Computational Cell Maps

Our research is inspired and driven by medical and biological questions that we answer by using multiple large-scale omics data. We are involved in several consortia and research projects. We systematically integrate molecular data with classical bioinformatic or statistical tools.

We also engage in a startup, which develops software that will allow users to store and automatically link their data in order to analyze the user data in a holistic manner. Find out more on our startup knowing.

We are always seeking motivated students, PhD candidates or Postdocs from the fields of systems biology, bioinformatics, computational biology or related fields.

Cell maps

The main focus of our group research is the integration of biological data, typically derived from two or more omics technologies. In tight collaborations with medical or biological partners, we apply and develop innovative tools to answer biological questions by systematically integrating data from large-scale omics. 

  • The model-based functional enrichment method for one, two or more omics level takes care of redundancies of gene ontology trees and thereby generates easy to understand and analyze so-called "enrichment analysis". Original publication of the method MONA and the respective web tool RAMONA
  • The pre-seed startup knowing integrates public data to a holistic data source of cellular molecules to a so called cell map. With this cell map, we are currently developing software to link experimental data. 

MicroRNA regulation

We are interested in the regulation the short microRNA molecules and their regulatory role on joint targets, pathways and diseases. In the advent of next generation sequences technologies, CLIP and friends pushed the miRNA field further, yet posing new bioinformatic challenges. Tools and web services were developed to assist experimental scientists in their bioinformatic  analysis of miRNAs.

  • Integrative analysis of miRNA and mRNA expression data with miRlastic. A regression based approach was developed to allow integrating matched miRNA and mRNA expression measurements. In addition a scoring of the resulting miRNA-mRNA target network is used for identification of locally enriched functional annotations. 
  • Tissue-specific pathway enrichment with Mitalos V2. Search the effect of one or a set of human miRNAs by adding tissue expression filters on target genes. MiRNAs act in a tissue-specific manner, such that a tissue filter is important for analyzing the function of miRNAs.
  • Cooperativity of miRNAs with Micro. MiRNA modulate target gene expression in a joint fashion. When two miRNAs bind in a confined distance, they may act in a cooperative fashion.
  • MiRNA and RNA-binding protien interactions with Simira.