Author

Flora Crozet

Centre National de la Recherche ScientifiqueORCID 0009-0001-9115-8991Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 1 Organism:human· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1 Organism:mouse· 1

Frequent Co-Authors

Adrien Eichmuller· 1 shared Christelle Da SilvaiD· 1 shared Elsa LabruneiD· 1 shared Elvira NikalayevichiD· 1 shared Gaëlle LetortiD· 1 shared Jean‐Philippe WolfiD· 1 shared Jérémy SalléiD· 1 shared Marie‐Emilie TerretiD· 1 shared

Activity by Year

2022-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperBioinformatics

Adrien Eichmuller

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1 paper

Recent·Most cited

An interpretable and versatile machine learning approach for oocyte phenotyping

Gaëlle Letort, Adrien Eichmuller, Christelle Da Silva, Elvira Nikalayevich, Flora Crozet, Jérémy Sallé, Nicolas Minc, Elsa Labrune, Jean‐Philippe Wolf, Marie‐Emilie Terret, Marie‐Hélène Verlhac

This paper develops a machine learning framework for oocyte phenotyping using transmitted light images, identifying new features to assess maturation potential in mouse and human oocytes.

Journal of Cell Science · Jun 6, 2022Peer-reviewedBioinformatics