AlphaFold is great, but do you know how to make the most of it ?
Come to visit me and participate in a AlphaFold training at @i2bcparissaclay.bsky.social
cnrsformation.cnrs.fr/catalogue/fo...
Come to visit me and participate in a AlphaFold training at @i2bcparissaclay.bsky.social
cnrsformation.cnrs.fr/catalogue/fo...
CNRS Formation Entreprises - Beginner's guide to AlphaFold : structural prediction of proteins and biological assemblies...
Découvrez nos modules de formation conçus par des experts du CNRS. Alliez théorie et pratique dans nos laboratoires pour maîtriser l'innovation scientifique.
cnrsformation.cnrs.fr
November 2, 2026 at 3:10 PM
AlphaFold is great, but do you know how to make the most of it ?
Come to visit me and participate in a AlphaFold training at @i2bcparissaclay.bsky.social
cnrsformation.cnrs.fr/catalogue/fo...
Come to visit me and participate in a AlphaFold training at @i2bcparissaclay.bsky.social
cnrsformation.cnrs.fr/catalogue/fo...
AlphaFold 3 predicts T cell recognition from genetic sequences alone better than chance—a task that previously performed little better than random guessing. doi.org/hcq7cx
AlphaFold 3 predicts complex immune interactions using protein sequences alone
Researchers at the Translational Genomics Research Institute (TGen), part of City of Hope, have developed a new approach using the artificial intelligence platform AlphaFold 3 to predict whether a T cell receptor will recognize a specific antigen based solely on its genetic sequence.
phys.org
November 4, 2026 at 7:20 PM
AlphaFold 3 predicts T cell recognition from genetic sequences alone better than chance—a task that previously performed little better than random guessing. doi.org/hcq7cx
People keep pointing to Alphafold, the protein-folding project as an example of AI's potential success in health & science, but Google disbanded it in July.
Google DeepMind disbands its Nobel-prize winning AlphaFold team - Engadget
DeepMind's award-winning AlphaFold team is no more.
www.engadget.com
October 29, 2026 at 2:10 PM
People keep pointing to Alphafold, the protein-folding project as an example of AI's potential success in health & science, but Google disbanded it in July.
I mean... Drug discovery models _are_ also generative AI. AlphaFold and the protein-design tools are literally image generators for molecules, using the same diffusion technique image generation models use.
November 3, 2026 at 12:23 AM
I mean... Drug discovery models _are_ also generative AI. AlphaFold and the protein-design tools are literally image generators for molecules, using the same diffusion technique image generation models use.
Just like the other useful applications (ex. AlphaFold), this is also NOT an LLM.
November 1, 2026 at 10:53 PM
Just like the other useful applications (ex. AlphaFold), this is also NOT an LLM.
Edit: Please find the correct link for the webinar on 19 November with Dan Rigden: www.ebi.ac.uk/training/eve...
AlphaFold for gene structure annotation -
AlphaFold for gene structure annotation -
www.ebi.ac.uk
November 4, 2026 at 10:06 AM
Edit: Please find the correct link for the webinar on 19 November with Dan Rigden: www.ebi.ac.uk/training/eve...
General prediction of T cell receptor antigen specificity from sequence using AlphaFold 3
www.science.org/doi/10.1126/...
www.science.org/doi/10.1126/...
General prediction of T cell receptor antigen specificity from sequence using AlphaFold 3
The major histocompatibility complex (MHC):peptide:T cell receptor (TCR) complex is the most diverse trimolecular interface known in nature and a key trigger for adaptive immunity. TCRs are now routin...
www.science.org
October 30, 2026 at 8:20 PM
General prediction of T cell receptor antigen specificity from sequence using AlphaFold 3
www.science.org/doi/10.1126/...
www.science.org/doi/10.1126/...
➡️ AlphaFold model visualisation: www.youtube.com/watch?v=6xDM...
➡️ pLDDT scores: www.youtube.com/watch?v=WVCM...
➡️ PAE plots: www.youtube.com/watch?v=jowU...
➡️ Putative protein domains: www.youtube.com/watch?v=pQC8...
➡️ pLDDT scores: www.youtube.com/watch?v=WVCM...
➡️ PAE plots: www.youtube.com/watch?v=jowU...
➡️ Putative protein domains: www.youtube.com/watch?v=pQC8...
