TY - JOUR
T1 - Efficient finite-difference method for computing sensitivities of biochemical reactions
AU - Thanh, Vo Hong
AU - Zunino, Roberto
AU - Priami, Corrado
PY - 2018/10/1
Y1 - 2018/10/1
N2 - Sensitivity analysis of biochemical reactions aims at quantifying the dependence of the reaction dynamics on the reaction rates. The computation of the parameter sensitivities, however, poses many computational challenges when taking stochastic noise into account. This paper proposes a new finite-difference method for efficiently computing sensitivities of biochemical reactions. We employ propensity bounds of reactions to couple the simulation of the nominal and perturbed processes. The exactness of the simulation is preserved by applying the rejection-based mechanism. For each simulation step, the nominal and perturbed processes under our coupling strategy are synchronized and often jump together, increasing their positive correlation and hence reducing the variance of the estimator. The distinctive feature of our approach in comparison with existing coupling approaches is that it only needs to maintain a single data structure storing propensity bounds of reactions during the simulation of the nominal and perturbed processes. Our approach allows to compute sensitivities of many reaction rates simultaneously. Moreover, the data structure does not require to be updated frequently, hence improving the computational cost. This feature is especially useful when applied to large reaction networks. We benchmark our method on biological reaction models to prove its applicability and efficiency.
AB - Sensitivity analysis of biochemical reactions aims at quantifying the dependence of the reaction dynamics on the reaction rates. The computation of the parameter sensitivities, however, poses many computational challenges when taking stochastic noise into account. This paper proposes a new finite-difference method for efficiently computing sensitivities of biochemical reactions. We employ propensity bounds of reactions to couple the simulation of the nominal and perturbed processes. The exactness of the simulation is preserved by applying the rejection-based mechanism. For each simulation step, the nominal and perturbed processes under our coupling strategy are synchronized and often jump together, increasing their positive correlation and hence reducing the variance of the estimator. The distinctive feature of our approach in comparison with existing coupling approaches is that it only needs to maintain a single data structure storing propensity bounds of reactions during the simulation of the nominal and perturbed processes. Our approach allows to compute sensitivities of many reaction rates simultaneously. Moreover, the data structure does not require to be updated frequently, hence improving the computational cost. This feature is especially useful when applied to large reaction networks. We benchmark our method on biological reaction models to prove its applicability and efficiency.
KW - Finite-difference sensitivity analysis
KW - Rejection-based simulation
KW - Stochastic simulation
UR - http://www.scopus.com/inward/record.url?scp=85056507598&partnerID=8YFLogxK
U2 - 10.1098/rspa.2018.0303
DO - 10.1098/rspa.2018.0303
M3 - Article
VL - 474
SP - 1
EP - 20
JO - PROCEEDINGS OF THE ROYAL SOCIETY A: MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
JF - PROCEEDINGS OF THE ROYAL SOCIETY A: MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
SN - 1364-5021
IS - 2218
ER -