Author

M. Ben Ezra

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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Physiology· 2 Cell Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 3 Research Focus:differential expression· 2 Organism:human· 2 Organism:mouse· 2 Assay:bulk RNA-seq· 1 Research Focus:cell-cell communication· 1 Research Focus:chromatin & epigenetic regulation· 1 Approach:deep learning· 1

Frequent Co-Authors

I. Heckenbach· 3 shared M. Scheibye-Knudsen· 3 shared L. H. Mortensen· 2 shared M. A. Petr· 2 shared A. A. Teklu· 1 shared B. Fink· 1 shared B. Osborne· 1 shared D. Bakula· 1 shared

Activity by Year

2021-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 31 mutual co-author links

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3 shared papersPhysiology

I. Heckenbach

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Author profile →

3 papers

Recent·Most cited

The human pathome shows sex specific aging patterns post-development

M. Ben Ezra, J. B. Garbrecht, N. Rasmussen, I. Heckenbach, M. A. Petr, D. J. Bakula, L. H. Mortensen, M. Scheibye-Knudsen

The paper analyzes histological data to identify age- and mortality-associated features, revealing sex-specific aging patterns and suggesting nintedanib as a potential aging intervention.

bioRxiv · Feb 27, 2023 · PreprintPhysiology

Ketones facilitate transcriptional resolution of secondary DNA structures in premature aging

M. A. Petr, L. M. Carmona-Marin, T. Tulika, S. Kristensen, S. Reves, D. Bakula, G. Keijzers, B. Osborne, S. J. Mitchell, S. Hamilton, J. Kato, I. Alfaras, A. A. Teklu, I. Heckenbach, J. Madsen, , M. Scheibye-Knudsen

This study shows that ketones like beta-hydroxybutyrate reduce premature aging features in Cockayne syndrome models by enhancing transcriptional readthrough of DNA secondary structures through histone acetylation.

bioRxiv · Mar 8, 2022 · PreprintPhysiology

Deep Learning Shows Cellular Senescence Is a Barrier to Cancer Development

I. Heckenbach, M. Ben Ezra, G. V. Mkrtchyan, J. S. Madsen, M. H. Nielsen, D. Oro, L. H. Mortensen, E. Verdin, R. Westendorp, M. Scheibye-Knudsen

This study uses deep learning to predict cellular senescence from cell morphology and finds higher senescence rates correlate with lower cancer incidence.

bioRxiv · Mar 18, 2021Cell Biology