none4We present and discuss the results of an experimental analysis in the design of Boolean networks by means of genetic algorithms. A population of networks is evolved with the aim of nding a network such that the attractor it reaches is of required length l. In general, any target can be dened, provided that it is possible to model the task as an optimisation problem over the space of networks. We experiment with dierent initial conditions for the networks, namely in ordered, chaotic and critical regions, and also with dierent target length values. Results show that all kinds of initial networks can attain the desired goal, but with dierent success ratios: initial populations composed of critical or chaotic networks are more likely to r...
This paper presents an abstract, tunable model by which to explore aspects of artificial genetic reg...
We determine stability and attractor properties of random Boolean genetic network models with canaly...
Dynamical systems theory and complexity science provide powerful tools for analysing artificial agen...
We present and discuss the results of an experimental analysis in the design of Boolean networks by ...
A Boolean network (BN) is a mathematical model of genetic networks. We propose several algorithms fo...
Random Boolean networks are a widely acknowledged model for cell dynamics. Previous studies have sho...
In this work we address the issue of designing a Boolean network such that its attractors are maxima...
Finding control strategies of cells is a challenging and important problem in the post-genomic era. ...
This master's thesis introduces the Random Boolean Networks as a developmental model in the evolutio...
We study the problem of finding optimal control policies for Probabilistic Boolean Networks (PBNs)....
This paper considers a problem of finding control strategies for Boolean networks, where Boolean net...
Boolean networks (BNs) have been mainly considered as genetic regulatory network models and are the ...
<p>Boolean networks are important models of biochemical systems, located at the high end of the abst...
<p>Boolean networks are important models of biochemical systems, located at the high end of the abst...
Boolean networks are a popular modeling framework in computational biology to capture the dynamics o...
This paper presents an abstract, tunable model by which to explore aspects of artificial genetic reg...
We determine stability and attractor properties of random Boolean genetic network models with canaly...
Dynamical systems theory and complexity science provide powerful tools for analysing artificial agen...
We present and discuss the results of an experimental analysis in the design of Boolean networks by ...
A Boolean network (BN) is a mathematical model of genetic networks. We propose several algorithms fo...
Random Boolean networks are a widely acknowledged model for cell dynamics. Previous studies have sho...
In this work we address the issue of designing a Boolean network such that its attractors are maxima...
Finding control strategies of cells is a challenging and important problem in the post-genomic era. ...
This master's thesis introduces the Random Boolean Networks as a developmental model in the evolutio...
We study the problem of finding optimal control policies for Probabilistic Boolean Networks (PBNs)....
This paper considers a problem of finding control strategies for Boolean networks, where Boolean net...
Boolean networks (BNs) have been mainly considered as genetic regulatory network models and are the ...
<p>Boolean networks are important models of biochemical systems, located at the high end of the abst...
<p>Boolean networks are important models of biochemical systems, located at the high end of the abst...
Boolean networks are a popular modeling framework in computational biology to capture the dynamics o...
This paper presents an abstract, tunable model by which to explore aspects of artificial genetic reg...
We determine stability and attractor properties of random Boolean genetic network models with canaly...
Dynamical systems theory and complexity science provide powerful tools for analysing artificial agen...