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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.
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.
This Master’s programme also encompasses the (sub)domains of Computational Biology, Systems Biology and Computational Life Sciences.
Tailor your own programme
This Master's programme will be a deep-dive in bioinformatic data analysis, modelling and simulating biocomplexity. In two years, you will learn the theoretical basis and fundamental techniques relevant for bioinformatics and/or biocomplexity. Additionally you will learn to apply, modify and redevelop these methods to answer complex biological research questions. We will use state of the art research directly from our community as the basis for our lectures, assignments and internships.
Data Sciences and this Master’s programme
Big data can be found almost everywhere, from banks to insurance companies. Also, bioinformatics and biocomplexity deal with big data. As such, there are similarities in general techniques like programming or machine learning that do not depend on domain-specific knowledge. On the other hand, answering the grand questions in biology - without exception - requires a solid understanding of a particular biology discipline, in addition to the analytical methods.
As a consequence, many of the techniques that are used in bioinformatics or biocomplexity, for example, in next-generation sequencing or in determining the evolutionary history of cells and organisms require highly specific classes of algorithms. These algorithms often differ from those used in (applied) data sciences, and their proper application and further development require domain-specific biological knowledge.
- Degree: This Master's programme is officially registered under its name in the Central Register of Higher Education Study Programmes
- Title: MSc
- Master's degree in: Biosciences
- Programme: Bioinformatics and Biocomplexity
- Accredited by the NVAO
- Croho code:
- Language of instruction:
- Part- or full-time status:
- 2 years
- Credits: 60 credits equals one year full-time study load (European Credit Transfer System, ECTS)
- Start of studies:
- Application deadline:
- September: Dutch & EU/EER students: 1 June
- September: Non-EU/EEA students: 1 April
- Graduate school:
- Life Sciences