AlphaFoldのTwitterイラスト検索結果。 31 件

#Diffusion models are effective for protein-ligand structure prediction with equivariant transformers. Our method NeuralPLexer accurately inpaints binding site while using #alphafold doesn't. @ZhuoranQ @wn8_nie @ArashVahdat @tfmiller3 https://t.co/Yz1Wi2hTUs

Packaged our algorithm to design binding peptides into a simple colab. Enter a protein sequence, indicate where you want the peptide to bind, and in a few minutes you'll have a peptide predicted to tightly bind via AlphaFold + Bayesian Optimization. 1/2

https://t.co/MvoXmnUHvK

AI methods can help scientists analyse #cryoEM data.

Find out how researchers from @UniHalle developed a new method to automatically interpret cryo-EM data using open source #AI software including #AlphaFold. #KastritisLab

https://t.co/gmuPFFkLhT

A new era for structural biology

"The AI revolution allows us to peer inside something that is not visible to us from the outset"

A. Ramanathan

#Science
#ArtificialIntelligence
#AlphaFold
⏯️Researchers turn to #deeplearning to decode protein structures
https://t.co/o8gmPsbXbq

Finally got round to drawing @DeepMind ‘s proteins folding predictor #AlphaFold as a man. #sciart

A computational biologist called Colby Ford used DeepMind's AlphaFold software to predict the shape of Omicron's spike in November, based on its genome sequence, long before the structure was determined physically. The prediction was extremely accurate

#AI for protein structure prediction is the @ScienceMagazine breakthrough and a @Nature top pick of the year 🎉

Thousands of protein structure predictions powered by @Deepmind's revolutionary AI are available in the #openaccess AlphaFoldDB

https://t.co/yV1ebwvnlV

Interesting... I suspect, by reducing the # of seqs in the MSA, this reduced the strength/certainty of restraints derived from coevolution, allowing AlphaFold to generate multiple hypotheses (conformations) with randomseed, model param, or msa pertubations https://t.co/3JPM8Ysgox

Recording of 'FEBS Junior Sections – AlphaFold Database webinar' by @PDBeurope team leaders - Gerard Kleywegt and Sameer Velankar is now available. Find it here https://t.co/2yCepK5YsD

#AlphaFold @FEBSnews

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

A paper on "AlphaFold-multimer", a version of AlphaFold that works on protein complexes, was released by @DeepMind.

Accurately predicted structures can lead to better understand the function of such protein complexes that underpin many biological processes!

#DeepLearning 1/4

Many single protein chains can be accurately predicted using AlphaFold, but multi-chain protein complexes remain challenging. Introducing AlphaFold-Multimer, a model that can predict the structure of multi-chain protein complexes with increased accuracy https://t.co/KMyN87wgDE 1/

Spot the difference: can you find all 49359 differences between these two #AlphaFold galleries?
It takes only seconds to model glycans with GlycoSHIELD https://t.co/U87xBZMGiF.
It is indeed #glycotime!

Glad to see this out! Minor contribution from my side. We tested to see how well AlphaFold can predict homo-oligomers and their oligomeric state. Here I'm plotting the min(pTMscore) across 5 models, splitting success (top row) and failures (bottom row). https://t.co/fhdMtC3f4L

A #MachineLearning method, AlphaFold2, "predicts protein structures with near-experimental accuracy."

I read again with pleasure about this breakthrough!

#Science
#AI
@emblebi

⏯️Protein-structure prediction revolutionized
1-https://t.co/4r1fmqRXRc
2-https://t.co/LKXDQpJOGf

/AlphaFold2の非専門家向け活用法 第4回前半「AlphaFoldが現状カバーできていない構造情報」｜上海老師｜note https://t.co/GNnuOGbV6n

Like everybody else in the world of science, I've been having fun exploring the database of AlphaFold structures. Here are (subunits of) a few proteins that show up often in my paintings. It (amazingly) gets all the bits and pieces right, but doesn't quite yet get the biology.

分子収斂が見つかったら勝手にAlphaFoldの構造をダウンロードして収斂座位をマップしたPyMOLセッションを作ってくれる機能を実装してみた。

AlphaFold2 is useful to design proteins.

遅ればせながら、ようやく時間ができたのでAlphaFold2で遊んでる。ATeamで使ってる枯草菌のFoF1-εの配列入れて見たところ、リガンドのATP無くてもC末端ヘリックスバンドルが折りたたまれた結果が出てきた。これは予想外。