Marcus Naymik

The paper uses pseudotime analysis on bulk RNA-seq data from Alzheimer's disease brains to identify conserved and region-specific molecular programs across nine brain regions.

This study performs a phenome-wide association analysis of APOE alleles in the All of Us Research Program, identifying significant associations with various health outcomes and highlighting sex and ancestry differences.

This study uses whole genome sequencing and AI to identify genetic variants associated with TDP43-Type-C neurodegeneration, finding novel links to FIG4, UBQLN2, INPP5A, and ANXA11.

GEM, an AI-based tool, ranks causal genes highly for rare genetic diseases, improving diagnostic efficiency and reducing manual effort.

This study profiles RNA expression in MSA cerebellar tissue, identifying distinct transcriptional signatures between parkinsonian and cerebellar subtypes, with greater dysregulation observed in the cerebellar subtype.

The paper identifies genes associated with Rett syndrome-like (RTT-L) phenotype through whole exome sequencing and protein-protein interaction network analysis, revealing shared pathways with classical Rett syndrome.