Computational Biomedicine

Description of the 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. The ultimate goal is to improve the diagnosis, prognosis and treatment of complex diseases, such as diabetes and cancer.

While modern biotechnologies have enabled large-scale measurements of molecular events in health and disease, the experimental data alone are not sufficient for understanding the complex disease processes. Instead, computational methods and models are needed that can effectively integrate and analyse the experimental data so that meaningful interpretations can be made. Accordingly, mathematical modelling has become a central part of molecular biology and medicine as well as development of treatment and diagnosis strategies.

We have developed data integration and data-driven optimization approaches to improve the detection of reliable molecular markers and their interaction partners in global molecular networks. The eventual goal is to develop an integrative network-based modelling approach that can explain the observations as dynamic interaction networks and reveal the key molecular components and mechanisms underlying disease pathogenesis in a robust and unbiased manner.

Group leader

Laura Elo, Ph.D., Adjunct Professor in Biomathematics
Research Director in Bioinformatics
laura.elo[at] or laura.elo[at]

Research Coordinator

Anu Kukkonen-Macchi, Ph.D.
E-mail: bioinformatics-coordinator[at]
E-mail: anukuk[at]
Phone: +358 (0)29 450 3796

Contact information

Medical Bioinformatics Centre

Turku Centre for Biotechnology
Tykistökatu 6A, Biocity, 7th floor
FI-20520 Turku

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We have received funding from European Research Council (ERC), JDRF, Horizon 2020, Sigrid Jusélius Foundation, Academy of Finland, Päivikki and Sakari Sohlberg Foundation, Yrjö Jahnsson Foundation, Diabetes Research Foundation, Otto A. Malm Foundation, K. Albin Johansson Foundation, CIMO and University of Turku Graduate School (UTUGS)



Marie Sklodowska-Curie Innovative Training Network

The mission of ENLIGHT-TEN is to provide cross-disciplinary training in T cell immunology and big data analysis in order to train a new generation of researchers to exploit the power of emerging technological platforms.