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#AlphaFold DB now has TED integrated! It's a special one for me — my first project where I took ownership from start to finish, bringing together different teams to integrate domain annotations into AFDB. Huge learning experience, and I’m excited to finally see it live!
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🚀#AlphaFold Database update
AlphaFold DB now integrates The Encyclopedia of Domains (TED) – a resource designed to systematically identify & classify structural domains within AlphaFold-predicted protein structures.
ebi.ac.uk/about/news/updates…
The real fight club no one speaks of...
Finally a more intuitive way to learn pLDDT/pAE? 😎
sokrypton.github.io/protein_…
(Character idea from @HannesStaerk & Alex Waldherr)
Check out my latest article: How do you eat an elephant? (My journey into ML) linkedin.com/pulse/how-do-yo… via @LinkedIn
Check out my latest article: Nine Years, Three Hours: How I Finally Built My Personal Website linkedin.com/pulse/nine-year… via @LinkedIn
You probably heard about the last major release at #AlphaFold Database two weeks ago. We hope this new post will cover any further questions about the details of the release. If you have any other questions, please do reply here or email us your queries – [email protected]
The latest #AlphaFold DB update is out!
We synchronised with @uniprot release 2025_03, predicted protein isoforms across all species, and provide MSAs used to generate each prediction.
Proud of the team at the @PDBeurope for the hard work that went into this!
We’re renewing our collaboration with @GoogleDeepMind!
We'll keep developing the AlphaFold Database to support protein science worldwide 🎉
To mark the moment we’ve synchronised the database with UniProtKB release 2025_03
ebi.ac.uk/about/news/technol…
#AlphaFold
And just like that, AlphaFold3 is now open source! Take a look at it yourselves, and have fun predicting some cool macromolecular complexes! nature.com/articles/d41586-0…
The Encyclopedia of Domains (TED) is out now! This here is some incredible work done to structurally identify domain annotations across all ~214 million #AlphaFold models at AlphaFold DB. This was a collaborative work between @CATH_Gene3D and the Jones group (@psipred) at @ucl.
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Excited to be at #FEBS2024 Congress in Milano! I presented our latest work on integrating #AlphaMissense into #AlphaFold DB. This allows users to interactively explore all missense variants in canonical human proteins. Let's have a chat to learn how it can help you! #FEBS2024
and we now have another iteration of AlphaFold! @GoogleDeepMind has finally released its latest AI model to predict the structure of proteins with their cognate ligands. Check out their webserver golgi.sandbox.google.com/abo… and make sure to read their paper nature.com/articles/s41586-0…
Announcing AlphaFold 3: our state-of-the-art AI model for predicting the structure and interactions of all life’s molecules. 🧬
Here’s how we built it with @IsomorphicLabs and what it means for biology. 🧵 dpmd.ai/3URDiNo
Wow, these are incredible…
It's #PortfolioDay ! I'm Michael, currently a PhD student in the biological sciences and budding scientific animator and designer. Interested in the complexity of life at microscopic scales.
Here's a few things I've made and my portfolio website is linked in the replies!
Maxim Tsenkov retweeted
Improving small molecule findability -- covalently linked components (CLCs) -- being presented (amongst other things) by our team member Preeti Choudhary (@preeti_cy). Read more here: ebi.ac.uk/pdbe/news/introduc…
Preeti Choudhary (@preeti_cy) from @PDBeurope talks about finding enriched data for drugs, #antibiotics, and other small #molecules in #PDBe. Watch what she has to say about it in this #ABLS24 poster video 🎥



















