State diagrams (stategraphs) are suitable for describing the behavior of dynamic systems. However, when they are used to model large and complex systems, determining the states and transitions among them can be overwhelming, due to their flat, unstratified structure. In this article, we present the use of statecharts as a novel way of modeling complex gene networks. Statecharts extend conventional state diagrams with features such as nested hierarchy, recursion, and concurrency. These features are commonly utilized in engineering for designing complex systems and can enable us to model complex gene networks in an efficient and systematic way. We modeled five key gene network motifs, simple regulation, autoregulation, feed-forward loop, sing...
A gene regulatory network can be considered a dynamic cellular system which describes the behavior (...
In this study, some methodologies and a review of the recently obtained new results are presented fo...
Advancements in high-throughput technologies to measure increasingly complex biological phenomena at...
Background: Gene regulatory networks are widely used by biologists to describe the interactions amon...
Abstract. With the increasing availability of experimental data on gene-gene and protein-protein int...
Abstract Many different approaches have been developed to model and simulate gene regulatory network...
Mathematical models are useful for providing a framework for integrating data and gaining insights i...
Approaches to describe gene regulation networks can be categorized by increasing detail, as network ...
BackgroundGene regulatory networks with dynamics characterized by multiple stable states underlie ce...
The development process for biochemical network models follows the traditional pipeline: Biochemical...
International audienceLearning regulatory networks from time-series of gene expression is a challeng...
AbstractApproaches to modelling gene regulation networks can be categorized, according to increasing...
Approaches to modelling gene regulation networks can be categorized, according to increasing detail,...
How good is our understanding of the way cells treat information and make decisions? To what extend ...
Abstract: This article proposes a computational framework for modelling the logical behavior of a cl...
A gene regulatory network can be considered a dynamic cellular system which describes the behavior (...
In this study, some methodologies and a review of the recently obtained new results are presented fo...
Advancements in high-throughput technologies to measure increasingly complex biological phenomena at...
Background: Gene regulatory networks are widely used by biologists to describe the interactions amon...
Abstract. With the increasing availability of experimental data on gene-gene and protein-protein int...
Abstract Many different approaches have been developed to model and simulate gene regulatory network...
Mathematical models are useful for providing a framework for integrating data and gaining insights i...
Approaches to describe gene regulation networks can be categorized by increasing detail, as network ...
BackgroundGene regulatory networks with dynamics characterized by multiple stable states underlie ce...
The development process for biochemical network models follows the traditional pipeline: Biochemical...
International audienceLearning regulatory networks from time-series of gene expression is a challeng...
AbstractApproaches to modelling gene regulation networks can be categorized, according to increasing...
Approaches to modelling gene regulation networks can be categorized, according to increasing detail,...
How good is our understanding of the way cells treat information and make decisions? To what extend ...
Abstract: This article proposes a computational framework for modelling the logical behavior of a cl...
A gene regulatory network can be considered a dynamic cellular system which describes the behavior (...
In this study, some methodologies and a review of the recently obtained new results are presented fo...
Advancements in high-throughput technologies to measure increasingly complex biological phenomena at...