Learning outcomes


Graduates in Computational biomedicine are able to understand and reflect on knowledge regarding the integration and application of computational methods in the life sciences, including molecular cell biology, structural biology, genomics, proteomics, metabolomics and bioinformatics, based on a scientific approach.


Graduates in Computational biomedicine master specific scientific tools and methods within computational biology/biomedicine, bioinformatics, molecular life sciences and translational medicine:

  • Programming of computer tools and scripts
  • Tools and databases used in genomics
  • DNA-sequencing
  • mRNA expression analysis by sequencing and micro arrays
  • Qualitative and quantitative proteomics using mass spectrometry and electrophoretic techniques
  • Metabolite analyses by chromatography, NMR and mass spectrometric detection
  • Quantification in connection with gene expression
  • Interaction analyses
  • Structural biology, including protein structure and simulation

Graduates master the following general skills related to future employment in research in Computational biomedicine:

  • Acquisition of knowledge within a defined area of topics
  • General experimental design in the context of statistical and computational data analysis
  • Detailed planning of experiments for subsequent interpretation by computational approaches
  • Interpretation of experimental data using computational methods
  • Documentation of computational techniques and programs

In addition, graduates are able to:

  • choose among scientific theories, methods, tools and general properties within computational biomedicine and bioinformatics and apply these to the investigation of scientific questions.
  • establish testable hypotheses or improve on existing ones, on the basis of experiments and/or computational models and simulations and newly obtained knowledge.
  • design experiments and/or computational/statistics methods to verify or falsify a given hypothesis. 
  • discuss and organize new experimental data and computational/statistical results in a context of pre-existing knowledge.
  • disseminate research based knowledge and discuss professional and scientific problems with both peers and non-specialists.


Graduates in Computational biomedicine are qualified to:

  • control and develop complex processes within different computational and statistical approaches and propose approaches if unexpected situations occur.
  • independently initiate and implement disciplinary and interdisciplinary cooperation and collaborations and to assume professional responsibility based on own expertise.
  • independently take responsibility for their own professional development and specialization.

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