Viewing AlphaFold models in Jalview
YouTube video by Jalview
www.youtube.com
November 5, 2026 at 3:58 PM
➡️ AlphaFold model visualisation: www.youtube.com/watch?v=6xDM...
➡️ pLDDT scores: www.youtube.com/watch?v=WVCM...
➡️ PAE plots: www.youtube.com/watch?v=jowU...
➡️ Putative protein domains: www.youtube.com/watch?v=pQC8...
➡️ pLDDT scores: www.youtube.com/watch?v=WVCM...
➡️ PAE plots: www.youtube.com/watch?v=jowU...
➡️ Putative protein domains: www.youtube.com/watch?v=pQC8...
Sebastian Mallaby joins @kball.llc to explore the story of Demis Hassabis and DeepMind, from its early breakthroughs to AlphaFold and the race to build AGI.
softwareengineeringdaily.com/podcasts/dem...
softwareengineeringdaily.com/podcasts/dem...
Demis Hassabis and the Race to Build AI with Sebastian Mallaby - Software Engineering Daily
Sebastian Mallaby joins Kevin Ball to explore the story of Demis Hassabis and DeepMind, from its early breakthroughs to AlphaFold and the race to build AGI.
softwareengineeringdaily.com
November 3, 2026 at 10:30 AM
Sebastian Mallaby joins @kball.llc to explore the story of Demis Hassabis and DeepMind, from its early breakthroughs to AlphaFold and the race to build AGI.
softwareengineeringdaily.com/podcasts/dem...
softwareengineeringdaily.com/podcasts/dem...
Took ages to dig this out!
Google are folding alphafold,
Google are folding alphafold,
November 3, 2026 at 5:52 PM
Took ages to dig this out!
Google are folding alphafold,
Google are folding alphafold,
A tale of two states: AlphaFold binding pockets on the apo-holo continuum www.biorxiv.org/content/10.64898/2026.10.26.762003v1 #cryoem
October 31, 2026 at 10:14 AM
A tale of two states: AlphaFold binding pockets on the apo-holo continuum www.biorxiv.org/content/10.64898/2026.10.26.762003v1 #cryoem
CRV Science Wiki
🧬 AlphaFold — AlphaFold is a deep-learning neural network architecture that predicts atomic-resolution three-dimensional protein structures from primary amino-acid sequences by coupling multiple sequence alignment co-evolutionary attention w…
https://crvscience.com/wiki/alphafold
🧬 AlphaFold — AlphaFold is a deep-learning neural network architecture that predicts atomic-resolution three-dimensional protein structures from primary amino-acid sequences by coupling multiple sequence alignment co-evolutionary attention w…
https://crvscience.com/wiki/alphafold
CRV Science Wiki
🧬 AlphaFold — AlphaFold is a deep-learning neural network architecture that predicts atomic-resolution three-dimensional protein structures from primary amino-acid sequences by coupling multiple sequence alignment co-evolutionary attention with SE(3)-equivariant coordinate refine…
crvscience.com
November 2, 2026 at 8:04 AM
CRV Science Wiki
🧬 AlphaFold — AlphaFold is a deep-learning neural network architecture that predicts atomic-resolution three-dimensional protein structures from primary amino-acid sequences by coupling multiple sequence alignment co-evolutionary attention w…
https://crvscience.com/wiki/alphafold
🧬 AlphaFold — AlphaFold is a deep-learning neural network architecture that predicts atomic-resolution three-dimensional protein structures from primary amino-acid sequences by coupling multiple sequence alignment co-evolutionary attention w…
https://crvscience.com/wiki/alphafold
17/18 We have moved beyond skepticism toward synthetic data, such as the +200M structures predicted by AlphaFold, to directly incorporating these predictions as a major foundation for our algorithms.
In 2022, we remained cautious but optimistic about ...
In 2022, we remained cautious but optimistic about ...
November 4, 2026 at 10:02 PM
17/18 We have moved beyond skepticism toward synthetic data, such as the +200M structures predicted by AlphaFold, to directly incorporating these predictions as a major foundation for our algorithms.
In 2022, we remained cautious but optimistic about ...
In 2022, we remained cautious but optimistic about ...
