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Bioinformatics & Systems Biology


Today, massively parallel DNA sequencing or hybridization approaches allow the identification of not only the gene repertoire but also the gene regulatory networks of an organism. The huge amounts of data acquired from such experiments can only be handled with intensive bioinformatics support that has to provide an adequate infrastructure for storing and analyzing these data. Thus, bioinformatics has to deliver efficient data analysis algorithms, user-friendly tools and software applications, as well as extensive hardware infrastructure for answering such questions.

As part of the Bielefeld-Giessen Resource Center for Microbial Bioinformatics (BiGi), a service unit of the 'German Network for Bioinformatics Infrastructure – de.NBI', the group is focused on data management for genome and post-genome research projects that require new software solutions for systematic data acquisition, secure data storage of structured information, and high-throughput data analysis. Bioinformatics training and education and the cooperation within the German bioinformatics community is a main scope of the group.

Recent publications
The introduction of next generation sequencing has caused a steady increase in the amounts of data that have to be processed in modern life science. Sequence alignment plays a key role in the analysis of sequencing data e.g. within whole genome sequencing or metagenome projects. BLAST is a commonly used alignment tool that was the standard approach for more than two decades, but in the last years faster alternatives have been proposed including RapSearch, GHOSTX, and DIAMOND.
The rapidly increasing availability of microbial genome sequences has led to a growing demand for bioinformatics software tools that support the functional analysis based on the comparison of closely related genomes. By utilizing comparative approaches on gene level it is possible to gain insights into the core genes which represent the set of shared features for a set of organisms under study.
DistAMo is a versatile web-based tool for analyzing motif distributions in bacteria, archaea and viruses. It allows for an analysis of motif over/underrepresentation from the level of single genes to the level of whole replicons.
The huge amounts of data acquired from PolyOmics technologies can only be handled with intensive bioinformatics support that has to provide an adequate data management, efficient data analysis algorithms, and user-friendly software applications. Over the last years, we developed a large scale software suite to substantially support researchers in the field of genome and metagenome, transcriptome, proteome, and metabolome data analysis. As all software applications follow a similar design pattern, experimental data as well as analysis results can be easily integrated to achieve higher-level evaluation and combined visualizations.
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