We develop and apply new bioinformatics methods to drive discoveries in cancer and translate these into improved outcomes for patients.
Our approach is to use mathematics, statistics and computing to make sense of omics data, especially related to cancer evolution spanning initiation, progression and outcome. The main focus of our computational biology research is rare cancers, melanoma and prostate cancer, but our methodological research is also relevant to cancer in general and other diseases.
We have a strong track record in developing methods for analysing genome sequencing data, especially associated with chromosomal rearrangements. A major focus of our research is now the development of new computational and machine learning tools to analyse large, complex multiomics datasets.