Weize Xu @Nanguage

Excited to share Navigo, our first step toward building an AI-powered Virtual Embryo! By integrating flow matching at the population level with RNA kinetics modeling at the molecular level, and learning developmental dynamics from 12.4 million single cells across 43 embryonic time points, Navigo transforms static snapshots into a continuous, generative model of embryogenesis. The model enables: 1. 🧬 Predicting developmental trajectories across the entire mouse embryogenesis 2. 🫀 Enabling disease modeling by mechanistically resolving regulatory networks that distinguish congenital heart disease subtypes 3. 🧪 Zero-shot genetic perturbation prediction and uncovering lineage-specific gene-compensation mechanisms 4. 🔬 Rational cell-fate engineering, exemplified by fibroblast reprogramming analyses, including identifying pro-fibrotic barriers to cardiac fates and evaluating hundreds of pairwise transcription factor combinations for neuronal fate, each consisting of one bHLH factor and one POU factor We hope this represents an important milestone toward predictive, in silico developmental biology, where virtual embryos can help us understand, simulate, and eventually engineer development. A huge congrats to @YiminFanCUHK from Dr. Yu Li's group at CUHK on this awesome work and all members in my lab and collaborators who made this work possible, and especially to @LaudeInstitute for supporting our vision of building AI-native virtual embryos. We also thank @JShendure @CXchengxiangQIU @junyue_cao @malte_spielmann @XingfanH Jana Henck and @coletrapnell for reporting the original studies and for producing the data we used for training and prediction!

Learn about the PantheonOS Researcher Access Program, fill out the form to receive $200 in monthly usage credits for 3 months. 👐

evo-devo @Xiaojie_Qiu

2 weeks ago

🧬 Introducing PantheonOS Researcher Access After extensive internal testing and validation, the PantheonOS online platform is now stable, scalable, and ready for real-world biological research. We're excited to open applications for our first Researcher Access cohort on top of

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🧬 Introducing PantheonOS Researcher Access After extensive internal testing and validation, the PantheonOS online platform is now stable, scalable, and ready for real-world biological research. We're excited to open applications for our first Researcher Access cohort on top of our current free access program. PantheonOS is an AI-native scientific workbench for biological data science. Simply upload your single-cell, spatial, imaging, or genomics datasets, and an AI research agent collaborates with you to perform analyses using real bioinformatics tools, interactive scientific viewers, executable notebooks, and publication-quality figures and reports, all directly in your browser. Unlike traditional analysis pipelines, PantheonOS enables researchers to interact with their data through an evolving team of specialized AI agents, accelerating discovery while maintaining transparency, reproducibility, and scientific rigor. To support early adopters, selected members of our first cohort will receive: • $200/month in free compute credits for 3 months • Full access to the PantheonOS online platform • Direct support from the development team • Opportunities to influence the future direction of the platform We welcome applications from wet-lab scientists, bioinformaticians, pharmaceutical and biotech R&D teams, computational biologists, and clinicians across the life sciences. Extensive contributors will be invited to be co-authors on the PantheonOS work and to collaborate on future PantheonOS publications. Apply: docs.google.com/forms/d/e/1FAI… Learn more: pantheonos.stanford.edu/blog/pantheono…

Interaction between users and agents should not be limited to conversation. LiveView enables interaction among users, agents, and visual components. Unlike Canvas, LiveView allows the agent to fully control components and read their state, and it can dynamically generate new LiveViews to create interaction modes beyond the built-in components. This is very convenient for visual data exploration. See more details at: pantheonos.stanford.edu/blog/pantheono…

evo-devo @Xiaojie_Qiu

2 weeks ago

Introducing PantheonOS Live View PantheonOS agents can now open popular interactive scientific viewers, including 3D Spatial Viewer with WebGL, Viv (spatial imaging), Vitessce (single cell & spatial omics), IGV (genomics browser), and Mol* (3D molecular structures), directly on

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Introducing PantheonOS Live View PantheonOS agents can now open popular interactive scientific viewers, including 3D Spatial Viewer with WebGL, Viv (spatial imaging), Vitessce (single cell & spatial omics), IGV (genomics browser), and Mol* (3D molecular structures), directly on your data, explore data interactively with your agent, and generate publication-grade figures, all live in your browser. This transforms the agent experience from static reports into an interactive, visual workflow where you can inspect data, explore results, and follow analyses as they happen. Alongside Live View, the PantheonOS online platform has received a major upgrade, delivering substantially improved stability and reliability for long-horizon analyses, together with more than 4× faster execution speeds than previous releases.

