Alena Kalyakulina

EpImAge combines epigenetic and immunological markers to predict biological age with high accuracy, showing sensitivity to multiple diseases.

This study performs a meta-analysis of epigenetic age acceleration across 93 datasets and 23K samples, highlighting geographic, ethnic, and gender differences in aging rates.

The paper develops a small immunological age clock model called SImAge using 10 biomarkers, achieving high accuracy with a deep neural network.

This study examines epigenetic age acceleration and adaptation mechanisms in the Yakutian population using DNA methylation data, finding higher age acceleration and region-specific methylation patterns related to climate adaptation and aging.

This study shows CKD patients have accelerated aging linked to inflammation, using DNA methylation and protein biomarkers.

The paper models mitochondrial polymorphisms as co-mutation networks in three high-altitude populations to identify functionally enriched genetic interactions associated with high-altitude adaptation.

The paper presents a method for classifying healthy individuals and patients using whole blood DNA methylation data, including data harmonization, imputation, and XAI for model explanation.

This study identifies age-associated DNA methylation changes in Alzheimer's disease, showing accelerated epigenetic aging but no significant sex interaction.

The paper analyzes mitochondrial genome co-occurrence networks in Asian populations at different altitudes to understand high altitude adaptation mechanisms.

The paper assesses sex-specific DNA methylation changes with aging using whole blood datasets, finding 43% of sex-associated probes show age-related methylation changes and higher methylation variability in males.