Author

Quentin Blampey

InsermORCID 0000-0002-3836-2889Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:spatial transcriptomics· 4 Approach:deep learning· 3 Research Focus:dimensionality reduction· 3 Assay:imaging· 3 Research Focus:benchmarking· 2 Research Focus:cell type annotation· 2 Research Focus:clustering· 1 Approach:experimental assay· 1

Frequent Co-Authors

Paul-Henry CournèdeiD· 4 shared Hakim BenkiraneiD· 3 shared Stergios ChristodoulidisiD· 3 shared Fabrice AndréiD· 2 shared Félicie Giraud-SauveuriD· 2 shared Florent GinhouxiD· 2 shared Kevin MulderiD· 2 shared Arianna MarinelloiD· 1 shared

Activity by Year

2024-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 32 mutual co-author links

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4 shared papersBioinformatics

Paul-Henry CournèdeORCID

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4 papers

Recent·Most cited

ALHENA, an H&E encoder distilled from transcriptomic foundation models for multi-scale slide analysis

Félicie Giraud-Sauveur, Quentin Blampey, Pierre Marza, Hakim Benkirane, Maria Vakalopoulou, Paul-Henry Cournède, Stergios Christodoulidis

ALHENA improves transcriptomic signature prediction and cell-type separability using H&E images alone, without requiring spatial transcriptomics data.

bioRxiv · Oct 25, 2026 · PreprintBioinformatics

STHELAR, a multi-tissue dataset linking spatial transcriptomics and histology for cell type annotation

Félicie Giraud-Sauveur, Quentin Blampey, Hakim Benkirane, Arianna Marinello, Paul-Henry Cournède, Stergios Christodoulidis

The paper introduces STHELAR, a multi-tissue dataset integrating spatial transcriptomics and H&E images for cell type annotation in cancer research.

Scientific Data · Mar 12, 2026Peer-reviewedCell Biology

Novae: a graph-based foundation model for spatial transcriptomics data

Quentin Blampey, Hakim Benkirane, Nadège Bercovici, Kevin Mulder, Grégoire Gessain, Florent Ginhoux, Fabrice André, Paul-Henry Cournède

Novae is a graph-based foundation model for spatial transcriptomics that improves domain inference and batch correction across multiple tissues and technologies.

Nature Methods · Dec 1, 2025Peer-reviewedBioinformatics

Sopa: a technology-invariant pipeline for analyses of image-based spatial-omics

Quentin Blampey, Kevin Mulder, Margaux Gardet, Stergios Christodoulidis, Charles‐Antoine Dutertre, Fabrice André, Florent Ginhoux, Paul-Henry Cournède

Sopa provides a technology-invariant pipeline for analyzing image-based spatial-omics data, offering unified visualization and analysis tools.

Nature Communications · Jun 11, 2024Peer-reviewedBioinformatics