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Dr Mark Wass

Senior Lecturer in Computational Biology

School of Biosciences


Mark joined the School of Biosciences in October 2012. He obtained his first degree in Natural Sciences at Cambridge University in 2000 followed by a Masters in Computing at Imperial College London. After a few years working in Industry as an IT consultant Mark studied for a PhD with Prof Mike Sternberg at Imperial (2004-2008) and continued onto a post-doctoral position in the group until 2011. In 2011 Mark was awarded a FEBS Long Term Fellowship to work in the group of Alfonso Valencia at the CNIO (Spanish National Cancer Research Centre, Madrid, Spain).

Mark's research interests are in Structural Bioinformatics particularly the analysis and prediction of protein function, structure and interactions. He is also interested in using such approaches to analyse genetic variation and identify the functional effects that are associated with disease.

Mark is a member of the Cytogenomics and Bioinformatics Group.

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Also view these in the Kent Academic Repository

Kelley, L. et al. (2015). The Phyre2 web portal for protein modeling, prediction and analysis. Nature protocols [Online] 10:845-58.
Michaelis, M. et al. (2015). Identification of flubendazole as potential anti-neuroblastoma compound in a large cell line screen. Scientific reports [Online] 5:8202.
Wass, M. et al. (2014). The automated function prediction SIG looks back at 2013 and prepares for 2014. Bioinformatics [Online] 30:2091-2092.
Pappalardo, M. and Wass, M. (2014). VarMod: modelling the functional effects of non-synonymous variants. Nucleic Acids Research [Online] 42:W331-W336.
Radivojac, P. et al. (2013). A large-scale evaluation of computational protein function prediction. Nature Methods [Online] 10:221-227.
Wass, M. et al. (2012). Proteomic analysis of Plasmodium in the mosquito: progress and pitfalls. Parasitology [Online] 139:1131-1145.
David, A. et al. (2012). Protein-protein interaction sites are hot spots for disease-associated nonsynonymous SNPs. Human Mutation [Online] 33:359-363.
Wass, M., Barton, G. and Sternberg, M. (2012). CombFunc: predicting protein function using heterogeneous data sources. Nucleic Acids Research [Online] 40:W466-W470.
Wass, M. et al. (2011). Towards the prediction of protein interaction partners using physical docking. Molecular Systems Biology [Online] 7.
Chambers, J. et al. (2011). Genome-wide association study identifies loci influencing concentrations of liver enzymes in plasma. Nature Genetics [Online] 43:1131-1138.
Wass, M., David, A. and Sternberg, M. (2011). Challenges for the prediction of macromolecular interactions. Current Opinion in Structural Biology [Online] 21:382-90.
Chambers, J. et al. (2010). Genetic variation in SCN10A influences cardiac conduction. Nature Genetics [Online] 42:149-152.
Sinden, R. et al. (2010). The flagellum in malarial parasites. Current Opinion in Microbiology [Online] 13:491-500.
Wass, M., Kelley, L. and Sternberg, M. (2010). 3DLigandSite: predicting ligand-binding sites using similar structures. Nucleic Acids Research [Online] 38:W469-W473.
Chambers, J. et al. (2010). Genetic loci influencing kidney function and chronic kidney disease. Nature Genetics 42:373-5.
Chambers, J. et al. (2009). Genome-wide association study identifies variants in TMPRSS6 associated with hemoglobin levels. Nature Genetics [Online] 41:1170-1172.
Wass, M. and Sternberg, M. (2009). Prediction of ligand binding sites using homologous structures and conservation at CASP8. Proteins:Structure, Function, and Genetics [Online] 77 Sup:147-151.
Wass, M. and Sternberg, M. (2008). ConFunc--functional annotation in the twilight zone. Bioinformatics [Online] 24:798-806.
Gherardini, P. et al. (2007). Convergent evolution of enzyme active sites is not a rare phenomenon. Journal of Molecular Biology [Online] 372:817-845.
Total publications in KAR: 19 [See all in KAR]


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My research is primarily based in protein bioinformatics. I have developed methods for the prediction of protein function (ConFunc and CombFunc – webserver at ) and for the prediction of small molecule binding sites in proteins (3DLigandSite - Recent research has demonstrated the ability to use protein-protein docking tools to predict interactions between proteins. I am increasingly interested in using structural bioinformatics tools to analyse genetic variation and the functional effects that they may have in disease. To pursue this I have collaborated with a number of genome wide association and sequencing studies.

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Enquiries: Phone: +44 (0)1227 823743

School of Biosciences, University of Kent, Canterbury, Kent, CT2 7NJ

Last Updated: 29/09/2015