Jonathan A. Rink

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.

This paper creates a multimodal single-cell atlas of the human basal ganglia, revealing epigenomic and 3D genome features across cell types and linking them to disease-associated genetic risk.

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.

This paper presents a single-cell multiome atlas of the human basal ganglia, linking chromatin states and transcriptomes to cell-type identity and disease-associated variants.

The paper creates a single-cell atlas of transcription and chromatin states in the human brain, identifying regulatory programs and linking them to neuropsychiatric disorders.

The paper presents an integrated single-cell and epigenomic resource for exploring basal ganglia datasets across species, enabling multi-omics and comparative analysis.

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 generates a single-cell DNA methylome and 3D multi-omic atlas of the adult mouse brain, identifying methylation patterns and regulatory networks across cell types and brain regions.

The paper links single-cell epigenomes and projection patterns of 33,034 mouse neurons to identify transcriptomic and epigenomic properties of projection cell types.

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.