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kidger.site | ||
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www.blopig.com
[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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bair.berkeley.edu
[AI summary] This article explores the application of natural language processing (NLP) techniques, particularly self-supervised learning, to the study of proteins. It discusses the challenges of protein structure prediction, the potential of using large unlabeled protein sequence datasets, and introduces TAPE, a benchmarking framework for evaluating protein representations. The article highlights the importance of understanding protein structure and function, the limitations of traditional methods, and the promise of leveraging self-supervised learning to improve protein prediction tasks. It also touches on the practical implications of these advancements, such as protein engineering and drug discovery. |
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deepmind.google
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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deevybee.blogspot.com
There is growing awareness that Special Issues have become a menace in the world of academic publishing, because they provide a convenie... |
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