Michael Kleyman

The paper links chronic pain genetic variants to dorsal horn neuron subtypes using multi-species single-cell and spatial transcriptomic analyses.

The paper introduces a machine learning method to predict tissue-specific regulatory conservation by analyzing open chromatin patterns across mammals, showing improved performance over nucleotide alignment-based approaches.

The paper identifies addiction-associated genetic variants in brain cell type- and region-specific cis-regulatory elements using GWAS and machine learning.

This study identifies molecularly distinct medium spiny neuron types in the primate striatum, revealing new subtypes associated with specific anatomical compartments and functional roles.