Bioinformatics
Epigenetic Clocks
Reading biological age from your genome's methylation state — with greater precision than any chronological measure.
What we study
We train and validate epigenetic clock models on large-scale DNA methylation datasets spanning diverse populations, age groups, and disease states. Our clocks go beyond CpG sites to integrate chromatin accessibility and histone modification patterns — producing a richer biological age signal.
Why it matters
Chronological age is a poor proxy for how fast someone is actually ageing. Epigenetic clocks measure the biological age written into your cells' methylation state — a far more accurate predictor of disease risk, cognitive decline, and remaining healthspan than the year on your birth certificate.
Our approach
We combine transformer architectures with multi-tissue methylation arrays to build clocks that generalise across blood, saliva, and tissue biopsies. Continual retraining on incoming longitudinal data means our clocks improve with every cohort — and every intervention trial feeds new signal back into the model.
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