The response to different kinds of perturbations of a discrete model of gene regulatory network, which is a generalization of the random Boolean network model (RBN), is extensively discussed. The model includes memory effects and the analysis pays particular attention to the influence on the system stability of a parameter (i.e. the decay time of the gene products) that determines the duration of the memory effects. It is shown that this parameter deeply affects the overall behaviour of the system, with special regard to the dynamical regimes and the sensitivity. Furthermore, a noteworthy difference in the response of systems characterized by different memory lengths in presence of either temporary or permanent damages is highlighted, as we...
Random boolean networks (RBN) have been proposed more thanthirty years ago as models of genetic regu...
AbstractWe study a genetic regulatory network model developed to demonstrate that genetic robustness...
A Boolean model of gene and protein regulatory network with memory (GPBN) has recently attracted int...
The response to different kinds of perturbations of a discrete model of gene regulatory network, whi...
Classical random Boolean networks (RBN) are not well suited to describe experimental data from time-...
This thesis focuses on characterising and understanding robustness in Boolean models of genetic regu...
A major limitation of the classical random Boolean network model of gene regulatory networks is its ...
We describe here and discuss in detail the model of random Boolean networks (RBNs). Although these m...
Abstract Random Boolean models of genetic regulatory networks, when subject tosmall noise, may eithe...
We emphasize here the importance of generic models of biological systems that aim at describing the ...
Gene regulatory networks, like any evolving biological system, are subject to potentially damaging m...
Dynamics of gene interactions in cell and robustness of cell are still open problems. One of the mos...
Random boolean networks are a model of genetic regulatory networks that has proven able to describe ...
In this paper the stationary behavior of uncertain and possibly multistable gene regulation networks...
In this paper, we define a robustness measure for gene regulation networks, which allows to quantify...
Random boolean networks (RBN) have been proposed more thanthirty years ago as models of genetic regu...
AbstractWe study a genetic regulatory network model developed to demonstrate that genetic robustness...
A Boolean model of gene and protein regulatory network with memory (GPBN) has recently attracted int...
The response to different kinds of perturbations of a discrete model of gene regulatory network, whi...
Classical random Boolean networks (RBN) are not well suited to describe experimental data from time-...
This thesis focuses on characterising and understanding robustness in Boolean models of genetic regu...
A major limitation of the classical random Boolean network model of gene regulatory networks is its ...
We describe here and discuss in detail the model of random Boolean networks (RBNs). Although these m...
Abstract Random Boolean models of genetic regulatory networks, when subject tosmall noise, may eithe...
We emphasize here the importance of generic models of biological systems that aim at describing the ...
Gene regulatory networks, like any evolving biological system, are subject to potentially damaging m...
Dynamics of gene interactions in cell and robustness of cell are still open problems. One of the mos...
Random boolean networks are a model of genetic regulatory networks that has proven able to describe ...
In this paper the stationary behavior of uncertain and possibly multistable gene regulation networks...
In this paper, we define a robustness measure for gene regulation networks, which allows to quantify...
Random boolean networks (RBN) have been proposed more thanthirty years ago as models of genetic regu...
AbstractWe study a genetic regulatory network model developed to demonstrate that genetic robustness...
A Boolean model of gene and protein regulatory network with memory (GPBN) has recently attracted int...