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Hello Mem 👋 just setting up my Twitter flow. Here's my validation code: Fa2XGQ3VEXgcXHcnxqSQ

🎉Exciting Update of scGPT 🎉: After receiving significant attention from the community since our April release, we're thrilled to announce the first major update for scGPT - a foundation model for single-cell multi-omic data. This update integrates community feedback and

This is so true

Looking forward for the webinar tomorrow!

Glad and super excited about this collaboration with #CELLxGENE. Now you can access scGPT embeddings directly from the census API online, and enjoy zero-shot reference mapping and other tasks seamlessly @CZIScience Human Cell Atlas Jonah Cool

Thrilled to release new tutorials for zero-shot applications using scGPT, and a new continual pretrained model ckpt for cell embedding related tasks! 🎉Great thanks to Kuan Pang for creating these. Please find at github.com/bowang-lab/scG…

Exactly, the raw “thought string” in the mind is the actual next tokens. The text written actually skips contents in between. It will be interesting if a way to collect the raw data

Amazing work and congrats JunMa

I am pretty sure the biotech chatGPT time is coming 💪

Thrilled to announce that our AGILE framework, an AI-guided LNP development for mRNA delivery, is now published in Nature Communications! 🎉 This is a collaborative work with @BowenLi_lab. (Re-)Introducing the AGILE Platform: A Deep Learning-Powered Approach to Accelerate LNP Development

🚀 We're thrilled to introduce Orthrus 🧬🐕—a groundbreaking mature RNA foundation model designed to push the boundaries of RNA property prediction! 🔬 What is Orthrus? Orthrus is a Mamba-based RNA foundation model, pre-trained using a novel self-supervised contrastive learning

Big congrats to Phil Fradkin , and such a great fitting name Orthrus!🎉

Glad to see our scGPT is helpful to many genomic researchers! 🙏🔥 Thanks for sharing this study!

Thanks a lot! Eric Topol We discussed unique opportunities and a few promising techniques for building virtual cell models. I am also personally so exited about this direction. nature.com/articles/s4158…

In the third paper, Bo Wang Toronto General Hospital Research Institute & team unveil a powerful #AI model that learns from layers of biological data to decode how life works—poised to revolutionize #biotech. Stay tuned for a feature story… Read here➡️ nature.com/articles/s4158… (4/4) Haotian Cui

A good read at weekend: a recent benchmark of perturbation analysis with machine learning (arxiv.org/pdf/2408.10609). Perturbation analysis is considered one of the key testbed for virtual cells with genomic foundation models. Although perturbation prediction remains an open