Pascal Notin
@NotinPascal
Research in AI for Protein Design @Harvard | Prev. CS PhD @UniofOxford, Maths & Physics @Polytechnique
🧬 😴 TIRED: Scaling protein models to billions of parameters hoping they'll memorize all of evolution and generalize beyond 🔥 WIRED: Smart retrieval-augmented models that dynamically access what they need from sequence databases
🚨ICML Paper Alert🚨 What if finding the right protein homologs wasn't a slow search, but a learned part of the model itself? We introduce 𝐏𝐫𝐨𝐭𝐫𝐢𝐞𝐯𝐞𝐫, an end-to-end framework that learns to retrieve the most useful homologs for self-supervised reconstruction! (1/12)
I wonder if the gym membership for ProteinGym covers RNAGym as well?? oh wait, it's all free and 100% open source!
🚨 New paper 🚨 RNA modeling just got its own Gym! 🏋️ Introducing RNAGym, large-scale benchmarks for RNA fitness and structure prediction. 🧵 1/9
What would our data landscapes look like if we could biochemically characterize 100s, 1000s, 10^n evolutionary sequences? Papers like this make strides towards that moonshot dream!! Such neat work from @MargauxPinney lab! science.org/doi/10.1126/sc…
1/4 🚀 Announcing the 2025 Protein Engineering Tournament. This year’s challenge: design PETase enzymes, which degrade the type of plastic in bottles. Can AI-guided protein design help solve the climate crisis? Let’s find out! ⬇️ #AIforBiology #ClimateTech #ProteinEngineering…
Save the date! Machine Learning for Drug Discovery (MLDD) is happening soon on Monday 30 June, 2025. MLDD aims to bring together ML for drug discovery experts, innovators, and enthusiasts from the machine learning, biotechnology and drug discovery domains in London, UK to…
As sequence databases get bigger and more diverse, retrieval-based methods provide an interesting alternative to scaling successively bigger protein language models. (1/5)
🚨ICML Paper Alert🚨 What if finding the right protein homologs wasn't a slow search, but a learned part of the model itself? We introduce 𝐏𝐫𝐨𝐭𝐫𝐢𝐞𝐯𝐞𝐫, an end-to-end framework that learns to retrieve the most useful homologs for self-supervised reconstruction! (1/12)
End-to-end differentiable homology search for protein fitness prediction. @ruben_weitzman @lood_ml @yaringal @deboramarks @NotinPascal
Future-proofed vaccine design with generative models that predict viral evolution 👇
🚨 New in @ImmunityCP ! EVE-Vax, an AI model that anticipates future viral evolution and designs antigens to proactively test vaccines + therapeutics—before variants even emerge. We envision this work will help make future-proofed vaccines and therapeutics. 👇 (1/7)
🚨 New in @ImmunityCP ! EVE-Vax, an AI model that anticipates future viral evolution and designs antigens to proactively test vaccines + therapeutics—before variants even emerge. We envision this work will help make future-proofed vaccines and therapeutics. 👇 (1/7)