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• Protein structure prediction with AlphaFold

Protein structure prediction with AlphaFold

Abstract

Proteins are are large complex molecules, essential to practically all life’s processes. What a protein does largely depends on its unique 3D structure. Figuring out what shapes proteins fold into is known as the “protein folding problem”, and has stood as a grand challenge in biology for the past 50 years. The machine learning system AlphaFold has been recognised as a solution to this challenge by the organisers of the biennial Critical Assessment of protein Structure Prediction (CASP). In this talk Andrew will describe how AlphaFold works and how AlphaFold predictions are transforming molecular biology, as well as looking more broadly at how machine learning can impact science.

Bio

Andrew Senior is a research scientist in the science team at DeepMind in London where he led the AlphaFold team for the CASP13 protein structure prediction assessment. Previously he was tech lead for neural networks research in Google’s speech recognition acoustic modelling group. Before joining Google, he taught at Columbia University and worked at IBM Research on computer vision and biometrics. He received a PhD from Cambridge University for his thesis on recurrent neural networks and is a fellow of the Royal Academy of Engineering, IEEE and IET.