AlphaFold 2 is here: what’s behind the structure prediction miracle | Oxford Protein Informatics Group
Nature has now released that AlphaFold 2 paper, after eight long months of waiting. The main text reports more or less what we have known for nearly a year, with some added tidbits, although it is accompanied by a painstaking description of the architecture in the supplementary information. Perhaps more importantly, the authors have released the entirety of the code, including all details to run the pipeline, on Github. And there is no small print this time: you can run inference on any protein (I’ve checked!).
Nature has now released that AlphaFold 2 paper , after eight long months of waiting. The main text reports more or less what we have known for nearly a year, with some added tidbits, although it is accompanied by a painstaking description of the architecture in the supplementary information . Perhaps more importantly, the authors have released the entirety of the code, including all details to run the pipeline, on Github . And there is no small print this time: you can run inference on any protein (I’ve checked!). Have you not heard the news? Let me refresh your memory. In November 2020,
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- AlphaFold: a solution to a 50-year-old grand challenge in biologydeepmind.com
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- Great expectations – the potential impacts of AlphaFold DB | EMBLembl.org
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- How AI Revolutionized Protein Science, but Didn’t End It | Quanta Magazinequantamagazine.org
- AlphaFold: a solution to a 50-year-old grand challenge in biologydeepmind.google
- Unfolding AlphaFold | Towards Data Sciencetowardsdatascience.com
- Language models of protein sequences at the scale of evolution enable accurate structure predictionbiorxiv.org