Author

François Paris

Centre de Recherche en Cancérologie et Immunologie Intégrée Nantes AngersORCID 0000-0002-0176-7348Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Cancer Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:cancer & tumor microenvironment· 1 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Approach:experimental assay· 1 Organism:human· 1 Assay:imaging· 1 Assay:proteomics· 1

Frequent Co-Authors

A. PerriniD· 1 shared Anne ClavreuliD· 1 shared Arrate Muñoz‐BarrutiaiD· 1 shared Audrey RousseauiD· 1 shared Béatrice ClemenceauiD· 1 shared Catherine GratasiD· 1 shared Claire PecqueuriD· 1 shared Clément Philippe DelannoyiD· 1 shared

Activity by Year

2023-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

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1 shared paperCancer Biology

A. PerrinORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

Functional diversity of Vγ9Vδ2 T cells overcomes glioblastoma state plasticity and antigen heterogeneity

Pierre Paris, Marine Devinat, Julianne Ceroni, Elodie Guiet, Jocelyn Ollier, Mélanie Laurent—Blond, Pauline Thomas, M. Gaudin, Noémie Joalland, A. Perrin, Clément Philippe Delannoy, Audrey Rousseau, Philippe Meneï, Emmanuel Scotet, François Paris, , Claire Pecqueur

This study shows that combining GD2/OAcGD2-specific CAR and unmodified Vγ9Vδ2 T cells can overcome glioblastoma heterogeneity by targeting both PN and MES tumor states.

bioRxiv · May 21, 2026 · PreprintCancer Biology

Automatic Classification of Normal and Abnormal Cell Division Using Deep Learning Analysis of Mitosis Videos

Pablo Delgado-Rodriguez, Rodrigo Morales-Sánchez, Elouan Rouméas-Noël, François Paris, Arrate Muñoz‐Barrutia

This paper develops a deep learning classifier to distinguish normal from abnormal cell division in mitosis videos, achieving high accuracy in classification.

bioRxiv · Apr 27, 2023 · PreprintBioinformatics