Author

Frédéric Davi

Sorbonne UniversitéORCID 0000-0002-3764-063XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:statistical model· 5 Research Focus:benchmarking· 3 Research Focus:clustering· 3 Assay:CITE-seq· 2 Organism:human· 2 Research Focus:software / tool· 2 Research Focus:database / resource· 1 Research Focus:dimensionality reduction· 1

Frequent Co-Authors

Anne Langlois de Septenville· 4 shared Juliana BernardesiD· 4 shared Nika AbdollahiiD· 4 shared Lucile Jeusset· 2 shared Agustí AlentorniD· 1 shared Albert Pons‐EscodaiD· 1 shared Anna SchmittiD· 1 shared Audrey RousseauiD· 1 shared

Activity by Year

2020-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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4 shared papersBioinformatics

Anne Langlois de Septenville

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Author profile →

5 papers

Recent·Most cited

Morphologic intratumoral heterogeneity from routine whole-slide histopathology is prognostic for survival in primary central nervous system lymphoma: development in the LOC Network and international external validation

Lucas Rincón de la Rosa, Noemie Barillot, Isaias Hernández-Verdín, Roser Velasco, Bertrand Mathon, Sandrine Eimer, Jean Rodolphe Vignes, Audrey Rousseau, Jérôme Paillassa, Guido Ahle, Felix Lerintiu, Emmanuelle Uro‐Coste, Lucie Obéric, Émeline Tabouret, Romain Appay, , Agustí Alentorn

The paper develops and validates a prognostic model using morphologic intratumoral heterogeneity from histopathology slides to predict survival in primary central nervous system lymphoma.

bioRxiv · Sep 3, 2026 · PreprintBioinformatics

ViCloD, an interactive web tool for visualizing B cell repertoires and analyzing intra-clonal diversities: application to human B-cell tumors

Lucile Jeusset, Nika Abdollahi, Thibaud Verny, Marine Armand, Anne Langlois de Septenville, Frédéric Davi, Juliana Bernardes

NAR Genomics and Bioinformatics · Mar 29, 2023Peer-reviewedBioinformatics

Reconstructing the evolutionary history of a B cell lineage with minimum spanning tree and genotype abundances

Nika Abdollahi, Lucile Jeusset, Anne Langlois de Septenville, Frédéric Davi, Juliana Bernardes

ClonalTree reconstructs B cell lineage trees using genotype abundances and minimum spanning trees, outperforming existing methods in speed and accuracy for high-throughput BCR sequencing data.

bioRxiv · Feb 27, 2022 · PreprintBioinformatics

A multi-objective based clustering for identifying clonally-related sequences from high-throughput B cell repertoire data

Nika Abdollahi, Anne Langlois de Septenville, Hugues Ripoche, Frédéric Davi, Juliana Bernardes

This paper introduces a multi-objective clustering method for identifying clonally-related sequences in B cell repertoire data, showing improved accuracy and efficiency compared to existing tools.

bioRxiv · Oct 1, 2021 · PreprintBioinformatics

Automatic generation of ground truth data for the evaluation of clonal grouping methods in B-cell populations

Nika Abdollahi, Anne Langlois de Septenville, Frédéric Davi, Juliana Bernardes

The paper introduces a method to generate high-precision ground truth data for evaluating clonal grouping methods in B-cell populations using real repertoires and V(D)J annotations.

bioRxiv · Nov 30, 2020 · PreprintBioinformatics