Author

Elsa D. Angelini

Télécom ParisORCID 0000-0002-1602-300XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Assay:imaging· 2 Approach:benchmark study· 1 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Research Focus:differential expression· 1 Organism:human· 1

Frequent Co-Authors

Abdul I. BarakatiD· 1 shared Bettina Roellinger· 1 shared Catherine CoiraultiD· 1 shared Claire LeclechiD· 1 shared Francois ThenieriD· 1 shared Loïc Le FolgociD· 1 shared Yekta KesenciiD· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 11 mutual co-author links

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1 shared paperCell Biology

Abdul I. BarakatORCID

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2 papers

Recent·Most cited

Benchmarking the robustness of segmentation models to corruptions in biological imaging

Yekta Kesenci, Loïc Le Folgoc, Elsa D. Angelini

This study benchmarks segmentation models' robustness to corruptions in biological imaging, finding that older methods can be more robust than newer foundation models.

bioRxiv · Aug 25, 2026 · PreprintBioinformatics

A Variational Autoencoder Model for Clustering of Cell Nuclei on Microgroove Substrates: Potential for Disease Diagnosis

Bettina Roellinger, Francois Thenier, Claire Leclech, Catherine Coirault, Elsa D. Angelini, Abdul I. Barakat

This study uses a variational autoencoder to cluster nuclei on microgroove substrates, distinguishing between wildtype and laminopathy myoblasts based on nuclear deformation.

Scientific Reports · Jul 1, 2025Peer-reviewedCell Biology