What do we do?
At the Bioinformatics / Systems Biology Group we study the dynamics of entire biological systems, both at evolutionary time scales and at shorter time scales down to a few minutes. We often work in close collaborations with laboratory scientists, focusing on the computational aspects of studying such systems, in fields ranging from genetics to genomics to proteomics. In addition, we produce and maintain several online resources for the life science community, including STRING-db (protein networks), EGGNOG-db (gene orthology relations), and PAX-db (protein abundances).
In 2016, our group completely re-designed the web interface to our protein-protein interaction database, STRING. This removed several bottlenecks in usability and throughput, and provided much better value to expert and non-expert users alike. We also took the occasion to replace several outdated web-technologies, such as Adobe Flash. This and other improvements have been very well received by the users, with more than 3,000 distinct users now working with the database on a daily basis. In other news: we developed a high-throughput pipeline for recognizing microbial "species" from high-throughput sequencing data. We applied this pipeline to a truly global dataset, describing the quantitative occurrence patterns of many microbial species for the first time. We then used this dataset to derive novel measures for community similarity and for clustering quality.
Main publications 2016
- Schmidt TS, Matias Rodrigues JF, von Mering C. A family of interaction-adjusted indices of community similarity. ISME Journal, doi:10.1038/ismej.
- Szklarczyk D et al. The STRING database in 2017STRING v10: protein-protein interaction networks, integrated over the tree of life. Nucleic Acids Res 2017;45:D362-D368.
- Huerta-Cepas J et al. eggNOG 4.5: a hierarchical orthology framework with improved functional annotations for eukaryotic, prokaryotic and viral sequences. Nucleic Acids Res 2016;44:D286-D293.