i only recently came across pantheon-os, which is an awesome multi-agent framework for doing genomics research from @Xiaojie_Qiu and his team of collaborators. what struck me most is that unlike most other multi agent frameworks or ai scientists that i have come across, pantheon-os displays a serious effort in building a thoughtful software which other researchers can use. some of the features that i found fascinating were: > there is a marketplace where users can discover and share reusable biomedical ai building blocks such as agents, tools and skills. > employs evolutionary search to iteratively improve (aka autoresearch) algorithms that are used for batch correction in rna-sequencing and it used the map-elites style algorithm (conceptually similar to what has been used for idea exploration in alphaevolve from @GoogleDeepMind). > what xiaojie showed us is that one can use pantheon-os to build detailed research reports/papers end to end starting from given input genomics samples, images, etc., with minimal to no human intervention and the finally analysis happens to be fully reproducible. > comes in cli, desktop app and web ui and it is fully open source. > supports multiple multi-agent architecture such as mixture-of-agents (llm council style), sequential agents (assembly line style), coordinator-agent (one agent delegating tasks to other agent), etc. > privacy-preserving in the sense that the underlying data such as genomics data doesn't have to be uploaded to cloud but can be in local server, etc. xiaojie and his team of collaborators has done extraordinary work in building this.

evo-devo @Xiaojie_Qiu

2 months ago

PantheonOS allows any biologist to perform complex data analyses of emerging single cell, multi-omics and spatial transcriptomics datasets end to end through AI agent and human collaboration. We are releasing six replays of use cases trajectories. Each "trajectory" is a complete

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PantheonOS allows any biologist to perform complex data analyses of emerging single cell, multi-omics and spatial transcriptomics datasets end to end through AI agent and human collaboration. We are releasing six replays of use cases trajectories. Each "trajectory" is a complete end-to-end run, from prompt to analysis, to figures, and finally to report, and in fully inspectable and reproducible manner. See the six user cases in our PantheonOS Gallery: 1. 3D mouse embryo analysis: Tangram deconvolution and PyVista-based 3D visualization of E6 mouse embryo spatial transcriptomics data 2. 3D human fetal heart analysis: Spatial mapping of heart disease gene patterns using MERFISH data 3. Multi-omics spatial integration: Single cell multi-omics-to-spatial mapping with MOSCOT optimal transport 4. Gene panel design: 1000-plex immune-oncology MERFISH gene panel optimization 5. Cell segmentation benchmarking: Comparative evaluation of Cellpose-SAM, InstanSeg, StarDist, and other tools 6. Spatial disease biology: Ligand–receptor analysis of disease-associated tissue microenvironments We would love to hear how you can use PantheonOS for your research! Got an interesting agent run of your own and want to share? In the Pantheon UI, click Export Bundle (top-right of any chat) to package the full trajectory — chat history, code, figures, report — then submit it here:

@yodai_takei @biohub Congratulations!

@turingou @macbai21 其实还行，之前也以为要吃苦，来了发现好吃的中餐还挺多😂

PantheonOS Now Tackles Gene Panel Design Gene panel selection represents a critical bottleneck in spatial and single-cell genomics, where suboptimal choices compromise cell-type resolution and experimental validity. Pantheon automates this end-to-end via multi-agent workflow orchestration. A leader agent orchestrates the full pipeline, delegating to specialized analyzers that dynamically route tools and benchmark strategies in real time — enabling long-horizon, autonomous discovery. What can Pantheon do? 🧬 Multi-strategy gene selection — orchestrating parallel selection strategies to synthesize a single optimized panel. 📊 Clustering-aware optimization and biological grounding — directly maximizing ARI/NMI metrics while grounding decisions in domain knowledge, for panels that are both statistically and biologically meaningful. 📄 Self-documenting, reproducible runs — generating live notebooks, agent traces, and automated PDF reports with zero manual intervention. Unless you want to interact with it! Benchmarked on pan-cancer immuno-oncology with @Vizgen, PantheonOS achieves superior overlap with expert-curated panels while outperforming classical baselines on clustering metrics. Built on PantheonOS — the first evolvable, multi-agent operating system for biological discovery. Genomics is the beginning; the architecture goes beyond, and PantheonOS is fine-tunable for domain-specific scientific research. 📄 Preprint: biorxiv.org/content/10.648… 🌐 Website: pantheonos.stanford.edu Thank you to Erwin and @Nanguage for this incredible opportunity, and to @JiangHe_PhD , Lorenz Rongioni and the entire Vizgen @vizgen_inc team for the amazing collaboration. More to come soon!

Thanks to Qian Zhang (@QianZhang12138), Huaiyuan Cai (@hycai_wikk), and the team for their contributions. Qian Zhang is currently seeking a PhD position. She has strong engineering skills and a deep understanding of biological image processing and FISH probe design. If interested, please feel free to get in touch.

