Living cells are constantly subjected to a plethora of environmental stimuli that require integration into an appropriate cellular response. This integration takes place through signal transduction events that form tightly interconnected networks. The understanding of these networks requires capturing their dynamics through computational support and models. ANIMO (analysis of Networks with Interactive Modeling) is a tool that enables the construction and exploration of executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analyzed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signaling networks. This enforces precision and uniformity in the definition of signaling pathways, contributing to the integration of isolated signaling events into complex network models. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic behavior of the network of interest. A user-friendly interface hides the use of Timed Automata from the user, while keeping the expressive power intact. Abstraction to single-parameter kinetics speeds up construction of models that remain faithful enough to provide meaningful insight. The resulting dynamic behavior of the network components is displayed graphically, allowing for an intuitive and interactive modeling experience.

When analysing complex interaction networks occurring in biological cells, a biologist needs computational support in order to understand the effects of signalling molecules (e.g. growth factors, drugs). ANIMO (Analysis of Networks with Interactive MOdelling) is a tool that allows the user to create and explore executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analysed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signalling networks. This enforces precision and uniformity in the definition of signalling pathways, contributing to the integration of signalling event models into complex, crosstalk-driven networks. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic cell behaviour. A user friendly interface makes the use of Timed Automata completely transparent to the biologist, while keeping the expressive power intact. This allows to define relatively simple, yet faithful models of complex biological interactions. The resulting timed behaviour is displayed graphically, allowing for an intuitive and interactive modelling experience.

Despite several efforts to make search engines more child-friendly, children still have trouble using systems that require keyboard input. We present TeddIR: a system using a tangible interface that allows children to search for books by placing tangible figurines and books they like/dislike in a green/red box, causing relevant results to be shown on a display. This way, issues with spelling and query formulation are avoided. A fully functional prototype was built and evaluated with children aged 6--8 at a primary school. The children understood TeddIR to a large extent and enjoyed the playful interaction.

Very big displays are now commonplace but interactions with them are limited, even poorly understood. Recently, understanding touch-based interactions have received a great deal of attention due to the popularity and low costs of these displays. The direct extension of such interactions, touch less interactions, has not. In this paper we evaluated gesture-based interactions with very big interactive screens to learn which gestures are suited and why. In other words, did ‘Minority Report’ get it right? We aim to discover to which extend these gesture interfaces are technology-driven and influenced by prototyped, commercial and fictive interfaces. A qualitative evaluation of a gesture interface for wall sized displays is presented in which subjects experienced the interface while completing several simple puzzle tasks. We found that simple gestures based on the act of pressing buttons was the most intuitive.

On-line information retrieval systems often offer their users some means to tune the query to match the level of granularity of the information request. Users can be offered a far greater range of possibilities, however, if documents are indexed with coordinated index concepts. Coordinated index concepts are compound index concepts that express a relation between concepts that function as simple subject descriptors, as in cures(headache, aspirin). We show the point by giving a functional specification of a query engine that can handle both simple and coordinated index concepts, Boolean combinations, and superconcept expansion. The Condorcet Query Engine, a prototype query engine that can be run over the World Wide Web (WWW), demonstrates the feasibility of these ideas. The combination of known and novel techniques ensures a smooth migration path from existing query engines to more advanced engines that handle coordinated index concepts.

Presents a particular way of building ontologies that proceeds in a bottom-up fashion. Concepts are defined in a way that mirrors the way their instances are composed out of smaller objects. The smaller objects themselves may also be modeled as being composed. Bottom-up ontologies are flexible through the use of implicit and, hence, parsimonious part-whole and subconcept-superconcept relations. The bottom-up method complements current practice, where, as a rule, ontologies are built top-down. The design method is illustrated by an example involving ontologies of pure substances at several levels of detail. It is not claimed that bottom-up construction is a generally valid recipe; indeed, such recipes are deemed uninformative or impossible. Rather, the approach is intended to enrich the ontology developer's toolkit.