AlphaFold 3 Prediction Accuracy and Reliability across RNA Structures and Protein-RNA Interfaces https://www.biorxiv.org/content/10.64898/2026.11.02.763690v1
November 4, 2026 at 6:46 PM
AlphaFold 3 Prediction Accuracy and Reliability across RNA Structures and Protein-RNA Interfaces https://www.biorxiv.org/content/10.64898/2026.11.02.763690v1
AlphaFold 3 Prediction Accuracy and Reliability across RNA Structures and Protein-RNA Interfaces https://www.biorxiv.org/content/10.64898/2026.11.02.763690v1
November 4, 2026 at 6:46 PM
AlphaFold 3 Prediction Accuracy and Reliability across RNA Structures and Protein-RNA Interfaces https://www.biorxiv.org/content/10.64898/2026.11.02.763690v1
Endogenous ADARs can be harnessed with engineered arRNAs for safe RNA editing. LEAPER 3.0 utilizes AlphaFold 3 for improved design, boosting efficiency and precision in RNA edits. PMID:42269608, Cell 2026, @Cell https://www.cell.com/cell/fulltext/S0092-8674(26)00514-3 #Medsky #Pharmsky #RNA #ASHG 🧪
https://www.cell.com/cell/fulltext/S0092-8674(26)00514-3
No description available
www.cell.com
November 4, 2026 at 5:00 PM
Google juuri kesällä hajotti Alphafold-tutkimustiiminsä, koska halusivat keskittyä proteiinitutkimuksen sijaan kielimalleihin eli slopin tuottamiseen.
Lääkkeiden kehittäminen on vain yksi boostereiden keppihevosista, jolla ei ole mitään tekemistä "tekoälynä" myytävän paskan kanssa
Lääkkeiden kehittäminen on vain yksi boostereiden keppihevosista, jolla ei ole mitään tekemistä "tekoälynä" myytävän paskan kanssa
October 31, 2026 at 8:58 AM
Google juuri kesällä hajotti Alphafold-tutkimustiiminsä, koska halusivat keskittyä proteiinitutkimuksen sijaan kielimalleihin eli slopin tuottamiseen.
Lääkkeiden kehittäminen on vain yksi boostereiden keppihevosista, jolla ei ole mitään tekemistä "tekoälynä" myytävän paskan kanssa
Lääkkeiden kehittäminen on vain yksi boostereiden keppihevosista, jolla ei ole mitään tekemistä "tekoälynä" myytävän paskan kanssa
Chapter 16 explains how @OpenAI passed @Google Deep Mind which was preoccupied with AlphaFold & because @Google didn't recognize the threat of @openai
November 3, 2026 at 3:41 PM
Chapter 16 explains how @OpenAI passed @Google Deep Mind which was preoccupied with AlphaFold & because @Google didn't recognize the threat of @openai
I will forever be unimpressed by AlphaFold until we see confirmation in wet lab studies.
Oh wait, our NIH is drastically underfunded.
Computer scientists predictably fail to internalize that we lack a significant understanding of components in a COMPLEX system.
#triplethenih
Oh wait, our NIH is drastically underfunded.
Computer scientists predictably fail to internalize that we lack a significant understanding of components in a COMPLEX system.
#triplethenih
Researchers at TGen used AlphaFold 3 to predict which antigens T cells recognize from their genetic sequences.
Across 9,000+ T-cell receptors and 1,000+ epitopes, their model achieved 81–92% AUC on independent tests.
A major advance in decoding immune responses.
www.science.org/doi/10.1126/...
Across 9,000+ T-cell receptors and 1,000+ epitopes, their model achieved 81–92% AUC on independent tests.
A major advance in decoding immune responses.
www.science.org/doi/10.1126/...
General prediction of T cell receptor antigen specificity from sequence using AlphaFold 3
The major histocompatibility complex (MHC):peptide:T cell receptor (TCR) complex is the most diverse trimolecular interface known in nature and a key trigger for adaptive immunity. TCRs are now routin...
www.science.org
October 30, 2026 at 10:23 PM
I will forever be unimpressed by AlphaFold until we see confirmation in wet lab studies.
Oh wait, our NIH is drastically underfunded.
Computer scientists predictably fail to internalize that we lack a significant understanding of components in a COMPLEX system.
#triplethenih
Oh wait, our NIH is drastically underfunded.
Computer scientists predictably fail to internalize that we lack a significant understanding of components in a COMPLEX system.
#triplethenih
A tale of two states: AlphaFold binding pockets on the apo-holo continuum https://www.biorxiv.org/content/10.64898/2026.10.26.762003v1
October 31, 2026 at 2:48 AM
A tale of two states: AlphaFold binding pockets on the apo-holo continuum https://www.biorxiv.org/content/10.64898/2026.10.26.762003v1
3/ Protein Folding (AlphaFold)
DeepMind predicted 3D structures for 200M+ proteins, catalysing targeted therapies for cancer, Parkinson's & malaria. Led to the 2024 Nobel Prize.
