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COVID-19 Interview: Disease Modeling Phylogenetics
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In this interview, Dr Emma Hodcroft, a Molecular Epidemiologist from the University of Basel, explains how disease modeling works and the impact that limitations have had on our reactions to the COVID-19 outbreak.

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Testing Computer-designed Coronavirus Binding Proteins
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In this video we take you inside the lab at the UW Institute for Protein Design. The institute's scientists are hard at work testing their first round of computer-designed coronavirus binding proteins.

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Happiness: What Your Mother Didn't Tell You
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Our cultures give us a lot of advice about how to find happiness. Science, however, suggests that much of that advice just isn‘t right...

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The Surprising Science of Happiness
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Dan Gilbert, author of Stumbling on Happiness, challenges the idea that we'll be miserable if we don't get what we want. Our "psychological immune system" lets us feel truly happy even when things don't go as planned.

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The Medical Potential of AI and Metabolites
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Biotech entrepreneur and TED Fellow Leila Pirhaji shares her plan to build an AI-based network to characterize metabolite patterns, better understand how disease develops – and discover more effective treatments.

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Tackling the Challenges of Rational Compound Design
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Professor Charlotte Deane from the University of Oxford outlines the challenges of rational compound design and how they can be overcome using the DeLinker method.

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The MELLODDY Project
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In this video recorded at ELRIG Drug Discovery 2019 in Liverpool, Dr Hugo Ceuleans from Janssen Pharmaceutica NV, outlines the MELLODDY project and its aims.

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Applying Neural Networks to Drug Discovery
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Ola Engkvist, Associate Director at AstraZeneca outlines how neural networks are applied to drug discovery and the challenges associated with this approach.

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Machine Learning in Drug Discovery
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Dr Hugo Ceulemans from Janssen Pharmaceutica NV, explains how machine learning benefits drug discovery.

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Richard Feynman: Can Machines Think?
Video

The inimitable Richard Feynman answers question on the future of AI in 1985 that seem just as relevant today in this video.

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