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🔥🔥 Check our latest generative model for antibody design GeoFlow, which can be used for both antigen-antibody complex structure prediction and de novo antibody design SOTA performance on Ab-Ag complex prediction, comparable to AF3 Try it here: geobiologics-lite.biogeom.com

Congratulations! We have tested this model on a collection of 160 SARS-CoV-2 RBD mAbs that have not been published before, and happily found ~43% structure predictions compatible with DMS-defined epitope and ~33% gives high-quality consistency (similar or even superior to AF3).

Glad to participate in this exciting ML conference for drug discovery. I shared our recent progress on "Geometric Deep Learning for Protein Understanding". Slides available at: dropbox.com/scl/fi/le5iqbi…

Can we steer the transcriptome foundation model (TFM) trained on scRNA-seq data? Check our recent work scCello, a transcriptome foundation model (TFM) guided by cell ontology. SOTA results on identifying new cell types, prediction of marker genes and drug responses.

Excited to deepen our collaboration with the global leader Sino Biological Inc. on protein/antibody production to push the frontier of generative AI in protein design! Another successful example of our protein generative AI foundational model GeoFlow in real-world applications.

Check out our new generative-AI platform for antibody design, GeoBiologics (geobiologics.biogeom.com/index) GeoBiologics are developed based on a lot of proprietary data from our partners and some latest generative AI models. Welcome to try it out!

🚨Just 1 WEEK left to go before paper submissions close for #MoML2024! Students + postdocs can receive FREE admission to #MoML2024 either by signing up for the Waitlist or having an accepted paper! 💰Win a cash prize for Best Paper!: moml.mit.edu/submit

Billion-dollar markets in the future: autonomous vehicles, humanoid robotics, quantum computing (which he says is 10-15 years away) and digital biology

Our recent work on protein conformation sampling. We proposed to deploy LLMs in the discrete latent space of protein structures. Code: github.com/lujiarui/esmdi… Paper: arxiv.org/abs/2410.18403

We are giving a tutorial on AI for protein design at this year's #AAAI, covering topics including: (1) Protein Representation Learning; (2) Protein Structure and Dynamics Prediction; (3) Protein Design. Welcome to join us!

Check our latest work at #ICLR2025 on using discrete diffusion language models for understanding protein dynamics!