Medical research, and the molecular biology that it relies on, can be advanced in many ways using theoretical and computational approaches, mostly by harnessing the power of small and big data generated by experimental methods. Regenerative medicine and personal genomics will be two of the most exciting growth areas in the coming decade. Our research group has expertise spanning scales of biology from DNA, proteins, interactions, networks, cells, etc. up to whole organism phenotypes; we join these together to create innovative technologies and advance scientific knowledge in areas including regenerative medicine and personal genomics.
We are contributing to the field of cell reprogramming by predicting factors for human cell differentiation and to the field of human genetics by predicting phenotypic effects of genetic variation through causal molecular biology. To achieve this our group requires a range of biological and computational backgrounds, and we work closely with industry and biotech start-ups to translate our basic research into practise.
Selected Papers
- Rackham, O.J.L., Firas, J., Fang, H.,Oates, M.E., Holmes, M.L., Knaupp, A.S., The FANTOM Consortium, Suzuki, H.,Nefzger, C.M., Daub, C.O., Shin, J.W., Petretto, E.P., Forrest, A.R.R., Hayashizaki, Y., Polo, J.M. and Gough, J. (2016)
A predictive computational framework for direct reprogramming between human cell types
Nature Genetics 43(3): 331-335 - Vavoulis, D.V., Francescatto, M., Heutink, P. and Gough, J. (2015)
DGEclust: differential expression analysis of clustered count data
Genome Biology 16(39): 1-18 - Smithers, B., Oates, M.E. and Gough, J. (2015)
Splice junctions are constrained by protein disorder
Nucl. Acids Res. 43(10): 4814-22 - Sardar, A.J., Oates, M.E., Fang, H., Forrest, A.R.R., Kawaji, H., The FANTOM consortium, Gough, J. and Rackham, O. (2014)
The Evolution of Human Cells in Terms of Protein Innovation
Mol. Biol. Evol. 31(6): 1364-74 - Mitchell, A. et al. (2014)
The InterPro protein families database: the classification resource after 15 years
Nucl. Acids Res. 43: D213-221 - Oates, M.E., Romero, P., Takashi, I., Ghalwash, M., Mizianty, M.J., Xue, B., Dosztanyi, Z., Uversky, V.N., Obradovic, Z., Kurgan, L., Dunker, A.K. and Gough, J. (2013)
D2P2: Database of Disordered Protein Predictions
Nucl. Acids Res. 41: D508-D516 - Radivojac et al. (2013)
A large-scale evaluation of computational protein function prediction
Nature Methods 10: 221-227 - Shihab, H.A., Gough, J., Cooper, D.N., Barker, G.L.A., Edwards, K.J., Day, I.N.M., Gaunt, T. (2012)
Predicting the Functional, Molecular, and Phenotypic Consequences of Amino Acid Substitutions using Hidden Markov Models
Human mutation 34(1): 57-65
Group Members
- Ieva Berzanskyte
- Thea Fennell
- Alexey Murzin
- Himani Tandon
- Wencan Zhu