Ryo Nakaki

This study predicts biological age and clinical biomarkers from cheek mucosa DNA methylation data, showing high accuracy for age and multiple biomarkers compared to blood-derived data.

The paper develops a pseudo-longitudinal framework to estimate a buccal PACE-like aging-rate score from cross-sectional DNA methylation data, showing moderate reproducibility but limited correlation with blood-derived DunedinPACE.

This paper calibrates epigenetic age between EPICv2 and MSA arrays using linear regression models to reduce cross-platform differences in six epigenetic clocks.

This paper introduces temporal entropy as a measure of dynamic instability to improve psychiatric classification across cohorts using blood transcriptomic data, finding that excluding individuals with unstable transcriptomic dynamics enhances classification performance.

The paper introduces an incremental batch effect correction framework for DNA methylation data, allowing new data to be corrected without reprocessing existing data.

The paper develops Transfer Elastic Net, a transfer learning method to create epigenetic clocks for the Japanese population with smaller sample sizes, achieving lower prediction errors than existing models.