Harnessing the power of data and models to study life
Life is one of the most complex systems to study as it encompasses a multitude of interacting levels. These scale from the interacting atoms to the essential molecules, genes and proteins up to the interactions between cells, tissues, organisms and between organisms and their environment. In addition to this, living systems are typically spatially structured and very dynamic.
Examples are the propagation of nerve pulses along axons, and the intricate patterning processes occurring during multicellular development. Bioinformatics is used to analyse the multitude of biological 'big data' that originate from observations and experiments investigating living matter. Biocomplexity researchers develop mathematical and computational models to simulate these processes and thereby unravel the building blocks and interactions responsible for the observed dynamic behaviour. Therefore both bioinformatics and biocomplexity research are core to research in the life sciences, making it a very interdisciplinary trade.
Bioinformaticians and biocomplexity scientists can be found in many different laboratories, such as in the hospital to discover novel genes that cause a particular disease. Or, at research institutes and companies that study novel drug targets, explore ecological models or improve crop yield.
Interdisciplinary programme
This Master's programme will bring together the intricate worlds of biology, computer and data sciences. Our programme is broad and interdisciplinary and involves the input from many Utrecht faculties and research institutes such as the Faculty of Science, the Hubrecht Institute, University Medical Centre Utrecht and the Princess Máxima Center for Pediatric Oncology (for more information, see Utrecht Bioinformatics Center). Hence we can offer a wide variety of internships and projects, allowing the choice of a favoured research topic, which can be in a medical research area, for example in cancer genomics, or a more fundamental area such as modelling of complex biological systems.
