​​(Re)Discovering Protein Structure and Function Through Language Modeling
Trained solely on unsupervised language modeling, the Transformer's attention mechanism recovers high-level structural (folding) and functional properties of proteins!
Why this is important: traditional protein modelling requires lots of computational power. This might be a key to more efficient structure modelling. Protein structure => function. Function => faster drug research and understanding of diseases mechanisms.
Blog: https://blog.einstein.ai/provis/
Paper: https://arxiv.org/abs/2006.15222
Code: https://github.com/salesforce/provis
#DL #NLU #proteinmodelling #bio #biolearning #insilico
Trained solely on unsupervised language modeling, the Transformer's attention mechanism recovers high-level structural (folding) and functional properties of proteins!
Why this is important: traditional protein modelling requires lots of computational power. This might be a key to more efficient structure modelling. Protein structure => function. Function => faster drug research and understanding of diseases mechanisms.
Blog: https://blog.einstein.ai/provis/
Paper: https://arxiv.org/abs/2006.15222
Code: https://github.com/salesforce/provis
#DL #NLU #proteinmodelling #bio #biolearning #insilico
​​DeepMind significally (+100%) improved protein folding modelling
Why is this important: protein folding = protein structure = protein function = how protein works in the living speciment and what it does.
What this means: better vaccines, better meds, more curable diseases and more calamities easen by the medications or better understanding.
Dataset: ~170000 available protein structures from PDB
Hardware: 128 TPUv3 cores (roughly equivalent to ~100-200 GPUs)
Link: https://deepmind.com/blog/article/alphafold-a-solution-to-a-50-year-old-grand-challenge-in-biology
#DL #NLU #proteinmodelling #bio #biolearning #insilico #deepmind #AlphaFold
Why is this important: protein folding = protein structure = protein function = how protein works in the living speciment and what it does.
What this means: better vaccines, better meds, more curable diseases and more calamities easen by the medications or better understanding.
Dataset: ~170000 available protein structures from PDB
Hardware: 128 TPUv3 cores (roughly equivalent to ~100-200 GPUs)
Link: https://deepmind.com/blog/article/alphafold-a-solution-to-a-50-year-old-grand-challenge-in-biology
#DL #NLU #proteinmodelling #bio #biolearning #insilico #deepmind #AlphaFold
