John M.S. Bartlett

This study identifies germline genetic variants influencing somatic mutation patterns in 2,642 cancer genomes across 39 cancer types.

This study characterizes mitochondrial genomes in 2,700 cancer patients across 37 types using whole-genome sequencing and RNA-seq, revealing mutational patterns, truncating mutations, and nuclear transfer of mitochondrial DNA.

The paper develops a prognostic model for pancreatic ductal adenocarcinoma using meta-analysis of transcriptomic data, identifying gene pairs associated with early mortality after surgery.

The paper compares whole-genome data from primary pancreatic cancer, xenografts, and organoids to assess genetic concordance across different models.

The paper introduces SIMMS, a method that identifies biomarkers by analyzing molecular data and biological networks, showing improved performance in predicting disease subtypes and outcomes.