The use of stochastic models, in effect piecewise deterministic Markov processes (PDMP), has become increasingly popular especially for the modeling of chemical reactions and cell biophysics. Yet, exact simulation methods, for the simulation of these models in evolving environments, are limited by the need to find the next jumping time at each recursion of the algorithm. Here, we report on a new general method to find this jumping time for the True Jump Method. It is based on an expression in terms of ordinary differential equations for which efficient numerical methods are available. As such, our new result makes it possible to study numerically stochastic models for which analytical formulas are not available thereby providing a way to ap...
Biochemical reactions can happen on different time scales and also the abun-dance of species in thes...
Abstract. Well stirred chemical reaction systems which involve small numbers of mole-cules for some ...
In the past years it has become evident that stochastic effects in regulatory networks play an impor...
The use of stochastic models, in effect piecewise deterministic Markov processes (PDMP), has become ...
International audienceIn this paper, we are interested in the exact simulation of a class of Piecewi...
In cellular reaction systems, events often happen at different time and abundance scales. It is poss...
Jumps which are observed in many population models give rise to fluctuations in the dynamics of syst...
Abstract — This paper introduces a method for approximat-ing the dynamics of deterministic hybrid sy...
The stochastic Hodgkin-Huxley model is one of the best-known examples of piecewise deterministic Mar...
In cellular reaction systems, events often happen at different time and abundance scales. It is pos...
We introduce a novel algorithm (JEA) to simulate exactly from a class of one-dimensional jump-diffus...
In this paper we present a rather general hybrid system made of deterministic differential equations...
International audienceDensity dependent Markov chains (DDMCs) describe the interaction of groups of ...
Stochastic models are widely used in the simulation of biochemical systems at a cellular level. For ...
International audienceThis paper proposes an efficient approach to model stochastic hybrid systems a...
Biochemical reactions can happen on different time scales and also the abun-dance of species in thes...
Abstract. Well stirred chemical reaction systems which involve small numbers of mole-cules for some ...
In the past years it has become evident that stochastic effects in regulatory networks play an impor...
The use of stochastic models, in effect piecewise deterministic Markov processes (PDMP), has become ...
International audienceIn this paper, we are interested in the exact simulation of a class of Piecewi...
In cellular reaction systems, events often happen at different time and abundance scales. It is poss...
Jumps which are observed in many population models give rise to fluctuations in the dynamics of syst...
Abstract — This paper introduces a method for approximat-ing the dynamics of deterministic hybrid sy...
The stochastic Hodgkin-Huxley model is one of the best-known examples of piecewise deterministic Mar...
In cellular reaction systems, events often happen at different time and abundance scales. It is pos...
We introduce a novel algorithm (JEA) to simulate exactly from a class of one-dimensional jump-diffus...
In this paper we present a rather general hybrid system made of deterministic differential equations...
International audienceDensity dependent Markov chains (DDMCs) describe the interaction of groups of ...
Stochastic models are widely used in the simulation of biochemical systems at a cellular level. For ...
International audienceThis paper proposes an efficient approach to model stochastic hybrid systems a...
Biochemical reactions can happen on different time scales and also the abun-dance of species in thes...
Abstract. Well stirred chemical reaction systems which involve small numbers of mole-cules for some ...
In the past years it has become evident that stochastic effects in regulatory networks play an impor...