Our Research Projects
The Computational Biology group adresses biological problems using computational methods. We pursue several lines of research:
1. we are interested in large-scale data integration, focusing on mitochondrial function in development and disease
2. we are developing methods to work with remote sequence similarities; currently, we are focusing on de novo prediction of short, functional motifs in proteins
3. we are involved in several genome sequencing and annotation projects
1. Integration of -omics data
We work on the integration of -omics data from different sources to extract meaningful biological information. We use mostly NGS-data, integrating differential expression with ChIP-seq or interactome data to provide biologists with testable hypothesis for further experimental studies. To this end, we develop data integration methods that are easy to use for non-experts.
1.1 mitoXplorer - exploring the dynamics of mitochondrial gene expression by visual data mining
We have developed the mitoXplorer platform, a visual data mining web-server that allows us to mine the expression dynamics of mitochondria-associated genes in the vast amount of available -omics data. A manually curated, mitochondrial interactome is at the heart of this web-tool ... more
This project was supported by DFG grant ‘CancerSysDB’ and is currently supported by ANR grant ‘MITO-DYNAMICS’, the Max Planck Society and the CNRS.
1.2 Biological networks for data analysis, integration and visualization
Biological networks such as protein-protein interaction networks or gene regulatory networks are an integral part to understand biological systems. We use such networks to interpret and integrate -omics data. We have developed several algorithms for network analysis and visualization ... more
These projects were supported by BMBF grants ‘HEPATOSYS’ and 'SYBACOL' and the Max Planck Society .
2. Working with remote sequence similarity
Our Darwinian view on evolution states that evolution is the result of random changes of our genetic code combined with the process of natural selection. Many small changes over a long period of time have a major evolutionary impact. As a result, even true orthologs can share only low sequence similarity, which we refer to as conservation in the twilight or midnight zone.
Our group is interested in detecting sequence relationships in the twilight and midnight zone.
2.1 HH-MOTiF: de novo detection of short linear motifs in proteins using HMM-comparisons
Protein motifs are defined as self-sufficient functional units. They are typically only between 3 and 23 amino acids long and have various functions in proteins. We have developed an easy-to-use, efficient de novo search engine for short linear motifs in a set of proteins. Our method is based on the comparison of Hidden-Markov-Models (HMM) and uses a hierarchical model, so-called motif trees, to identify conserved motifs ... more
This project is supported by the Max Planck Society and the CNRS.
2.2 morFeus: finding remotely conserved orthologs using iterative, relaxed BLAST-searches and network scoring
We are interested in discovering remote orthologs. We have developed the web-based method morFeus for the detection of orthologs in the twilight and midnight zone of sequence similarity ... more
This project was supported by BMBF grant NGS goes HPC and the Max Planck Society.