Nicholas D. Johnson

The paper constructs an integrative single-cell epigenomic atlas of the adult mouse brain, mapping chromatin states and gene regulatory programs across 100 cell subclasses.

The paper uses single-cell epigenomics to study brain aging in mice, finding heterochromatin instability and transcription factor dysfunction across multiple brain regions and cell types.

The paper maps epigenetic and spatial transcriptomic changes in aging mouse brain using single-cell multi-omic data and develops deep-learning models to predict age-related gene expression changes.

The paper examines age and sex effects on human cortical neurons using multiomic data, finding age-related changes in gene expression and DNA methylation, and sex differences in gene expression and X-inactivation escape.

The paper constructs a single-cell chromatin accessibility atlas of the human brain, identifies cell-type-specific regulatory elements, and develops models to predict regulatory function of disease risk variants.

The paper identifies 188 cell types in the human brain using single-cell DNA methylation and 3D genome data, and develops a tool to predict cell types based on methylation patterns.