Moment computation is essential to the analysis of stochastic kinetic models of biochemical reaction networks. It is often the case that the moment evolution, usually the first and...
The stochastic simulation of biological systems is an increasingly popular technique in bioinformatics. It often is an enlightening technique, which may however result in being com...
Marco Aldinucci, Mario Coppo, Ferruccio Damiani, M...
A biologically inspired cognitive model is presented for human decision making and applied to the simulation of the web user. The model is based on the Neurophysiology description ...
Transcriptional attenuation at E.coli’s tryptophan operon is a prime example of RNA-mediated gene regulation. In this paper, we present a discrete stochastic model for this pheno...
Background: Stochastic simulation has become a useful tool to both study natural biological systems and design new synthetic ones. By capturing the intrinsic molecular fluctuation...
Howard Salis, Vassilios Sotiropoulos, Yiannis N. K...
The paper summarizes some important results at the intersection of the fields of Bayesian statistics and stochastic simulation. Two statistical analysis issues for stochastic sim...
The purpose of this paper is to develop and demonstrate Simulation of Satellite Communications (SIMSATCOM), a high resolution, stochastic simulation of satellite communications fo...
We extend the basic theory of kriging, as applied to the design and analysis of deterministic computer experiments, to the stochastic simulation setting. Our goal is to provide fl...
Suppose one wishes to compare two closely related systems via stochastic simulation. Common random numbers (CRN) involves using the same streams of uniform random variates as inpu...
We present a translation of a generic stochastic process algebra model into a form suitable for stochastic simulation. By systematically generating rate equations from a process d...
Jeremy T. Bradley, Stephen T. Gilmore, Nigel Thoma...