3 research outputs found
Efficient Finite Difference Method for Computing Sensitivities of Biochemical Reactions
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
reserved 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 computing 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.Comment: 29 pages with 6 figures, 2 table
Tree-Based Search for Stochastic Simulation Algorithm
In systems biology, the cell behavior is governed by a series of biochemical reactions. The stochastic simulation algorithm (SSA), which was introduced by Gillespie, is a standard method to properly realize the dynamic and stochastic nature of such systems. In general, SSA follows a two-step approach: finding the next reaction firing, and updating the system accordingly. In this paper we apply the Huffman tree, an optimal tree for data compression, so to improve the search for the next reaction firing