Generally, we perform bioinformatic data analyses and data integration to get a systemic view of natural organisms in their environment. Therefor we process and combine data that were obtained from high-throughput methods like "second- or third-generation sequencing" or mass spectrometry.
Right now we are focussing on analyses of RNA-seq data to detect and quantify RNA species and interactions of RNA with proteins. While some of our projects focus on clarification of ribosomal regulatory mechanisms of pathogenic bacteria, we support genomic analyses of various research groups that are specialized on other species or domains of life.
Among other things, we deal with the construction and the development of customized bioinformatics analysis pipelines of high-throughput sequencing experiments, for example in the context of different projects of e.g. microbial or neurogenetic origin and initiatives of the Comprehensive Cancer Center (CCC) Mainfranken.
The current spectrum of methods includes variant calling and comparison of tumor and normal tissue in panel, exome and genome sequencing, bisulfite sequencing (DNA methylation analysis), transcriptome sequencing (mRNA lnRNA, miRNAs) as well as single-cell RNA sequencing. Further applications in the field of proteomics and metabolomics can initially be implemented as pilot projects.
Another part of our work is the development of new methods and applications in systems biology issues, disease-oriented research (eg, metabolic and immunological diseases) and translational research (development and preclinical monitoring of pharmacological treatments) and development of preventive measures (eg nutritional interventions).
In addition, we closely collaborate with experimentally oriented partners to develop (open source) bioinformatic tools and are supporting the design of high-throughput experiments, data visualization and the teaching of computer science-based methods in biology.