Author

M. Ayadi

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· 3

Signature Assays, Organisms & Methods

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

Frequent Co-Authors

R. Nicolle· 3 shared C. Neuzillet· 2 shared J. Cros· 2 shared J. Iovanna· 2 shared N. J. Dusetti· 2 shared Y. Blum· 2 shared A. Bardier-Dupas· 1 shared A. Brunel· 1 shared

Activity by Year

2020-2022 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 34 mutual co-author links

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3 shared papersCancer Biology

R. Nicolle

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3 papers

Recent·Most cited

PACpAInt: a deep learning approach to identify molecular subtypes of pancreatic adenocarcinoma on histology slides

C. Saillard, F. Delecourt, B. Schmauch, O. Moindrot, M. Svrcek, A. Bardier-Dupas, J.-F. Emile, M. Ayadi, V. Rebours, L. de Mestier, P. Hammel, C. Neuzillet, J.-B. Bachet, J. Iovanna, N. Dusetti, , J. Cros

PACpAInt uses deep learning to identify molecular subtypes of pancreatic adenocarcinoma on histology slides, revealing prognostic heterogeneity and novel subtypes.

bioRxiv · Jan 4, 2022 · PreprintCancer Biology

Translatome-based classification reveals a dual metabolic dependency of a new tumor subtype of pancreatic cancer.

S. Shin, R. Nicolle, C. Jean, R. Samain, M. Ayadi, J. Raffenne, A. Brunel, J. Solorzano, C. Neuzillet, C. Joffre, S. Rocchi, J. Iovanna, N. J. Dusetti, O. Larsson, S. Pyronnet, , Y. Martineau

The paper identifies a new pancreatic cancer subtype with low protein synthesis but high integrated stress response activation, linked to metabolic impairments and drug resistance.

bioRxiv · Dec 23, 2020Cancer Biology

Establishment of a pancreatic adenocarcinoma molecular gradient (PAMG) that predicts the clinical outcome of pancreatic cancer

R. Nicolle, Y. Blum, P. Duconseil, C. Vanbrugghe, N. Brandone, F. Poizat, J. Roques, M. Bigonnet, O. Gayet, M. Rubis, N. Elarouci, L. Armenoult, M. Ayadi, A. Dereynies, M. Giovannini, , N. J. Dusetti

This paper develops a transcriptomic gradient (PAMG) to predict pancreatic cancer aggressiveness and treatment response using patient-derived xenografts and clinical data.

bioRxiv · Mar 25, 2020Cancer Biology