I am often asked by scientists across fields for advice & resources on how to get started with #scRNAseq analyses I summarize here such an analysis into a flowchart with 9 core steps. Analyzing your own scRNAseq data today is more accessible than ever And it gets even easier🧵

Excited to share that we are emerging from stealth mode today! Stay tuned for updates as we use AI to transform the drug discovery process

We are looking for talented postdocs/visiting students to join our team MIT Dept of BE and Koch Institute at MIT to innovate spatial multi-omics technologies, map clinical samples, and integrate AI/ML models to advance next-generation cancer immunotherapy. Please help to spread!!

Today, we're releasing the fuel for the next generation of AI in biology 🧬 X-Atlas/Orion is now the largest public genome-wide Perturb-seq dataset, built to create better “virtual cell” models and accelerate drug discovery. Learn more: businesswire.com/news/home/2025…

Such an exciting initiative. Congrats to all those involved! Hope people put the X-Atlas/Orion dataset to use 💪

In the wake of all the Bio x AI updates, I'm also here to spread awareness of important cat-related research. Isparta et al analyzed 400+ cat videos and found that cats favor the leftward side (p < 0.001), allowing for fast response to stimuli. Paper: cell.com/current-biolog…

New to virtual cells? freethink’s primer explains these AI-powered, in silico models—why they’re game-changers for biology & the hurdles still to solve. Worth a read bit.ly/4ljre1j

Virtual Cell community - this one's for you! X-Atlas/Orion is now live on Hugging Face. Train your own models with streamlined workflows built into the Hugging Face API. 🔗 HuggingFace: huggingface.co/datasets/Xaira… 📜 License: cc-by-nc-sa-4.0