John C. Connelly

Explainable machine learning relates histological to genomic pathology

This paper uses machine learning to predict genomic alterations from H&E images of liver tumors, revealing genotype-phenotype links and highlighting genetic background limitations.

Germline and somatic variation influence nuclear-mitochondrial crosstalk in tumourigenesis

This study investigates how germline and somatic genetic variations affect mitochondrial DNA content, mutation patterns, and gene expression in liver tumors across four mouse strains.

Strand-resolved mutagenicity of DNA damage and repair

The paper investigates how strand-asymmetric processes like replication and transcription influence DNA damage, repair, and mutagenesis, revealing mechanisms that shape cancer genome evolution.