Torbjørn Rognes' group

Bioinformatics Group


The bioinformatics group is a research groups at Rikshospitalet, Oslo University Hospital and the University of Oslo (UiO), Norway.

The group belongs to the Department of Microbiology at Rikshospitalet and UiO. The group is also a part of the Biomedical Informatics research group (BMI) at the Department of Informatics, UiO.

New sequencing technologies allow extensive sequencing to be carried out to analyse sequence variation, transcription, epigenetics and other phenomena. Complete genome sequences from thousands of organisms as well as data from large-scale protein structure determination projects are also publicly available. Microbiotic diversity and composition can be analysed in detail by sequencing patient or environmental samples. The main challenge in computational biology is to integrate and make sense of all of this data.

The Bioinformatics group uses computational methods to analyse genome sequences, amino acid sequences, molecular structures and gene expression data, both to identify new genes of interest and to understand their structure, function and role in the cell. Advanced computational tools are both used and developed. The group is also creating databases and web sites with our tools and generated data. We are involved in many collaborative projects with different research groups both within and outside OUS.

Current projects

  • Analysis of high-throughput sequencing data, in particular mutation detection analysis and analysis of metagenomics / microbiome data
  • Development of parallel and effective algorithms and open source tools for sequence alignment, searching, indexing and clustering
  • Structural bioinformatics and DNA repair

We have made several bioinformatics tools, including ParAlign, RNAmmer, SWIPE, Swarm and VSEARCH.

Publika - the scientific publication database for Oslo University Hospital has been developed in the group.


We also work in structural bioinformatics, for instance by modelling the structure of proteins and predicting the effect of mutations. An example of this is the work by Jon K. Lærdahl et al. on the PCSK9 protein shown above (see publication for details).