Computational Biomedicine Research

We develop computational data analysis tools and mathematical modelling methods for analyzing and interpreting data generated by modern high-throughput biotechnologies, such as next-generation sequencing and mass spectrometry-based proteomics. A specific focus is on biomedical applications in close collaboration with experimental and clinical groups to enable robust and reproducible interpretation of the molecular as well as clinical data. Using statistical modelling and advanced machine learning techniques, we have, for instance, identified early markers for type 1 diabetes and developed several powerful computational models for predicting disease and treatment risks. Our ultimate goal is to improve the diagnosis, prognosis and treatment of complex diseases, such as diabetes and cancer.

Photo of Laura Elo

Professor and Research Director Laura Elo introducing bioinformatics.

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