Author

Manuel Saiselet

Université Libre de Bruxelles

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Cancer Biology· 2 Genomics· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:clustering· 2 Research Focus:differential expression· 2 Organism:human· 2 Assay:spatial transcriptomics· 2 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Approach:deep learning· 1

Frequent Co-Authors

Joel Rodrigues VitóriaiD· 3 shared Vincent DetoursiD· 3 shared Adrien TourneuriD· 2 shared Carine Maenhaut· 2 shared Denis LarsimontiD· 2 shared Ligia CraciuniD· 2 shared Akeila BellahcèneiD· 1 shared Alex SpinetteiD· 1 shared

Activity by Year

2020-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 32 mutual co-author links

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3 shared papersCancer Biology

Joel Rodrigues VitóriaORCID

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3 papers

Recent·Most cited

Cancer BiologyMolecular OncologyPeer-reviewedAug 11, 2026

Idiosyncratic and generic single nuclei and spatial transcriptional patterns in papillary and anaplastic thyroid cancers

Adrien Tourneur, Joel Rodrigues Vitória, Manuel Saiselet…·Vincent Detours

This study uses single nuclei RNA-seq and spatial transcriptomics to analyze transcriptional patterns in papillary and anaplastic thyroid cancers, revealing idiosyncratic and generic transcriptional variations and EMT-related features.

2 citations

humanscRNA-seq

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Cancer BiologybioRxivPreprintJul 7, 2025

Glycation Stress-Driven Transcriptomic Signature Predicts Survival Benefit from Adjuvant Gemcitabine in Resectable Pancreatic Cancer.

Oier Azurmendi Senar, Kosta Stosic, Christelle Bouchart…·Jean-Luc Van-Laethem

The paper develops a 16-gene signature (MG-GEM) that predicts survival benefit from adjuvant gemcitabine in resectable pancreatic cancer based on glycation stress, outperforming existing signatures.

DOI 10.1101/2025.07.07.663493

humanbulk RNA-seq

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GenomicsJournal of Molecular Cell BiologyPeer-reviewedJun 15, 2020

Transcriptional output, cell types densities and normalization in spatial transcriptomics

Manuel Saiselet, Joel Rodrigues Vitória, Adrien Tourneur…·Vincent Detours

The paper shows that total read counts in spatial transcriptomics spots reflect cell numbers and biology, and that normalization by total read counts can distort cell-type-related expression.

65 citations

spatial transcriptomicsstatistical model

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