PantheonOS: An Evolvable Multi-Agent Framework for Automatic Genomics Discovery

This seminar was delivered on 4 May 2026. For more information: https://spds.sydney.edu.au/ Speaker: Dr Weize Xu, Stanford University Abstract: The convergence of large language model-powered autonomous agent systems and single-cell biology promises a paradigm shift in biomedical discovery. However, existing biological agent systems, building upon single-agent architectures, are narrowly specialized or overly general, limiting applications to routine analyses. We introduce PantheonOS (https://PantheonOS.stanford.edu), an evolvable, privacy-preserving multi-agent framework designed to reconcile generality with domain specificity. Critically, PantheonOS enables agentic code evolution, allowing evolving state-of-the-art batch correction and our reinforcement-learning augmented gene panel selection algorithms to achieve super-human performance. PantheonOS drives biological discoveries across systems: uncovering asymmetric paracrine Cer1–Nodal inhibition in proximal–distal axis formation of novel early mouse embryo 3D data; integrating human fetal heart multi-omics with whole-heart data to reveal molecular programs underpin heart diseases; and adaptively selecting virtual cell models to predict cardiac regulatory and perturbation effects. Together, PantheonOS points towards a future where scientific discoveries are increasingly driven by self-evolving AI systems across biology and beyond. About the speaker: Dr Weize Xu is a postdoctoral researcher in Dr Xiaojie Qiu’s laboratory, where he focuses on advancing computational biology and genomics research. He earned his PhD in Dr Gang Cao’s lab, where he made significant contributions to the development of computational methods and pipelines for spatial transcriptomics (MiP-Seq) and single-cell Hi-C (sciDLO Hi-C). His work during this time centered on enhancing data analysis frameworks, providing more precise insights into complex biological systems.