We study the properties of the distance between attractors in RandomBoolean Networks, a prominent model of genetic regulatory networks. We definethree distance measures, upon which attractor distance matrices are constructed andtheir main statistic parameters are computed. The experimental analysis shows thatordered networks have a very clustered set of attractors, while chaotic networks’ attractorsare scattered; critical networks show, instead, a pattern with characteristicsof both ordered and chaotic networks.We study the properties of the distance between attractors in Random Boolean Networks, a prominent model of genetic regulatory networks. We define three distance measures, upon which attractor distance matrices are constructed and th...
The dynamical features of Random Boolean Networks (RBN) are examined, in the case where a scale-free...
Abstract — The multi-scale strategy in studying biological regulatory networks analysis is based on ...
Random Boolean networks are used as generic models for the dynamics of complex systems of interactin...
We study the properties of the distance between attractors in RandomBoolean Networks, a prominent mo...
We study the properties of the distance between attractors in Random Boolean Networks, a prominent m...
We study the properties of the distance between attractors in Random Boolean Networks, a prominent m...
none6noRandom boolean networks are a model of genetic regulatory networks that has proven able to de...
Despite their apparent simplicity, random Boolean networks display a rich variety of dynamical behav...
Boolean networks are a popular modeling framework in computational biology to capture the dynamics o...
Random Boolean Networks (RBNs for short) are strongly simplified models of gene regulatory networks ...
Many mathematical models for gene regulatory networks have been proposed. In this study, the authors...
<div><p>Attractors represent the long-term behaviors of Random Boolean Networks. We study how the am...
Random Boolean Networks (RBNs for short) are strongly simplified models of gene regulatory networks ...
Since real networks are noisy systems, in this work we investigate thedynamics of the random Boolean...
Attractors represent the long-term behaviors of Random Boolean Networks. We study how the amount of ...
The dynamical features of Random Boolean Networks (RBN) are examined, in the case where a scale-free...
Abstract — The multi-scale strategy in studying biological regulatory networks analysis is based on ...
Random Boolean networks are used as generic models for the dynamics of complex systems of interactin...
We study the properties of the distance between attractors in RandomBoolean Networks, a prominent mo...
We study the properties of the distance between attractors in Random Boolean Networks, a prominent m...
We study the properties of the distance between attractors in Random Boolean Networks, a prominent m...
none6noRandom boolean networks are a model of genetic regulatory networks that has proven able to de...
Despite their apparent simplicity, random Boolean networks display a rich variety of dynamical behav...
Boolean networks are a popular modeling framework in computational biology to capture the dynamics o...
Random Boolean Networks (RBNs for short) are strongly simplified models of gene regulatory networks ...
Many mathematical models for gene regulatory networks have been proposed. In this study, the authors...
<div><p>Attractors represent the long-term behaviors of Random Boolean Networks. We study how the am...
Random Boolean Networks (RBNs for short) are strongly simplified models of gene regulatory networks ...
Since real networks are noisy systems, in this work we investigate thedynamics of the random Boolean...
Attractors represent the long-term behaviors of Random Boolean Networks. We study how the amount of ...
The dynamical features of Random Boolean Networks (RBN) are examined, in the case where a scale-free...
Abstract — The multi-scale strategy in studying biological regulatory networks analysis is based on ...
Random Boolean networks are used as generic models for the dynamics of complex systems of interactin...