Author

Michael D. Mueller

University of Bern

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

Biology Disciplines

Click to filter author papers

Molecular Biology· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

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

Angelo DuòiD· 1 shared 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 Peter Nestorov· 1 shared

Activity by Year

2024-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

1 shared paperMolecular Biology

Angelo DuòORCID

Mutual co-authors in cluster

Author profile →

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