Modelling cancer as a transcriptional landscape

Short description: More than half a century ago, the British developmental biologist and philosopher Conrad Hal Waddington introduced the landscape as a metaphor of how cells differentiate into different types of tissues. This is now recognised as “probably the most famous and most powerful metaphor in developmental biology”. Nonetheless it has remained unclear how such a surface might be computed from actual cell-state data, and if so whether it could be informative or predictive about real-life biology. Here I explore Hopfield neural networks with genome-wide gene expression data as a computational model of Waddington’s landscape. I discuss concepts of state, trajectory and attractors, and present visualisations of the Hopfield surface for subtypes of breast cancer.

Presenter: Dr Mark Ragan, Professor, Genomics of Disease and Development, Institute of Molecular Biology, University of Queensland