A multimodal AI-driven framework for Bioscientists: from bulk to single-cell and spatial data

This project developed a multimodal AI-driven framework designed to help bioscientists analyse and integrate bulk, single-cell and spatial data. The work aimed to make advanced AI methodologies more accessible to researchers and facilitate insights from increasingly complex biological datasets.

Key Outputs

• An integrated framework for the analysis of multimodal biological datasets.
• Enhanced capability for applying AI approaches across multiple bioscience data types.
• Training activities delivered across the UK, including at the AIBIO-UK Annual Meeting 2026 in Aberdeen.
• Training materials supporting multimodal data integration and machine learning approaches.

Impact

The project has increased the adoption and accessibility of AI methods among bioscientists through the development of a multimodal analysis framework that integrates bulk, single-cell and spatial data, alongside the delivery of training activities across the UK. The framework enables researchers to analyse diverse biological datasets within a single workflow, supporting more comprehensive data interpretation. Feedback from participants was highly positive, and the project has already led to several new collaborations, with discussions underway for future joint research projects and larger grant applications.