Gene-regulatory networks control the expression of genes and therefore the phenotype of cells. Modeling and simulation of such networks can provide deep insights into the functioning of cells. Boolean networks are a commonly used technique to model gene-regulatory networks. We introduce methods to construct Boolean networks from literature knowledge and to analyze their dynamics. In particular, methods to identify and analyze attractors are presented. In simulations on three biological networks, we analyze the robustness of attractors. These evaluations confirm the biological relevance of previously identified attractors
Gene Regulatory Networks represent the interactions among genes regulating the activation of specifi...
This article presents an abstract, tunable model containing two of the principal information-process...
Bioinformatics and network biology provide exciting and challenging research and application areas f...
Motivation: As the study of information processing in living cells moves from individual pathways to...
This thesis focuses on the topic of gene regulatory network inference and control based on the Boole...
Motivation: As the study of information processing in living cells moves from individual pathways to...
A Boolean model of gene and protein regulatory network with memory (GPBN) has recently attracted int...
Systems biology studies complex systems which involve a large number of interacting entities such th...
Gene regulatory networks represent the interactions among genes regulating the activation of specifi...
Abstract. Boolean threshold networks have recently been proposed as useful tools to model the dynami...
In Gene Regulatory Networks research there is a considerable lack of tech- niques and tools to under...
Gene regulatory networks represent the interactions among genes regulating the activation of specifi...
Motivation: Boolean network models are suitable to simulate gene regulatory networks (GRNs) in the a...
Regulatory networks play a central role in cellular behavior and decision making. Learning these reg...
Regulatory networks play a central role in cellular behavior and decision making. Learning these reg...
Gene Regulatory Networks represent the interactions among genes regulating the activation of specifi...
This article presents an abstract, tunable model containing two of the principal information-process...
Bioinformatics and network biology provide exciting and challenging research and application areas f...
Motivation: As the study of information processing in living cells moves from individual pathways to...
This thesis focuses on the topic of gene regulatory network inference and control based on the Boole...
Motivation: As the study of information processing in living cells moves from individual pathways to...
A Boolean model of gene and protein regulatory network with memory (GPBN) has recently attracted int...
Systems biology studies complex systems which involve a large number of interacting entities such th...
Gene regulatory networks represent the interactions among genes regulating the activation of specifi...
Abstract. Boolean threshold networks have recently been proposed as useful tools to model the dynami...
In Gene Regulatory Networks research there is a considerable lack of tech- niques and tools to under...
Gene regulatory networks represent the interactions among genes regulating the activation of specifi...
Motivation: Boolean network models are suitable to simulate gene regulatory networks (GRNs) in the a...
Regulatory networks play a central role in cellular behavior and decision making. Learning these reg...
Regulatory networks play a central role in cellular behavior and decision making. Learning these reg...
Gene Regulatory Networks represent the interactions among genes regulating the activation of specifi...
This article presents an abstract, tunable model containing two of the principal information-process...
Bioinformatics and network biology provide exciting and challenging research and application areas f...