihood-based inference in stochastic non-linear dynamical systems, such as those found in chemical reaction networks and biological clock systems, is inherently complex and has…
Geometry of Gene Regulatory Dynamics
David A. Rand, Archishman Raju, Meritxell Saez +2
Embryonic development leads to the reproducible and ordered appearance of complexity from egg to adult. The successive differentiation of different cell types, that elaborates this…
Quantifying intrinsic and extrinsic noise in gene transcription using the linear noise approximation: An application to single cell data
Bärbel Finkenstädt, Dan J. Woodcock, Michal Komorowski +4
A central challenge in computational modeling of dynamic biological systems is parameter inference from experimental time course measurements. However, one would not only like to i…
Sensitivity, robustness and identifiability in stochastic chemical kinetics models
Michal Komorowski, Maria J. Costa, David A. Rand +1
We present a novel and simple method to numerically calculate Fisher Information Matrices for stochastic chemical kinetics models. The linear noise approximation is used to derive…
Bayesian inference of biochemical kinetic parameters using the linear noise approximation
Michal Komorowski, Barbel Finkenstadt, Claire V. Harper +1
Fluorescent and luminescent gene reporters allow us to dynamically quantify changes in molecular species concentration over time on the single cell level. The mathematical modeling…