Nuclear morphology is a deep learning biomarker of cellular senescence
2022 · Nature Aging · 195 citations
https://doi.org/10.1038/s43587-022-00263-3
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Indra Heckenbach
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Indra Heckenbach is an academic researcher from University of Copenhagen. The author has contributed to research in topics: Telomeres, Telomerase, and Senescence & Genetics, Aging, and Longevity in Model Organisms & Sirtuins and Resveratrol in Medicine. The author has an h-index of 10, co-authored 29 publications.
ORCID: 0000-0001-7038-4677Papers by this author
worksSpatial mapping of cellular senescence: emerging challenges and opportunities
2023 · Nature Aging · 109 citations
https://doi.org/10.1038/s43587-023-00446-6
Histone malonylation is regulated by SIRT5 and KAT2A
2023 · iScience · 29 citations
https://doi.org/10.1016/j.isci.2023.106193
Effect of nicotinamide riboside on airway inflammation in COPD: a randomized, placebo-controlled trial
2024 · Nature Aging · 25 citations
https://doi.org/10.1038/s43587-024-00758-1
Deep learning assessment of senescence-associated nuclear morphologies in mammary tissue from healthy female donors to predict future risk of breast cancer: a retrospective cohort study
2024 · The Lancet Digital Health · 11 citations
https://doi.org/10.1016/s2589-7500(24)00150-x
Cellular senescence predicts breast cancer risk from benign breast disease biopsy images
2025 · Breast Cancer Research · 1 citations
https://doi.org/10.1186/s13058-025-01993-z
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