SenPred: a single-cell RNA sequencing-based machine learning pipeline to classify deeply senescent dermal fibroblast cells for the detection of an in vivo senescent cell burden - Hughes, Bethany K.; Davis, Andrew; Milligan, Deborah; Wallis, Ryan; Mossa, Federica; Philpott, Michael P.; Wainwright, Linda J.; Gunn, David A.; Bishop, Cleo L. (Genome medicine, 2025)
Keywords: 3D organotypic culture; Age; Analysis; Antibiotics; Bioinformatics; Biomedical and Life Sciences; Biomedicine; Cancer Research; Cell cycle; Cellular Senescence - genetics; Classification; Datasets; Fibroblasts; Fibroblasts - cytology; Fibroblasts - metabolism; Genomics; Human Genetics; Humans; Humidity; Immunofluorescence; In vivo senescence detection; Learning algorithms; Living skin equivalent; Machine Learning; Medicine/Public Health; Metabolomics; Morphology; Pipe lines; Pipelines; RNA; RNA sequencing; RNA-Seq; scRNA-seq; Senescence; Sequence Analysis, RNA - methods; Single-Cell Analysis - methods; Skin; Skin - cytology; Systems Biology; Transcriptome; Transcriptomics; In vivo senescence detection; Living skin equivalent; 3D organotypic culture; scRNA-seq; Senescence; Machine learning