Source: doi.org/10.1038/s415...
DeepMind predicted 3D structures for 200M+ proteins, catalysing targeted therapies for cancer, Parkinson's & malaria. Led to the 2024 Nobel Prize.
Source: doi.org/10.1038/s415...
Highly accurate protein structure prediction with AlphaFold - Nature
AlphaFold predicts protein structures with an accuracy competitive with experimental structures in the majority of cases using a novel deep learning architecture.
doi.org
November 1, 2026 at 11:04 AM
3/ Protein Folding (AlphaFold)
DeepMind predicted 3D structures for 200M+ proteins, catalysing targeted therapies for cancer, Parkinson's & malaria. Led to the 2024 Nobel Prize.
Source: doi.org/10.1038/s415...
DeepMind predicted 3D structures for 200M+ proteins, catalysing targeted therapies for cancer, Parkinson's & malaria. Led to the 2024 Nobel Prize.
Source: doi.org/10.1038/s415...
Researchers at TGen used AlphaFold 3 to predict which antigens T cells recognize from their genetic sequences.
Across 9,000+ T-cell receptors and 1,000+ epitopes, their model achieved 81–92% AUC on independent tests.
A major advance in decoding immune responses.
www.science.org/doi/10.1126/...
Across 9,000+ T-cell receptors and 1,000+ epitopes, their model achieved 81–92% AUC on independent tests.
A major advance in decoding immune responses.
www.science.org/doi/10.1126/...
General prediction of T cell receptor antigen specificity from sequence using AlphaFold 3
The major histocompatibility complex (MHC):peptide:T cell receptor (TCR) complex is the most diverse trimolecular interface known in nature and a key trigger for adaptive immunity. TCRs are now routin...
www.science.org
October 30, 2026 at 9:06 PM
Researchers at TGen used AlphaFold 3 to predict which antigens T cells recognize from their genetic sequences.
Across 9,000+ T-cell receptors and 1,000+ epitopes, their model achieved 81–92% AUC on independent tests.
A major advance in decoding immune responses.
www.science.org/doi/10.1126/...
Across 9,000+ T-cell receptors and 1,000+ epitopes, their model achieved 81–92% AUC on independent tests.
A major advance in decoding immune responses.
www.science.org/doi/10.1126/...
I wasn’t going to get into it with that dipshit, but Alphafold did not deliver as much as hoped, because it turns out dicking around with amino acids with an LLM like they are words only goes so far without a deeper quantum mechanical view of intermolecular/interatomic interactions.
November 3, 2026 at 6:08 PM
I wasn’t going to get into it with that dipshit, but Alphafold did not deliver as much as hoped, because it turns out dicking around with amino acids with an LLM like they are words only goes so far without a deeper quantum mechanical view of intermolecular/interatomic interactions.
In joint work, Andy Jones and Dan Rigden explored whether AF could help select the correct gene structure model, using original and manually curated pairs from two fungi and an apicoplast.
Registration is free but essential to secure your place on this webinar.
www.ebi.ac.uk/training/eve...
🧬🖥️📊
Registration is free but essential to secure your place on this webinar.
www.ebi.ac.uk/training/eve...
🧬🖥️📊
November 3, 2026 at 2:55 PM
In joint work, Andy Jones and Dan Rigden explored whether AF could help select the correct gene structure model, using original and manually curated pairs from two fungi and an apicoplast.
Registration is free but essential to secure your place on this webinar.
www.ebi.ac.uk/training/eve...
🧬🖥️📊
Registration is free but essential to secure your place on this webinar.
www.ebi.ac.uk/training/eve...
🧬🖥️📊
💡 Go beyond viewing AlphaFold structures in Jalview! Explore pLDDT and PAE metrics to assess prediction confidence, colour structures and identify putative protein domains.
⤵️ Video tutorials in comments
⤵️ Video tutorials in comments
November 5, 2026 at 3:57 PM
💡 Go beyond viewing AlphaFold structures in Jalview! Explore pLDDT and PAE metrics to assess prediction confidence, colour structures and identify putative protein domains.
⤵️ Video tutorials in comments
⤵️ Video tutorials in comments