Cross-referencing of diverse experimental data in one unified system will enable us to combine datasets.

Cross-referencing of diverse experimental data in one unified system will enable us to combine datasets to make novel inferences, to construct gene/protein interaction maps, and to perform meta-analyses and apply data-mining algorithms. The interconnection of different data types and pathways will play a central role in understanding cancer biology and this in turn will lead to new discoveries and better treatments for breast cancer.

We aim to establish a systems biology model for repeated cycles of experimentation, analysis, modelling and prediction to formally and systematically investigate the signalling cascades and biological process that play a key role in transformation and metastasis during cancer, in collaboration with Breakthrough scientists.