Author

Melissa Da Silva

Centre National de la Recherche Scientifique

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· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Assay:spatial transcriptomics· 1

Frequent Co-Authors

Alice BlondeliD· 1 shared Aurélien de ReynièsiD· 1 shared Christian PfisteriD· 1 shared Clarice S. GroeneveldiD· 1 shared Clémentine Krucker· 1 shared Isabelle Bernard‐PierrotiD· 1 shared Jacqueline FontugneiD· 1 shared Maryam KarimiiD· 1 shared

Activity by Year

2025-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperCancer Biology

Alice BlondelORCID

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1 paper

Recent·Most cited

Deep Learning Bridges Histology and Transcriptomics to Predict Molecular Subtypes and Outcomes in Muscle-Invasive Bladder Cancer

Alice Blondel, Clémentine Krucker, Valentin Harter, Melissa Da Silva, Clarice S. Groeneveld, Aurélien de Reyniès, Maryam Karimi, Simone Benhamou, Isabelle Bernard‐Pierrot, Christian Pfister, Stéphane Culine, Yves Allory, Thomas Walter, Jacqueline Fontugne

This paper develops a deep learning model to predict molecular subtypes and outcomes in muscle-invasive bladder cancer using histopathological images instead of RNA sequencing.

bioRxiv · Oct 23, 2025 · PreprintCancer Biology