Computational Biology Group
School of Biosciences
University of Kent
Kent, UK


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Welcome to the Computational Biology Group at the University of Kent.

The group is lead by Mark Wass and extensively collaborates with the Michaelis group to perform combined computational and wet laboratory research

Our research focusses on:

  • Investigating acquired resistance to anti-cancer drugs
    • Acquired resistance to anti-cancer drugs is a common problem in the treatment of cancer, with patients initally responding to treatment, only for their tumour to develop resistance and stop responding to treatment. We collaborate with Prof Martin Michaelis to use the Resistant Cancer Cell Line (RCCL) collection to identify both mechanisms and biomarkers of acquired resistance.
  • Identifying biomarkers for drug sensitivty in cancer
    • A number of recent large scale studies, inclding the Cancer Cell Line Encyclopedia (CCLE) and the Genomics of Drug Sensitivity in Cancer (GDSC), have consdiered generated extensive sets of drug senstiity in cancer cell lines with associated omics profiling. We are interested in mining these resources to further advance our understanding of how genetic and epi-genetic factors influcence drug sensitivity in cancer
  • Core bioinformaticsThe development of novel methods for:
    • The inference of gene and protein function
    • The prediction of protein structure
    • The identification of protein-protein interactions and their interface sites
    • The modelling of small molecule binding sites in proteins
    • Assessing the functional effects of single nucleotide variants
  • While most of our research focuses on cancer we also apply the novel methods we develop to other areas:
    • Investigating the molecular determinants of Ebola virus pathogenicity
    • Investigating myosin evolution and selective pressures based on phenotype
    • Investigating the genetic causes of human disease - with a recent focus on Cystinuria
Full details of our research, publications, lab members and resources are available on the relevant pages.