… the vast majority based on … epigenetic clocks using deep learning. First, we gathered 142
publicly available data sets from several human tissues to develop AltumAge, a neural network …

… the vast majority based on … epigenetic clocks using deep learning. First, we gathered 142
publicly available data sets from several human tissues to develop AltumAge, a neural network …

… the vast majority based on … epigenetic clocks using deep learning. First, we gathered 143
publicly available data sets from several human tissues to develop AltumAge, a neural network …

… machine learning model to find out the biological meaning behind these DNA methylation
age … In this study, we have designed an epigenetic clock using the DNA methylation levels of …

… age and correlations between “DNA methylation age” and … epigenetic age predictors, the
Horvath pan-tissue epigenetic … is an expected characteristic of any machine learning approach. …

… age predictors called epigenetic clocks can accurately estimate the biological age of an
individual based on cellular DNA methylation, … Similarly to the analysis of the pan-tissue cohort, …

… epigenetic age and chronological age. It is considered that the pan-tissue DNA methylation
clock … bulk data, allowing robust aging prediction based on accumulated genomic stress. …

… To better construct a pan-tissue epigenetic clock with high prediction accuracy, the datasets
… with existing epigenetic clocks developed based on elastic network and other deep learning …

… of age predictors utilising DNA methylation have been developed, referred to as epigenetic
clocks. … The first multi-tissue age predictor (referred to as the Horvath or Pan-Tissue clock) …

… Here, we present a compact epigenetic clock for blood, which outperforms state-of… clock to
sequencing-based data, with far-reaching implications for a better understanding of epigenetic …