Over the past decade, epigenetic clocks have emerged as powerful machine learning tools,
not only to estimate chronological and biological age but also to assess the efficacy of anti …

Deciphering cell-type heterogeneity is crucial for systematically understanding tissue
homeostasis and its dysregulation in diseases. Computational deconvolution is an efficient …

DNA methylation is a fundamental epigenetic mark that governs gene expression and
chromatin organization, thus providing a window into cellular identity and developmental …

Bulk-tissue DNA methylomes represent an average over many different cell types,
hampering our understanding of cell-type-specific contributions to disease development. As …

Background DNA methylation changes with age. Chronological age predictors built from
DNA methylation are termed 'epigenetic clocks'. The deviation of predicted age from the …

Tobacco use is a major modifiable risk factor for adverse health outcomes, including cancer,
and elicits profound epigenetic changes thought to be associated with long-term cancer risk …

An outstanding challenge of epigenome-wide association studies (EWASs) performed in
complex tissues is the identification of the specific cell type (s) responsible for the observed …

Aging is a significant risk factor for various human disorders, and DNA methylation clocks
have emerged as powerful tools for estimating biological age and predicting health‐related …

Background Changes in cell-type composition of tissues are associated with a wide range of
diseases and environmental risk factors and may be causally implicated in disease …

Background DNA methylation changes that accrue in the stem cell pool of an adult tissue in
line with the cumulative number of cell divisions may contribute to the observed variation in …