U-Probe is available as an open source software: • Web interface for interactive design • CLI for batch workflows • Agent interface for assisted design It supports the full workflow from design specification → probe generation → export. Resources: 📄 Preprint: biorxiv.org/content/10.648… 🌍 Website: u-probe.org 💻 GitHub: github.com/UFISH-Team/U-P… Feedback and use cases are very welcome!

Introducing U-Probe — the first agent-assisted platform for FISH probe design. 🧬 Probe design today is still fragmented and expert-heavy: different tools for different protocols, manual parameter tuning, and limited support for new probe designs. U-Probe addresses this by: • Supporting diverse protocols (MERFISH, seqFISH, DNA-FISH, etc.) • Enabling custom probe architectures via a programmable framework • Using AI agents to assist with panel design and parameter selection ⚙️ Built on the @PantheonOS evolvable multi-agent framework → from experimental goal to synthesis-ready probes

U-Probe: universal agentic probe design for imaging-based spatial-omics biorxiv.org/content/10.648… #biorxiv_bioinfo

PantheonOS v0.5.1+ is out. Highlights: • PantheonClaw gateway integration • Free OAuth via Codex CLI & Gemini CLI • LiteLLM removed → native SDK adapters • Intelligent context optimization + autocompact Release notes: pantheonos.stanford.edu/blog/pantheono… #AI #Agents #OpenSource

Huge congratulations to @Xiaojie_Qiu and the team on winning the Laude Institute Moonshots Seed Grant for the Virtual Embryo project. @PantheonOS will serve as the agent interface layer in this effort, helping connect AI agents with predictive model and large-scale multimodal embryogenesis data. Excited to be part of this vision: building a digital twin of mammalian embryogenesis and advancing the future of developmental biology and human health. 🚀🧬

evo-devo @Xiaojie_Qiu

3 months ago

Big news: Our Virtual Embryo project has been selected as a Laude Institute Moonshots Seed Grant winner — chosen from 125 proposals evaluated by 600+ leading researchers. I’m deeply honored to be recognized alongside a remarkable community that includes Fields Medalists like

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Advancing Healthcare track: Research that supports medical practitioners in diagnosis, treatment, and patient care. 🧬The Virtual Embryo Moonshot, @Stanford One in 33 newborns is affected by congenital defects. This team is building the first predictive digital twin of human embryonic development to help change that. @Xiaojie_Qiu Emily Fox @marinkazitnik @james_y_zou ⚕️JupyterHealth, @UCJointCPH @UCBerkeley @UCSF Project Jupyter became the shared infrastructure of modern science. This team is doing the same thing for healthcare. @Idasim @_ahmedmalaa @irenetrampoline @DrMayaPetersen Fernando Pérez

Big news: Our Virtual Embryo project has been selected as a Laude Institute Moonshots Seed Grant winner — chosen from 125 proposals evaluated by 600+ leading researchers. I’m deeply honored to be recognized alongside a remarkable community that includes Fields Medalists like Terence Tao, Nobel laureates like Michael Kremer, Turing Award winners like Raj Reddy, and creators of transformative tools such as Jupyter Notebook. We are now building (1) the largest time-resolved organism-level 3D perturbation atlas of mouse embryogenesis; (2) what could become the first digital twin of mammalian embryogenesis — a predictive model of development designed to uncover the mechanisms of congenital disease and ultimately help ensure that every newborn has the healthiest possible start in life. If this vision excites you, come build with us — alongside Emily Fox, James Zou (@james_y_zou), and Marinka Zitnik (@marinkazitnik). Thank you to @LaudeInstitute for believing in this vision. We also welcome industrial and philanthropic partners who want to help shape the future of developmental biology and human health.

We're excited to release Pantheon-Claw: a multi-channel IM gateway that brings PantheonOS's agentic AI capabilities to the messaging apps you use every day. Supported Channels (7): Telegram · Discord · Slack · WeChat · Feishu · QQ · iMessage What can you do? 📱 Chat from your phone: Send tasks to your AI agent while on the go. Ask it to download data, run analyses, generate plots — all from a text message. 🖼️ Rich media support: Send files and images to the agent, receive generated plots and reports back. 👥 Group collaboration: Mention @PantheonClaw in Slack or Discord. The agent identifies speakers and maintains shared context across the team. 🔧 Easy setup: Built-in step-by-step configuration guides for each platform. Collapsible instructions cover bot creation, permissions, and token setup — no extra docs needed. Built on PantheonOS, our fully open-source agentic platform for computational biology and beyond.