International audienceIn this course we will present some of the simulation methods most widely used to study the dynamics of biological networks. These networks may be metabolic networks, gene regulatory networks, and also the interactions between these two types of networks. We will discuss three types of approaches : the deterministic continuous simulations (ordinary dierential equation systems) discrete stochastic simulations (Gillespie method) and "entity-centered" systems (HSIM). We will see in which cases these approaches are applicable and the assumptions they imply. These simulation methods will be illustrated through two examples : the study of a model of circadian clock in the cyanobacterium and the study of oscillating systems u...
Mathematical modelling opens the door to a rich pathway to study the dynamic properties of biologica...
In the past years it has become evident that stochastic effects in regulatory networks play an impor...
This is the final version of the article. Available from Public Library of Science via the DOI in th...
International audienceIn this course we will present some of the simulation methods most widely used...
All processes of life are controlled by networks of interacting biochemical components. The purpose ...
Background: In recent years, several stochastic simulation algorithms have been developed to generat...
Modeling and simulation of biochemical reactions is of great interest in the context of system biolo...
AbstractThe biochemical reaction networks include elementary reactions differing by many orders of m...
In this paper we give an overview of some very recent work on the stochastic simulation of systems i...
Abstract Background Intrinsic fluctuations due to the...
Stochastic simulation has been widely used to model the dynamics of biochemical reaction networks. S...
As biochemical networks become more popular, the number of deterministic simulation tools grows rapi...
Discrete-state, continuous-time Markov models are becoming commonplace in the modelling of biochemic...
Stochasticity is a key characteristic of intracellular processes such as gene regulation and chemica...
It is a dream of Systems-Biology to efficiently simulate an entire cell on a computer. The potential...
Mathematical modelling opens the door to a rich pathway to study the dynamic properties of biologica...
In the past years it has become evident that stochastic effects in regulatory networks play an impor...
This is the final version of the article. Available from Public Library of Science via the DOI in th...
International audienceIn this course we will present some of the simulation methods most widely used...
All processes of life are controlled by networks of interacting biochemical components. The purpose ...
Background: In recent years, several stochastic simulation algorithms have been developed to generat...
Modeling and simulation of biochemical reactions is of great interest in the context of system biolo...
AbstractThe biochemical reaction networks include elementary reactions differing by many orders of m...
In this paper we give an overview of some very recent work on the stochastic simulation of systems i...
Abstract Background Intrinsic fluctuations due to the...
Stochastic simulation has been widely used to model the dynamics of biochemical reaction networks. S...
As biochemical networks become more popular, the number of deterministic simulation tools grows rapi...
Discrete-state, continuous-time Markov models are becoming commonplace in the modelling of biochemic...
Stochasticity is a key characteristic of intracellular processes such as gene regulation and chemica...
It is a dream of Systems-Biology to efficiently simulate an entire cell on a computer. The potential...
Mathematical modelling opens the door to a rich pathway to study the dynamic properties of biologica...
In the past years it has become evident that stochastic effects in regulatory networks play an impor...
This is the final version of the article. Available from Public Library of Science via the DOI in th...