Super fast!By using diffusion model with new designed network and the training with 256 A100 GPUs, AlphaFold3 predicts a 5000AA
protein complex within only 20 minutes! #AlphaFold3#diffusion#deepmind
@sokrypton RGN2(https://t.co/ULzcP0t1Ln) is the first to attempt to train a protein language model (AminoBert) for protein structure prediction. @peng_illinois What's the difference between AminoBert and the PLM in OmegaFold? Larger sequence DBs? or pretraining with structure information?
Our #CryoNet web server is updated! By introducing homology template modeling, CryoNet could build highly accurate full atomic #protein structure for #cryoEM map from high resolution at 3Å to low at 5~8Å.
Feel free to access CryoNet at: https://t.co/057EMcWVpl.
By CryoNet Team.
Adding a big enough number for "residue_index" feature is enough to model hetero-complex using AlphaFold (green&cyan: crystal structure / magenta: predicted model w/ residue_index modification).
#AlphaFold#alphafold2
Our PrismNet paper is online on Cell Research @cell_res! Congratulations to Lei, Wenze, and Yucheng! Thanks to Cliff and all the team members!
Code: https://t.co/kEsalILPAv
https://t.co/0AjDcYxV6u
Our #Cell paper is online! Proud to apply our PrismNet to predict proteins binding to #SARS_CoV_2!
PrismNet: https://t.co/kEsalILPAv
In vivo structural characterization of the #SARS_CoV_2 RNA genome identifies host proteins vulnerable to repurposed drugs https://t.co/5eSzEPgogk
One paper accepted to Science. Proud to apply our improved A2-Net to identify new proteins in the minor spliceosome, congratulations to Rui Bai and Ruixue Wan.
A2-Net: Building Structure from #CryoEM Density
https://t.co/6BUx3ugQM8
https://t.co/7iEIcBuaYT
Our work on the In vivo RNA structure of #SARS_CoV_2 is accepted by Cell today! Proud to apply our deep learning-based method--PrismNet to do the prediction. Congratulations to Lei Sun and Panpan and all other authors!
In vivo structural characterization of the whole SARS-CoV-2 RNA genome identifies host cell target proteins vulnerable to re-purposed drugs https://t.co/QUI95MJoL2
@biorxivpreprint@SARSCoV192@Sarscov2science
VRmol is online on @OUPBioinfo! Free to explore and perform #drug docking, genomic variation, structure editing, etc. on #3D molecular in #VR.🤟🤟🤟
Many thanks to Nan, Jingle, Xun, and David!!!
https://t.co/0wbMgf7tIA
https://t.co/9CyHVaAqZW
@RtoVR@UploadVR@htcvive@oculus