Last year we presented #AlphaFold v2 which predicts 3D structures of proteins down to atomic accuracy. Today we’re proud to share the methods in @Nature w/open source code. Excited to see the research this enables. More very soon!
https://t.co/6uiV51Xly5
https://t.co/CLo7EKubBT
@AlexLaterre@sarahookr Note that the the JAX graph does not allow for any conclusions to be drawn: JIT is not used and these are mostly tiny single ops completely dominated by Python/CPU overhead (different CPUs are used on the GPU/TPU machines). I've reported this issue to the authors.
We have updated the AlphaFold-Multimer paper and code with a new set of protein complex models trained with an improved loss. These models reduce the number of steric clashes and improve accuracy.
Code: https://t.co/LgqAo6GKzc
Paper: https://t.co/A3uTYVoTeq
The #AlphaFold source code has been updated and now accounts for multi-chain protein complexes - providing a significant improvement in accuracy for predicting protein interactions: https://t.co/4gyZ0loLrd
Generate predictions from your browser via: https://t.co/2Vd4itjElu
I’ve started reading this marvelous new book by Tristan Needham. It’s passionate and filled with geometrical insight, just like his earlier masterpiece VISUAL COMPLEX ANALYSIS. https://t.co/eDuAhYYJSi
Also, we've got a Colab for running AlphaFold using our validated genetic search up at: https://t.co/W5uq8X5Vt9 Have fun! Let me know if you have any issues. #alphafold
How can #AI help us speed up scientific discovery? We’ve teamed up with @DeepMind to make #AlphaFold protein structure predictions freely and openly available to the scientific community.
https://t.co/Lq2aUvjkQS
#FAIRdata#structuralbiology#opendata
Today with @emblebi, we're launching the #AlphaFold Protein Structure Database, which offers the most complete and accurate picture of the human proteome, doubling humanity’s accumulated knowledge of high-accuracy human protein structures - for free: https://t.co/vtBGmTkKhy 1/
Brief update on some exciting progress on #AlphaFold! We’ve been heads down working flat out on our full methods paper (currently under review) with accompanying open source code and on providing broad free access to AlphaFold for the scientific community. More very soon!
@CambridgeMLG is launching a blog, featuring a first two-part post about what keeps a Bayesian awake at night by Richard E. Turner and me. 🧵
https://t.co/Gs8MhzAp6L
If you follow me on Twitter, you probably know that I am pretty allergic to hype, especially around deep learning. So believe me when I say - this is a big f---ing deal.
https://t.co/GV7CDPQMlN
.@DeepMind's incredible AI-powered protein folding breakthrough will help us better understand one of life’s fundamental building blocks + enable researchers to tackle new and hard problems, from fighting diseases to environmental sustainability.
https://t.co/kpr8EAx34h
In a major scientific breakthrough, the latest version of #AlphaFold has been recognised as a solution to one of biology's grand challenges - the “protein folding problem”. It was validated today at #CASP14, the biennial Critical Assessment of protein Structure Prediction (1/3)
@sharky6000 Even the thought of calling a Python-implemented non-trivial RL environment ~millions of times whilst I'm fighting with some obstreperous learning algorithm causes me deep psychic pain 😜
I started a blog! The first post explains AlphaZero, but also touches on human cognition, why Python is bad for ML, game theory and model-based reinforcement learning. Hope you enjoy! https://t.co/T4RdWcMlRw