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Proteins are essential to life. Predicting their 3D structure is a major unsolved challenge in biology and could impact disease understanding and drug discovery. I’m excited to announce that we have won the CASP13 protein folding competition!
#AlphaFold https://deepmind.com/blog/alphafold/Prikaži ovu nit -
Although neural networks usually require massive datasets to do impressive things, for me the highlight of
#AlphaFold is the fact that it achieved state-of-the-art using only 30K training examples. Code: https://github.com/deepmind/deepmind-research/tree/master/alphafold_casp13 … Paper: https://www.nature.com/articles/s41586-019-1923-7 …pic.twitter.com/k533FyqD6q -
Using AI to help scientists solve big questions is at the core of DeepMind’s mission. Today we’re delighted to announce our first significant milestone: a successful application of machine learning to the protein folding problem. https://deepmind.com/blog/alphafold/
#AlphaFold (1/5)Prikaži ovu nit -
Online
@nature: Improved protein structure prediction using potentials from deep learning https://www.nature.com/articles/s41586-019-1923-7 …#AlphaFold@DeepMindAI@demishassabisPrikaži ovu nit -
Thanks to the CASP community for organising such a great benchmark, the gold standard for assessing protein folding techniques. Congratulations to the Science Team at
@DeepMindAI on this fantastic achievement! http://predictioncenter.org/casp13/zscores_final.cgi?formula=assessors … (#AlphaFold is listed as ‘A7D’)Prikaži ovu nit -
Disappointed that
#AlphaFold didn’t get references quite right- first was https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0028766 …Prikaži ovu nit -
DeepMind's
#AlphaFold algorithm won a prominent protein folding competition last month, outperforming many well-known pharmaceutical companies. Its an amazing time to be alive! I'll explain how it works in this episode https://youtu.be/cw6_OP5An8s -
@DeepMindAI enters protein folding: uses deep learning to predict 3D protein structure from sequence#AlphaFold. Solving A structure is the beginning. Proteins are dynamic & function in different conformations. Curious to see details when paper is out. https://deepmind.com/blog/alphafold/ -
#alphafold can predict amazing protein structures via#AI but we can refine to experimental accuracy via#MDSimulationhttps://www.pnas.org/content/early/2018/12/07/1811364115 … -
So what's next, after
#AlphaFold? We’re working to move beyond prediction to generate completely novel protein structures! Our lab's#NeurIPS2018 paper presents progress towards a deep learning-based complement/successor to#Rosetta for#proteindesign 1/n https://nips.cc/Conferences/2018/Schedule?showEvent=11721 …Prikaži ovu nit -
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Understanding how proteins fold is a fundamental scientific question that could one day help unlock treatments for a range of diseases. Excited that our
#AlphaFold work, which uses deep neural networks to predict protein structures, is published in@Nature today!https://twitter.com/DeepMind/status/1217510494984134657 … -
Majority won. Covered wide range of applications of Evolutionary Couplings and new approach to protein design. And
#AlphaFold team now also reading http://bit.ly/EVfold https://twitter.com/deboramarks/status/1217995629739364352 …pic.twitter.com/veiFkjy9yc
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@DeepMind has released a python package of#AlphaFold with@TensorFlow for protein fold prediction: contact prediction network, associated model weights and ~40Gb CASP13 dataset. https://github.com/deepmind/deepmind-research … Paper: https://rdcu.be/b0mtx -
Top
@DeepMind has released a package implementation of#AlphaFold which include the@TensorFlow contact prediction network, associated model weights and CASP13 dataset as published in Nature ( Authors access link : https://rdcu.be/b0mtx )
https://github.com/deepmind/deepmind-research/tree/master/alphafold_casp13 … -
After the coffee break, we will continue at 3.30pm with Andrew Senior (
#AlphaFold,@DeepMind), Katerina Vriza (@kvriza,@LC_Mater_Design) and last, but not least Katya Putintseva (@goneblotting,@labgeni_us). Looking forward!pic.twitter.com/kCI5IWPDjN
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#AlphaFold Deep learning system "could model#protein#structure from scratch – i.e., based only on genetic sequence – better than any previous modelling system with a similar accuracy to systems drawing on templates of previously solved protein"#AI#DLhttps://www.ucl.ac.uk/news/2020/jan/artificial-intelligence-used-predict-3d-structure-proteins … -
Congrats to the
@DeepMindAI team for publishing their exciting structure prediction work from CASP in@nature and PROTEINS. https://deepmind.com/blog/article/AlphaFold-Using-AI-for-scientific-discovery …#AlphaFold#MachineLearning -
Two of our recent projects published in
@Nature today! Our work on protein folding#AlphaFold and another exploring the link between distributional RL and dopamine in the brain. Huge congrats to everyone who contributed to make these scientific achievements possible!@DeepMindAI
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One describes AlphaFold, which uses deep neural networks to predict protein structures with high accuracy. AlphaFold made the most accurate predictions at the 2018 scientific community assessment CASP13. 1/4