AlphaFold: improved protein structure prediction using potentials from deep learning
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- čas přidán 22. 08. 2019
- Andrew Senior is a research scientist at Google DeepMind and team lead on the AlphaFold project. This talk was recorded at the University of Washington on August 19, 2019.
00:01:25 - Protein structure prediction at DeepMind
00:05:05 - Protein folding problem (overview)
00:07:45 - CASP13 (overview)
00:12:28 - CASP13 results
00:14:55 - AlphaFold system (overview)
00:18:01 - Key aspects of AlphaFold
00:21:00 - Deep learning (overview)
00:25:35 - Why machine learning for protein structure modelling?
00:26:29 - Predicting inter-residue distances
00:31:20 - Data used by AlphaFold
00:33:06 - Deep Dilated Convolutional Residual network
00:34:56 - Data cropping
00:37:43 - Example of an AlphaFold prediction
00:39:50 - Distogram performance on contact metrics
00:41:55 - Secondary structure and Torsion angle prediction
00:43:31 - Using deep learning to construct a reference state
00:49:23 - Accuracy vs computational cost
00:50:00 - Conclusions
00:52:10 - What’s next
00:54:50 - Q&A