About the seminar
We use machine learning and computational approaches to understand complex diseases, such as cancer. We search for gene networks and omics ‘signatures’ that enable us to understand how normal cells rewire their molecular circuits to become cancer cells, how they adapt to a heterogeneous microenvironment, and how they interact with other non-cancer cells. This helps us to understand cancer evolution and to predict therapeutic strategies that are most appropriate. I will introduce some studies where we used supervised learning approaches, such as penalized regression, to derive biomarkers across cancer types, and examples of the network and computational modelling approaches that we use to reconstruct the biology of the cancer ecosystem.
Join the seminar
This is an online seminar taking place via Zoom, please join us 11am - 12 noon UK time.
Get in contact
If you have any questions then please contact the organiser Matteo Barberis at firstname.lastname@example.org.