Excited to share our new paper in Nature Methods! 🚀 We present iSCALE, a “Google Map” for spatial transcriptomics, scaling cellular-resolution gene expression mapping to large-sized tissues beyond the reach of current platforms. 👉nature.com/articles/s4159…

Congrats to my colleagues Oana Carja's NSF CAREER cs.cmu.edu/news/2025/carj… and Yun William Yu's NIH MIRA cs.cmu.edu/news/2025/yu-m… 🎉their work exemplifies CMU comp bio: innovative & distinct methodology grounded in biological applications with real impact. Ray and Stephanie Lane Computational Biology Dept. CMU School of Computer Science

Do you know ~60% of human SVs fall in ~1% of GRCh38? See our new preprint: arxiv.org/abs/2509.23057 and the companion blog post on how we started this project and longdust: lh3.github.io/2025/09/29/on-…. Work with Qian Alvin Qin

🧪Announcing Biomni × PyLabRobot — a step toward an AI biologist that can think, design, and execute wet-lab experiments end-to-end. See Biomni in action below 👇 Super fun collab with Retro Biosciences Rick Wierenga Serena Zhang! Learn more: biomni.stanford.edu/blog/pylabrobo…

Biomni-R0-32B-Preview is now open-weight on Hugging Face! Biomni-R0-32B is biomedical AI model trained by the Biomni team. It beats GPT-5 and Claude Sonnet 4. To ground progress, we’re also releasing Biomni-Eval1 — 443 data points across 10 tasks for benchmarking agent on

So much of biomedical research rests on tacit knowledge—unwritten and invisible to LLMs—causing agents to underperform. The Biomni Open Know-How Catalogue bridges that gap: a curated library of human expertise that Biomni agents use intelligently on the fly, with dramatic gains.

Happy to share #DNALONGBENCH Nature Communications. We challenge DNA #FoundationModels w/ long-range sequence context and hope this sparks more meaningful ways to evaluate growing AI+BIO models. Kudos to Wenduo Cheng Zhenqiao Song Yang Zhang. Great collab w/ Lei Li @NeurIPS2025. nature.com/articles/s4146…