Computational melanoma genomics (Masters option available)

Computational melanoma genomics (Masters option available)

Project details

Building on exciting new findings about the evolution of lethal melanoma melanoma (Vergara et al, under review), this project will use a variety of melanoma genomics datasets including whole genome, exome, gene expression and methylation data to further refine our understanding of melanoma sub-clonality and how melanoma evolves to a lethal stage. Better understanding of melanoma progression will contribute to the development of prognostic tests of patient outcome, and also has the potential to identify new therapy targets.

About our research group

We  apply mathematics, statistics and computing to make sense of genomics data from human disease, especially related to the evolution of cancer. 

Our major research interests are: 

1. Cancer evolution, including 

  • Complex genomic rearrangements 
  • Formation and evolution of cancer neochromosomes 
  • Melanoma progression 

2. Bioinformatics methods development, including 

  • Identification and classification of genomic rearrangements 

3. Translational bioinformatics, including 

  • Rare cancers 
  • Bioinformatics tools for clinical cancer genomics


Professor Tony Papenfuss

Tony Papenfuss
Laboratory Head; Leader, Computational Biology Theme
Ismael Vergara
Bioinformatics division

Project Type: