Health & Nutrition, Digitalisation
Computational Genetics and Epigenetics of Cancer
Our team focuses on developing statistical and machine learning approaches for biological data with the aim to understand the role of molecular modifications in cancer progression.
Our group aims at addressing the following questions:
- Determine the role of epigenetic remodeling in oncogenic transformation
- Investigate the consequences of somatic genomic alterations on the epigenetic landscape in cancer in these cancers
- Adjust methodology for studying genetic and epigenetic changes in cancer.
Our methodological research is centered on data integration and the development of high throughput data analysis methods, including machine learning, to study regulation in cancer with a special focus on epigenetic regulation and transcriptional heterogeneity.
The methods we develop should allow in the future for better stratification of cancer patients into good and poor prognosis cases. Our research will also suggest novel therapeutic solutions for cancer patients based on their molecular profiles and provide novel biomarkers for treatment response.