scAgeClock: a single-cell transcriptome-based human aging clock model using gated multi-head attention neural networks (opens in new tab)

Aging clock models have emerged as a crucial tool for measuring biological age, with significant implications for anti-aging interventions and disease risk assessment. However, human aging clock models that offer single-cell resolution and account for cell and tissue heterogeneities remain underdeveloped. This study introduces scAgeClock, a novel gated multi-head attention neural network-based single-cell aging clock model. Leveraging a large-scale dataset of over 16 million single-cell trans...