Author

Emanuel Soda

Human TechnopoleORCID 0000-0002-2301-6465Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Cancer Biology· 1 Genetic & Genomic Medicine· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Organism:human· 2 Assay:ATAC-seq· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Research Focus:dimensionality reduction· 1 Research Focus:drug response / drug discovery· 1 Assay:imaging· 1

Frequent Co-Authors

Alessia ViscontiiD· 1 shared Amir HosseiniiD· 1 shared Andrea Mario VerganiiD· 1 shared Antonello MaiiD· 1 shared Arianna LandiniiD· 1 shared Carlo Andrea PivatoiD· 1 shared Chiara SorianiiD· 1 shared Craig A. GlastonburyiD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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1 shared paperGenetic & Genomic Medicine

Alessia ViscontiORCID

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2 papers

Recent·Most cited

Cell cycle control of chromatin creates a therapeutic window for epigenetic therapy in tumors

Kourosh Hayatigolkhatmi, Riccardo Valzelli, Elena Ceccacci, Amir Hosseini, Oualid El Menna, Mauro Romanenghi, Isabella Pallavicini, Emanuel Soda, Ornella Ejlli, Emanuela Villa, Paolo Falvo, Pedro Vizán, Enrique Blanco, Sergi Aranda, Roxana Barkhordar, , Saverio Minucci

This paper shows that extending G1 phase in cancer cells creates a therapeutic window for epigenetic drugs, with LSD1 inhibition and CDK4/6 inhibition working synergistically to induce differentiation and improve survival in AML models.

bioRxiv · Sep 6, 2026 · PreprintCancer Biology

Hundreds of cardiac MRI traits derived using 3D diffusion autoencoders share a common genetic architecture

Sara Ometto, Soumick Chatterjee, Andrea Mario Vergani, Arianna Landini, Sodbo Sharapov, Edoardo Giacopuzzi, Alessia Visconti, Emanuele Bianchi, Federica Santonastaso, Emanuel Soda, F. Cisternino, Carlo Andrea Pivato, Francesca Ieva, Emanuele Di Angelantonio, Nicola Pirastu, Craig A. Glastonbury

This study uses 3D diffusion autoencoders to derive latent cardiac MRI phenotypes, finds they share a genetic basis with cardiometabolic traits, and shows predictive power for disease risk.

Nature Communications · Jun 29, 2026Peer-reviewedGenetic & Genomic Medicine