A machine learning approach identifies cellular senescence on transcriptome data of human cells in vitro.
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| Title: | A machine learning approach identifies cellular senescence on transcriptome data of human cells in vitro. |
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| Authors: | Mahmud S; Institute on the Biology of Aging and Metabolism, University of Minnesota, Twin Cities, Minneapolis, MN, 55455, USA.; Department of Genetics, Cell Biology and Development, University of Minnesota, Twin Cities, Minneapolis, MN, 55455, USA., Zheng C; Institute on the Biology of Aging and Metabolism, University of Minnesota, Twin Cities, Minneapolis, MN, 55455, USA.; Department of Genetics, Cell Biology and Development, University of Minnesota, Twin Cities, Minneapolis, MN, 55455, USA.; Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China., Santiago FE; Institute on the Biology of Aging and Metabolism, University of Minnesota, Twin Cities, Minneapolis, MN, 55455, USA.; Department of Biochemistry, Molecular Biology, and Biophysics, University of Minnesota Twin Cities, Minneapolis, MN, 55455, USA., Zhang L; Institute on the Biology of Aging and Metabolism, University of Minnesota, Twin Cities, Minneapolis, MN, 55455, USA.; Department of Biochemistry, Molecular Biology, and Biophysics, University of Minnesota Twin Cities, Minneapolis, MN, 55455, USA., Robbins PD; Institute on the Biology of Aging and Metabolism, University of Minnesota, Twin Cities, Minneapolis, MN, 55455, USA.; Department of Biochemistry, Molecular Biology, and Biophysics, University of Minnesota Twin Cities, Minneapolis, MN, 55455, USA., Dong X; Institute on the Biology of Aging and Metabolism, University of Minnesota, Twin Cities, Minneapolis, MN, 55455, USA. dong0265@umn.edu.; Department of Genetics, Cell Biology and Development, University of Minnesota, Twin Cities, Minneapolis, MN, 55455, USA. dong0265@umn.edu. |
| Source: | GeroScience [Geroscience] 2025 Jun; Vol. 47 (3), pp. 5287-5301. Date of Electronic Publication: 2024 Dec 30. |
| Publication Type: | Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't |
| Journal Info: | Publisher: Springer International Publishing Country of Publication: Switzerland NLM ID: 101686284 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2509-2723 (Electronic) Linking ISSN: 25092723 NLM ISO Abbreviation: Geroscience Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 2509-2723 |
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| DOI: | 10.1007/s11357-024-01485-6 |
