to appear.International audienceKappa is a language geared towards the modelling of the complex systems of reactions that can occur between proteins inside cells. It is supported by sophisticated simulation and static analysis techniques which can be applied to the models to study their emergent behaviour. Part of this is the construction by the simulator of causal histories explaining the generation of patterns of connectivity that the user speci es to be of interest, for example the existence of links between speci ed kinds of protein. Standard notions of independence of rule applications fail to provide adequately concise causal histories, leading to the earlier formulation of strong and weak forms of trajectory compression for Kappa. In...
International audienceThanks to rule-based modelling languages, we can assemble large sets of mechan...
Abstract Data compression-based methods have been effectively applied to analysis of biological sequ...
To facilitate analysis and understanding of biological systems, large-scale data are often integrate...
In this paper, we introduce a novel way of constructing concise causal histories (pathways) to repre...
International audienceAbstractMotivation:We present an overview of the Kappa platform, an integrated...
International audienceDomain-specific rule-based languages to represent the systems of reactions tha...
AbstractRule-based modeling languages such as Kappa [Danos, V. and C. Laneve, Formal molecular biolo...
International audienceGraph compression is a data analysis technique that consists in the replacemen...
Data compression at its base is concerned with how information is organized in data. Understanding t...
Rule-based languages (like, for example, Kappa, BioNetGen, and BioCham) have emerged as successful m...
The adoption of the Kolmogorov-Sinai entropy is becoming a popular research tool among physicists, e...
Abstract—We present a theoretical framework for the compres-sion of automata, which are widely used ...
The technique of causal ordering is used to study causal and probabilistic aspects implied by model ...
To facilitate analysis and understanding of biological systems, large-scale data are often integrate...
International audiencePartial orders are a fundamental mathematical structure capable of rep- resent...
International audienceThanks to rule-based modelling languages, we can assemble large sets of mechan...
Abstract Data compression-based methods have been effectively applied to analysis of biological sequ...
To facilitate analysis and understanding of biological systems, large-scale data are often integrate...
In this paper, we introduce a novel way of constructing concise causal histories (pathways) to repre...
International audienceAbstractMotivation:We present an overview of the Kappa platform, an integrated...
International audienceDomain-specific rule-based languages to represent the systems of reactions tha...
AbstractRule-based modeling languages such as Kappa [Danos, V. and C. Laneve, Formal molecular biolo...
International audienceGraph compression is a data analysis technique that consists in the replacemen...
Data compression at its base is concerned with how information is organized in data. Understanding t...
Rule-based languages (like, for example, Kappa, BioNetGen, and BioCham) have emerged as successful m...
The adoption of the Kolmogorov-Sinai entropy is becoming a popular research tool among physicists, e...
Abstract—We present a theoretical framework for the compres-sion of automata, which are widely used ...
The technique of causal ordering is used to study causal and probabilistic aspects implied by model ...
To facilitate analysis and understanding of biological systems, large-scale data are often integrate...
International audiencePartial orders are a fundamental mathematical structure capable of rep- resent...
International audienceThanks to rule-based modelling languages, we can assemble large sets of mechan...
Abstract Data compression-based methods have been effectively applied to analysis of biological sequ...
To facilitate analysis and understanding of biological systems, large-scale data are often integrate...