The aging process results in multiple traceable footprints, which can be quantified and used
to estimate an organism's age. Examples of such aging biomarkers include epigenetic …

The search for reliable indicators of biological age, rather than chronological age, has been
ongoing for over three decades, and until recently, largely without success. Advances in the …

Age is the key risk factor for diseases and disabilities of the elderly. Efforts to tackle age-
related diseases and increase healthspan have suggested targeting the ageing process …

First published in 2016, predictors of chronological and biological age developed using
deep learning (DL) are rapidly gaining popularity in the aging research community. These …

Aging clocks dissociate biological from chronological age. The estimation of biological age
is important for identifying gerontogenes and assessing environmental, nutritional, or …

Modern machine learning techniques (such as deep learning) offer immense opportunities
in the field of human biological aging research. Aging is a complex process, experienced by …

Individuals of the same age may not age at the same rate. Quantitative biomarkers of aging
are valuable tools to measure physiological age, assess the extent of 'healthy aging', and …

The identification of genes and interventions that slow or reverse aging is hampered by the
lack of non-invasive metrics that can predict the life expectancy of pre-clinical models. Frailty …

Advanced age is the main common risk factor for cancer, cardiovascular disease and
neurodegeneration. Yet, more is known about the molecular basis of any of these groups of …

Epigenetic alterations are a hallmark of aging and age‐related diseases. Computational
models using DNA methylation data can create “epigenetic clocks” which are proposed to …