Aim
The project aims at starting to transform the scientific research pipeline by computer assisted design and selection of experiments. That means, unknown parameters in theoretical biological models are identified so experiments can be efficiently designed, optimised and selected in order to refine the model.
There are promising observation techniques (e.g. advances in confocal microscopy) that have the potential to yield spatiotemporal characteristics of signaling pathways. However, a more targeted approach of perturbation and observation would require better coupling of the theoretical models with experiments. Coupling experiments and theory (modellig, simulation) is a key in computational science – allowing to build models based on hypotheses to put them into a formal language and then to prove the hypotheses and advance models by experimental results. The result of this project would advance this linkage and foster scientific research by reducing the total number of experiments to a minimum.
Although optimal experiment design is used in Chemistry and Physics it is not well-established in Systems Biology. The steps in this project include:

• Deriving meaningful experiments out of SBML (Systems Biology markup language) models
• Optimal experiment design based on optimisation techniques
• Graphical User Interface which allows a Biologist (and not a Mathematician) to use this tool

Collaborators:

• German Cancer Research Centre (DKFZ), Heidelberg
• University of Heidelberg

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