Machine Masters

Cancer is a complex disease with significant mutations in the biological process of the cells. Understanding these changes is crucial for precise diagnosis and personalised therapy. One promising approach involves studying different aspects of cancer cells using a variety of techniques, such as genetics, metabolism, and imaging. However, combined analysis of all this information is challenging. That's where machine learning and deep learning come in. These methods can help analyse all this complex data together, allowing us to better diagnose cancer and predict treatment response.

In this talk, I will discuss the opportunities and challenges of machine learning and computational approaches to integrate genetics, metabolic, and imaging data for cancer diagnosis and treatment response.

Mass Spectrometry is a powerful and sensitive analytical technique which can be used to identify, quantify and determine the molecular structure of compounds. This is achieved by measuring the mass-to-charge ratio (m/z) of molecules and using this information to accurately measure their exact molecular weight. This talk will explore how and what state-of-the art mass spectrometry can tell us about our bodies, the foods that we eat, the drugs/medicines that we may take and the world around us.

We are in the midst of the sixth mass extinction, a biodiversity crisis with devastating consequences for species worldwide. In order to preserve biodiversity, to ensure that species are able to cope with future environmental change, effective conservation strategies can be developed based on information provided by the genomics toolkit. In this talk will take a deep dive into the gene pools of several wildlife species and investigate how analysis of genetic data can provide us with an early warning to identify species in danger of extinction.