Author

Angelo Duò

ORCID 0000-0002-4338-2497Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Assay:scRNA-seq· 1

Frequent Co-Authors

Brett David McKinnoniD· 1 shared Cinzia DonatoiD· 1 shared Dennis Goehlsdorf· 1 shared Hans C. BösmülleriD· 1 shared Jitka Skrabalova· 1 shared Lea DuempelmanniD· 1 shared Michael D. Mueller· 1 shared Peter Nestorov· 1 shared

Activity by Year

2024-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperMolecular Biology

Brett David McKinnonORCID

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1 paper

Recent·Most cited

Tracing Endometriosis: Coupling deeply phenotyped, single-cell based Endometrial Differences and AI for disease pathology and prediction

Lea Duempelmann, Shaoline Sheppard, Angelo Duò, Jitka Skrabalova, Brett David McKinnon, Thomas Andrieu, Dennis Goehlsdorf, Sukalp Muzumdar, Cinzia Donato, Ryan Lusby, Wiebke Solaß, Hans C. Bösmüller, Peter Nestorov, Michael D. Mueller

The paper creates a large single-cell endometrial atlas and uses AI to identify gene expression and receptor-ligand changes associated with endometriosis, developing predictive models for disease severity.

bioRxiv · Aug 9, 2024 · PreprintMolecular Biology