Imperial College London


Faculty of Natural SciencesDepartment of Mathematics

Chair in Applied Mathematics



+44 (0)20 7594 1474p.degond Website CV




6M38Huxley BuildingSouth Kensington Campus






BibTex format

author = {Degond, P and Jin, S and Zhu, Y},
journal = {Methods and Applications of Analysis},
title = {An uncertainty quantification approach to the study of gene expression robustness},
url = {},

RIS format (EndNote, RefMan)

AB - We study a chemical kinetic system with uncertainty modeling a gene regulatorynetwork in biology. Specifically, we consider a system of two equations for the messengerRNA and micro RNA content of a cell. Our target is to provide a simple framework for noisebuffering in gene expression through micro RNA production. Here the uncertainty, modeledby random variables, enters the system through the initial data and the source term. Weobtain a sharp decay rate of the solution to the steady state, which reveals that the biologysystem is not sensitive to the initial perturbation around the steady state. The sharpregularity estimate leads to the stability of the generalized Polynomial Chaos stochasticGalerkin (gPC-SG) method. Based on the smoothness of the solution in the random spaceand the stability of the numerical method, we conclude the gPC-SG method has spectralaccuracy. Numerical experiments are conducted to verify the theoretical findings.
AU - Degond,P
AU - Jin,S
AU - Zhu,Y
SN - 1073-2772
TI - An uncertainty quantification approach to the study of gene expression robustness
T2 - Methods and Applications of Analysis
UR -
ER -