No abstract

Ontologies are one of the key technologies for data integration and meta-databases, by connecting databases on a semantical level. Still, everything fails when one of the database schemas changes: specific parts of the ontology have to be reconstructed by hand. We propose an approach that allows the database schema and the ontology to change and evolve, without ever losing their connection to each other. We call that "coevolution". Coevolution cannot be completely automated, as data definition languages do not define the change of semantical concepts, but only technical schema changes. In this paper we present our mapping of database schemas to ontologies, describe how these ontologies can be enriched by semantical information and show our approach to transfer schema changes to the ontology.

This paper demonstrates the first steps of an automation process to develop models of signaltransduction pathways using discrete modelling languages. The whole approach consists of modelling, validation, animation, linking databases to simulation tools and also the qualitative analysis of the data. In this paper, we detail the modelling and simulation of the TLR4 pathway with a Coloured Petri Net simulation tool and the validation of this model against the semantic and mechanistic map from a biological database. These graphical maps contain all necessary reactions as a figure.We start with an UML class diagram to understand the static structure of molecules involved in the TLR4 pathway. Afterwards we model and simulate each "pathway step reaction" -one after another -to get the behaviour of the final system. The result is a model of the pathway which can be used in simulations, derived solely from basic chemical reactions in the database. Also, it is a lesson on critical points where human decision-making is needed, because not all the required information is stored directly in the database.

No abstract

This paper demonstrates the first steps of an automation process to develop models of signal transduction pathways using discrete modelling languages. The whole approach consists of modelling, validation, animation, linking databases to simulation tools and also the qualitative analysis of the data. In this paper, we detail the modelling and simulation of the TLR4 pathway with a coloured petri net simulation tool and the validation of this model against the semantic and mechanistic map from a biological database. These graphical maps contain all necessary reactions as a figure. We start with an UML class diagram to understand the static structure of molecules involved in the TLR4 pathway. Afterwards we model and simulate each "pathway step reaction" - one after another - to get the behaviour of the final system. The result is a model of the pathway which can be used in simulations, derived solely from basic chemical reactions in the database. Also, it is a lesson on critical points where human decision-making is needed, because not all the required information is stored directly in the database.