Recent biomedical research has shown that phenotype of living organisms depends on complex interdependent mechanisms, deriving not only from genotype and environment, but also from a large set of interactions modifying gene expression without alteration of the DNA sequence, a phenomenon called Epigenetics.
Links to epigenetic "signatures", such as DNA methylation, histone modification and changes in chromatin, have been established in cancer, in autoimmune and neuropsychiatric disorders, in response to stress and also in the ageing process. Epigenetic signatures often match to differential or abnormal gene expression profiles, with epigenetically-triggered silencing, or over-expression of genes, described in recent work.
Of particular interest are epigenetic phenomena and related molecular features, which occur during very early stages of disease initiation, since understanding these improves potential for developing strategies for early diagnosis.
Complex interactions exist between DNA methylation and histone modifications, while the respective epigenetic changes have different dynamics and stability.
The specific project is to develop a hybridised multi-layer model (accounting for different scales), to directly represent known epigenetic mechanisms and interactions, to extend this to a system-wide basis by parallel implementation and to use data sources and supporting analyses to validate assumptions.
Our work on Epigenetics consists on four investigative strands, namely development of:
- an epigenetic signature level micro-model;
- a representation of infection-induced aberrant DNA methylation in gastric cells, (developed in collaboration with the National Cancer Center (Tokyo, Japan), and used as a proof of concept);
- StatEpigen database, a novel knowledge management system for genetic and epigenetic molecular determinants of cancer;
- a network-based model for micro-molecular events observed at different stages of colon cancer, with a focus on the gene relationships and tumour pathways.
Selected Group Publications
Roznovat, I.A. and Ruskin, H.J., A Computational Model for Genetic and Epigenetic Signals in Colon Cancer, Interdisciplinary Sciences: Computational Life Sciences, 5 (3), pp. 175 - 186, 2013. Springer Berlin Heidelberg. DOI: 10.1007/s12539-013-0172-y.
Roznovăţ, I. and Ruskin, H.J., (2012), A Computational Model for Genetic and Epigenetic Signals in Colon Cancer, Proceedings of the 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW), Philadelphia, USA, 4th-7th October 2012, pp. 188 - 195. doi 10.1109/BIBMW.2012.6470302.
Shakya, K., O'Connell, M.J. and Ruskin, H. J., (2012), The landscape for epigenetic/epigenomic biomedical resources, Epigenetics, 7 (9): 982 – 986.
Barat, A. and Ruskin, H.J., (2010), A Manually Curated Novel Knowledge Management System for Genetic and Epigenetic Molecular Determinants of Colon Cancer, The Open Colorectal Cancer Journal, 3, 36-46.
Perrin, D., Ruskin, H. J. and Niwa, T., (2010), Cell type-dependent, infection-induced, aberrant DNA methylation in gastric cancer. Journal of Theoretical Biology 264(2):570–577.
Raghavan, K., Ruskin, H.J., Perrin, D., Goasmat, F., and Burns, J., (2010), Computational Micromodel for Epigenetic Mechanisms., PLoS ONE 5(11): e14031.