Collection
AI readiness for the future of biomedical data
A collection of recordings from AIBIO-UK EMBL-EBI AI readiness workshop
Time to complete:
> 3 hours
This course includes:
Written by:
Last reviewed:
March 2026
All materials are free cultural works licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license, except where further licensing details are provided.
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The surge in biomedical data fueled by AI is outpacing our ability to curate it. This collection features recorded lectures and discussions from AI experts in bioinformatics from academia and industry, focused on shaping future AI readiness within the community.
Who is this course for?
This collection is suitable for data generators, data stewards, data/resource and tools developers interested in creating/maintaining clean and AI ready data in the bioinformatics space. No prior knowledge of the field is required, but a basic knowledge of artificial intelligence would be helpful.
This collection is created in association with the AIBIO-UK.
What will I achieve?
By the end of the course you will be able to:
- Identify diverse use cases of AI integration in research and development
- Describe challenges and opportunities in deploying AI in data curation
DOI: 10.6019/TOL.ai-readiness-future-biodata-t.2026.00001.1
Course contents
- Introduction
- Building AI-ready data foundations for drug discovery and development
- An agentic AI framework for scalable curation of NER dictionaries derived from biomedical ontologies
- Understanding ancestry biases in HLA-related datasets: implications for machine learning predictors and healthcare equity
- AI in plant genomics
- Towards AI–assisted biocuration and FAIR pathogen–host knowledge
- Digital twins of rare diseases
- AI readiness for biological datasets: perspectives from the AIRBDS working group
- Challenges with deploying agentic AI for biomedical data integration and curation
- Summary: future actions and remarks
- Your feedback
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