Establishing shared evaluation standards to ensure AI models in biology are rigorous, reliable, and reproducible.

Foundation models are becoming increasingly popular across various biological domains, yet rigorous methods to comprehensively evaluate their full potential remain underdeveloped. This Perspective dis...

To what extent can large-scale approaches accurately reconstruct classic signaling pathways? Here, authors revisit the EGF pathway using phosphoproteomics and kinase-substrate interactions

New EMBL-EBI repository helps researchers share and reuse machine learning models trained on life science data.

We’re pleased to announce the launch of BEACON, a new open benchmarking consortium established through a collaborative effort by its founding partners from five organizations with deep expertise and p...

Julio Saez-Rodriguez discusses how MCP servers are helping AI connect to life science databases, making AI a more reproducible tool for research.

Your group The Petsalaki, Saez-Rodriguez (EMBL-EBI) and Korcsmáros (Imperial College) groups develop cutting-edge computational and AI approaches to unravel cellular signalling and gene regulation fro...

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Whether you're a scientist, IT specialist, accountant or administrator, you'll help us tackle the challenges of improving human health & biodiversity in the face of climate change on a global scal...

Jess Ewald, Research Group Leader at EMBL-EBI, uses cell profiling and AI to find and characterise chemical hazards to humans and ecosysystems.

EMBL-EBI’s newest Research Group Leader is investigating how somatic mutations reveal the hidden histories of human cells.

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