Hamid Reza Rezvani

SpaceBlocks is a workflow for reproducible, expert-supervised spatial transcriptomics analysis across platforms, identifying new cell types and differentially expressed genes in multiple datasets.

This study uses spatial and bulk transcriptomics to map cSCC progression, identifies stage-specific gene programs, and finds prognostic biomarkers relevant across cancers.

This study identifies a type I interferon signaling signature in XPC-deficient keratinocytes, linking UVB exposure to JAK/STAT pathway dysregulation and hypersensitivity.

This paper generates and characterizes CRISPR-Cas9-mediated XPC gene knockout in human skin cells to model XP-C disease and study its phenotypes and molecular mechanisms.