Cancer is a very heterogeneous disease. Correspondingly, the molecular signaling in each cancer cell is wired differently. We have developed computational models which estimate the relative importance of signaling pathways in individual cancer cell lines. In order to further explore these estimates of signaling activities, it is necessary to visualize the signaling along with the model structure. Such visualization would be particularly useful for communicating about the computational models with experimentalists and clinicians.

In this project, the assignment is to design and develop a graphical tool for exploring the molecular signaling in cancer cells after drug treatment. The tool would allow the user to give different drugs to the virtual cancer cells, and show the effects that it has on the signaling. The signaling estimates themselves are provided by our computational models, but you would need to design and develop a good way of presenting this data.

An initial version of such a tool has been developed here; however, this tool is very limited and can only show one very specific model. A new visualization tool should be able to display different types of models (which are specified in SBML/CellDesigner) such that it can be reused for different types of cancer. It would also be very useful if the underlying measurement data can be shown in addition to the computational estimates.