To Immunity and Beyond
To Immunity and Beyond
Podcast Description
In a series produced by the Oxford Immunology Network, Professor Paul Klenerman talks with colleagues about their recent ground-breaking publications, exploring the original scientific goals, challenges they encountered along the way, and future ambitions in the field. This series will be of interest to anyone studying or working in immunology, medical sciences, biology or related fields.
NB: To Immunity and Beyond is for educational purposes only and should not be considered professional medical advice.
Podcast Insights
Content Themes
The series centers on pivotal themes in immunology, medical sciences, and biology, exploring current research advancements. Specific episode examples include discussions on CAR-T cell sensitivity engineering, the role of ADAM10 in T cell efferocytosis, and genetic risks for multiple sclerosis in historical populations, presenting foundational studies and their implications for future research.
In a series produced by the Oxford Immunology Network, Professor Paul Klenerman talks with colleagues about their recent ground-breaking publications, exploring the original scientific goals, challenges they encountered along the way, and future ambitions in the field. This series will be of interest to anyone studying or working in immunology, medical sciences, biology or related fields.
NB: To Immunity and Beyond is for educational purposes only and should not be considered professional medical advice.
A conversation with Dr Rufus Daw about CellTypeAI. As single-cell datasets grow from thousands to hundreds of thousands of cells, accurate cell annotation is becoming a major bottleneck in biomedical research. In this episode, bioinformatician Rufus Daw discusses CellTypeAI, a new locally deployable AI framework that uses large language models to automate cell-type identification from single-cell RNA sequencing data. We explore how privacy-preserving AI tools, retrieval-augmented generation, and ensemble prompting can match or exceed conventional annotation approaches while keeping sensitive research data entirely in-house, and what this means for the future of AI-assisted immunology and systems biology.
Further resources:
Rufus H. Daw, Harry R. Deijnen, Magnus Rattray, John R. Grainger, ‘CellTypeAI: Automated cell identification for scRNA-seq using local generative-AI’, preprinted posted on bioRxiv March 05, 2026. https://doi.org/10.64898/2026.03.03.709253 [doi.org]
Rufus Daw talk: LLMs in the Laboratory: practical tools for AI-assisted research.
https://www.youtube.com/watch?v=I7AlwgYnu9c [youtube.com]
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