The research at the Bioinformatics Unit focuses on developing computational data analysis tools and mathematical modelling methods for analyzing and interpreting data generated by modern high-throughput biotechnologies, such as microarrays, deep sequencing and mass-spectrometry-based proteomic assays.
A specific focus of the research is on biomedical applications in close collaboration with experimental and clinical groups. Although the high-throughput biotechnologies enable large-scale measurements of molecular events in health and disease, the experimental data alone are not sufficient for understanding the complex disease processes.
Therefore, the goal of our research is to enable robust and reproducible interpretation of the data. Building on our previous computational, statistical and network-based studies, we aim at establishing a computational framework that allows optimized integration and analysis of large-scale clinical and molecular data at multiple levels as well as heterogeneity between individuals.
The ultimate goal is to improve the diagnosis, prognosis and treatment of complex diseases, such as diabetes and cancer, by combining computational, experimental and clinical expertise.
More information at the Computational Biomedicine Group website.