Shohei Noma

The paper identifies novel cell states and molecular profiles in lupus patients using single-cell data, linking them to disease severity and treatment outcomes.

This study maps transcription start sites and active enhancers in Galleria mellonella larvae during fungal infection and treatment using LQ-ssCAGE.

The paper constructs a single-cell atlas of transcribed cis-regulatory elements in the human genome, revealing gene regulation patterns and trait-gene relationships across cell populations.

The paper identifies widespread transcription initiation at microsatellites across species and develops deep learning models to predict STR-associated transcription and its impact on disease variants.