Yaroslav Markov

This study evaluates the technical and biological reliability of 18 epigenetic clocks and shows that technical reliability does not predict biological reliability, which is critical for clinical applications.

BrainBridge integrates single-cell transcriptomic data with phenotypes to model brain biology, prioritizing genes and cell types linked to Alzheimer's, aging, and sex differences.

This paper investigates how APOEe4 influences molecular changes in Alzheimer's disease through proteomic, epigenetic, and genetic analyses of post-mortem brain samples, identifying key proteins and epigenetic markers associated with risk and resilience.

TranslAGE provides a standardized framework for benchmarking epigenetic aging biomarkers by harmonizing datasets and precomputing scores across multiple performance domains.

The paper develops 11 system-specific methylation clocks from blood samples to quantify aging heterogeneity across physiological systems and identifies aging subtypes with distinct disease patterns.

This study evaluates the responsiveness of DNA methylation aging biomarkers across 51 longevity interventions, identifying factors influencing their response and highlighting the utility of explainable clocks.

This study improves the reliability of stochastic epigenetic mutations (SEMs) by filtering technical noise and identifies their associations with cardiovascular disease and aging.