Well stirred chemical reaction systems which involve small numbers of molecules for some species have a stochastic behavior and can be modeled by a continuous time, discrete state Markov process. An exact method for simulating the time evolution of the system is the Stochastic Simulation Algorithm, but this method is extremely slow for realistic biological systems. We propose an adaptive leapin...

BioScape is a concurrent language motivated by the biological landscapes found at the interface of biology and biomaterials [5]. It has been motivated by the need to model antibacterial surfaces, biofilm formation, and the effect of DNAse in treating and preventing biofilm infections. As its predecessor, SPiM [12], BioScape has a sequential semantics based on Gillespie’s algorithm [7], and its ...

Motivation: The Stochastic Simulation Algorithm (SSA) has largely diffused in the field of systems biology. This approach needs many realizations for establishing statistical results on the system under study. It is very computationnally demanding, and with the advent of large models this burden is increasing. Hence parallel implementation of SSA are needed to address these needs. At the very h...

Based on two intuitions – (i) event-driven systems and multi-agent systems are two computational paradigms that are amenable of a coherent interpretation within a unique conceptual framework; (ii) integrating the two simulation approaches can lead to a more expressive and powerful simulation framework – we propose a computational model integrating Discrete-Event Simulation (DES) and Multi-Agent...

In this work we present an extension of Bio-PEPA, a language recently defined for the modelling and analysis of biochemical systems, to handle events. Events are constructs that represent changes in the system due to some trigger conditions. The events considered here are simple, but nevertheless able to describe most of the discontinuous changes in models and experiments. Events are added to o...

Armed with increasingly fast supercomputers and greater knowledge of the molecular mechanisms of gene expression, it is now practical to numerically simulate complex networks of regulated biological reactions, or gene circuits. Using an exact stochastic simulation algorithm, we obtain an accurate time-evolution of the behavior of complex gene circuits, including the effects of fluctuations caus...

We use the recently proposed Nested Stochastic Simulation Algorithm (Nested SSA) to simulate the cell cycle model for budding yeast. The results show that Nested SSA is able to significantly reduce the computational cost while capturing the essential dynamical features of the system. AMS subject classifications: 65C05, 60G17, 74A25, 92C42

T paper is a follow-up work about the number soup model (1). It elaborates more mathematical details; describes more general properties and gives different interpretations of the model in a more heuristic way; and lists some intriguing questions deserved to be investigated more. The paper is organised in the following way. Section 1 shows examples of demographic structures in different n-metabo...

Mathematical modeling and simulation of dynamic biochemical systems are receiving considerable attention due to the increasing availability of experimental knowledge of complex intracellular functions. In addition to deterministic approaches, several stochastic approaches have been developed for simulating the time-series behavior of biochemical systems. The problem with stochastic approaches, ...