Author

Léa Ledoux

Université de LilleORCID 0009-0007-8963-7073Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioengineering· 1 Bioinformatics· 1 Cancer Biology· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Research Focus:cell type annotation· 2 Research Focus:differential expression· 2 Approach:machine learning (classical)· 2 Research Focus:benchmarking· 1 Research Focus:cell-cell communication· 1 Research Focus:database / resource· 1 Research Focus:dimensionality reduction· 1

Frequent Co-Authors

Isabelle FournieriD· 3 shared Michel SalzetiD· 3 shared Yanis ZiremiD· 3 shared Alexandre Goosen· 1 shared Cedric J. LioniD· 1 shared Chann H. LagadeciD· 1 shared Charlotte DufouriD· 1 shared Doriane Bomont· 1 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 34 mutual co-author links

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3 shared papersBioinformatics

Isabelle FournierORCID

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Author profile →

3 papers

Recent·Most cited

BioinformaticsbioRxivPreprintOct 22, 2026

SpacePath enables pathway and molecular-family analysis beyond annotation ambiguity in spatial metabolomics and lipidomics

Johanna Galvis, Mélanie Moreau, Sebastian Lillo…·Macha Nikolski

SpacePath improves spatial metabolomics analysis by handling molecular ambiguity and identifying novel lipid families in spatial datasets.

DOI 10.64898/2026.10.16.759546

𝕏 PostBluesky

Cancer BiologybioRxivPreprintOct 13, 2025

Transforming Esogastric Cancer Surgery Integrating SpiderMass Mass Spectrometry with Clinical and Microbiome Data for Margin Delineation and Prognosis

Léa Ledoux, Yanis Zirem, Alexandre Goosen…·Isabelle Fournier

The paper integrates SpiderMass mass spectrometry with clinical and microbiome data to improve intraoperative margin delineation and prognosis in esophageal-gastric cancers.

DOI 10.1101/2025.10.13.682035

humanmetagenomics

𝕏 PostBluesky

BioengineeringbioRxivPreprintDec 8, 2024

Development of Molecular Digital Twins Based on Ambient Ionization Mass Spectrometry Imaging for Real-Time Application in Oncological Surgery

Yanis Zirem, Léa Ledoux, Nina Ogrinc…·Isabelle Fournier

The paper develops a machine-learning pipeline using mass spectrometry imaging to create molecular digital twins for real-time oncological surgery, enabling precise tumor margin delineation and bacterial strain prediction.

DOI 10.1101/2024.12.08.627387

𝕏 PostBluesky