A life-changing database

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Manage episode 298079691 series 1301268
By BBC and BBC Radio 4. Discovered by Player FM and our community — copyright is owned by the publisher, not Player FM, and audio is streamed directly from their servers. Hit the Subscribe button to track updates in Player FM, or paste the feed URL into other podcast apps.
Proteomes, the sequences of protein within the DNA of every living thing, are notoriously difficult to model. The usual chemical methods can take months, but a new computational model using the ability of artificial intelligence to learn the complex sequences is able to predict structures within a matter of hours. Thousands of protein structure predictions are now available on a public database for anyone to access. Understanding such proteins is seen as key to treating nearly all disease. It also hold the potential for improvements in fields as diverse as increasing crop resilience to climate change and biodegrading plastic on an industrial scale. Marnie Chesterton speaks with Demis Hassabis from Deepmind which developed the protein structure prediction system, and Janet Thornton from the European Bioinformatics Institute which holds the database. Genetic engineering, the promise and perils, is the subject of a new series with Matthew Cobb on Radio 4, called Genetic Dreams, Genetic Nightmares. He tells us about the dilemmas now faced by researchers who on the one hand have the potential to send terminator genes into malaria spreading mosquitoes – but who are also aware of the huge unknowns surrounding the release of such technology. Extreme weather events are becoming more frequent. Hayley Fowler has been researching the links between weather systems, climate change and the heat and floods we are currently experiencing. And could we reduce the incidence of SARS-Cov2 with a different vaccination strategy? Julia Gog has modelled different scenarios, as the number of infections continues to rise. A strategy to target those who are mixing the most, whether socially or through their employment, may be more effective than one targeting the most vulnerable.

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