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kidger.site | ||
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deepmind.google
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| | | | | Proteins are essential to life, supporting practically all its functions. They are large complex molecules, made up of chains of amino acids, and what a protein does largely depends on its unique... | |
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www.blopig.com
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| | | | | [AI summary] The article discusses the release of AlphaFold 2, a groundbreaking deep learning system for protein structure prediction. It highlights how AlphaFold 2's success is due to advanced deep learning engineering and its ability to accurately predict protein structures from sequences. The article also reflects on the implications of this achievement for academia, suggesting that it may challenge the traditional role of academic research in basic science. Additionally, it explores the potential applications of AlphaFold 2 in drug discovery, protein design, and structural biology, emphasizing the transformative impact it could have on these fields. The author concludes by acknowledging the significance of AlphaFold 2's success and the need for the acade... | |
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www.nature.com
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| | | | | There has been considerable recent progress in designing new proteins using deep-learning methods19. Despite this progress, a general deep-learning framework for protein design that enables solution of a wide range of design challenges, including de novo binder design and design of higher-order symmetric architectures, has yet to be described. Diffusion models10,11 have had considerable success in image and language generative modelling but limited success when applied to protein modelling, probably due ... | |
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www.rdatagen.net
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| | | A key challenge - maybe the key challenge - of a stepped wedge clinical trial design is the threat of confounding by time. This is a cross-over design where the unit of randomization is a group or cluster, where each cluster begins in the control state and transitions to the intervention. It is the transition point that is randomized. Since outcomes could be changing over time regardless of the intervention, it is important to model the time trends when conducting the efficacy analysis. The question is how we choose to model time, and I am going to suggest that we might want to use a very flexible model, such as a cubic spline or a generalized additive model (GAM). | ||
