Csaba Kerepesi

The paper compares transcriptomic and proteomic estimates of sample-specific protein-protein interaction networks, finding similar size-adjusted characteristics and time-related trends but differing rates of change.

This study reprograms human dental pulp stem cells into neurons more rapidly and efficiently than fibroblasts, using a lentiviral vector and single-nucleus RNA sequencing to characterize the process.

This paper develops an inflammation-driven epigenetic clock to track disease progression and rejuvenation using DNA methylation data.

This study improves face age prediction by using multiple-angle photos, showing that combining front and side views enhances accuracy compared to single-view models.

The paper develops cell-type-specific transcriptomic aging clocks using single-nuclei RNA sequencing data from human prefrontal cortex tissue, showing distinct aging patterns across cell types.

This study develops CpGeneAge, a multi-omics aging clock combining epigenetic and transcriptomic features, showing improved interpretability and accuracy in age prediction.

This study examines how cardiorespiratory fitness affects epigenetic aging in different organs of rats, finding organ-specific and common changes in DNA methylation.

The paper uses face photos to predict mortality and shows that occupation affects age acceleration, with sports being the slowest aging occupation.

This study shows biological age can increase with stress and decrease with recovery, using epigenetic clocks in mice and humans.

The paper reanalyzes millions of molecular profiles to identify aging interventions using AI agents, finding over 500 interventions that reduce biological age and revealing patterns in aging modulation.

The paper shows that aging leads to increased intron retention and spurious splicing, causing transcriptome deterioration across multiple human tissues.

This study introduces scAge, a probabilistic method to estimate epigenetic age in single cells, validated in mice, showing cell-level aging heterogeneity and rejuvenation events.

The paper introduces TIME-Seq, a low-cost method for epigenetic age prediction, and validates it on mouse and human samples, showing improved scalability and accuracy.

The paper uses epigenetic clocks to show rejuvenation during early mouse and human embryogenesis followed by aging.