The Bioinformatics Group at MOMA


Circosplot

Graphic: Jakob Skou & Philippe Lamy

About Bioinformatics

Next-generation sequencing produces unprecedented amounts of DNA-based data. 
A single experiment routinely generates millions or even billions of data points. These data can potentially reveal the molecular changes underlying cancer and other diseases.
However, the size of the data sets makes it impossible to analyze them by hand. Bioinformatics deals with the development and application of computational methods for analyzing such large biological or clinical data sets.

Research Aims

We aim to contribute to the characterization and understanding of the molecular changes that occur during cancer development and progression.

Much of our research focuses on data sets generated at our local next-generation sequencing facility, which are analyzed in tight collaboration with the experimental groups at MOMA.

Finding the causative genetic and epigenetic changes in cancer requires integration and statistical analysis of multiple layers of information, including databases representing current knowledge. As the needed tools for this analysis are often lacking, the development of novel computational and statistical methods is a central aspect of our work.

The group has a strong focus on understanding the regulatory roles played by non-coding RNAs and other non-protein-coding regions of the genome, as well as on understanding the molecular changes in cancer.

Current Research Activities

  • Bioinformatic support for next-generation core facility customers and collaborators.
  • Characterization of molecular changes in bladder cancer progression.
  • Development of methods for integrating multiple layers of genomic data for molecular marker identification in prostate cancer (See molpros.dk).
  • Integration of probing data in RNA secondary structure prediction methods (See COAT).
  • Identification and analysis of alternative poly-adenylation sites in cancer.
  • Comparative identification of human RNA editing sites.
  • Long non-coding RNA (lncRNA) expression analysis in healthy tissues and cancer samples.
  • Identification of regulatory networks of long non-coding RNAs in health and disease (Sapere Aude grant).

Mirror of the UCSC Genome Browser

The bioinformatics group at MOMA maintains a public European mirror of the UCSC Genome Browser, which contains additional customized tracks.

 

Contacts

Jakob Skou Pedersen, group leader, professor, PhD, MSc


Søren Vang, Data Manager, PhD, MSc, vang@clin.au.dk
Philippe Lamy, associate professor, PhD, MSc, philippe.lamy@svf.au.dk
Morten Muhlig Nielsen, post doc, MSc, morten.muhlig@clin.au.dk
Michal Switnicki, PhD student, MSc, michal.switnicki@clin.au.dk
Henrik Hornshøj Jensen, assoc. prof., PhD, MSc, hhj@clin.au.dk
Tobias Madsen, PhD student, tobias.madsen@clin.au.dk
Malene Juul Rasmussenmalene.juul.rasmussen@clin.au.dk