Giulio Caravagna - Integrating machine learning and population genetics to better elucidate cancer evolutionary dynamics
|Starts:||14:00 18 Nov 2019|
|Ends:||14:50 18 Nov 2019|
|What is it:||Seminar|
|Organiser:||Department of Mathematics|
|Who is it for:||University staff, External researchers, Current University students|
(Room 3.44b Simon Building)
Join us for this seminar by Giulio Caravagna (Institute for Cancer Research) as part of the Mathematics in the Life Sciences Series.
Abstract: Cancers originate from the expansion of cells that acquire advantageous somatic alterations, in a Darwinian evolutionary framework. We can use molecular cancer data to measure the evolutionary process of clonal evolution, and unravel the key forces that shape tumour growth, and response to therapy. This allows us to reconcile heterogenous molecular profiles in light of evolution, and gives us a better position to implement cancer precision medicine. In this talk I will focus on two important problems of the field, both revolving around the challenge of measuring selection and evolutionary trajectories from cancer genome sequencing data. I will then present two possible solutions that integrate ideas and principles from population genetics and Machine Learning, in order to reconcile heterogeneity within and between patients.
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Role: Data Scientist
Organisation: Institute of Cancer Research, London
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