About Us

The Division of Computational Systems Biology (CUBE) at the Centre for Microbiology and Environmental Systems Science (CeMESS) is a group of bioinformaticians and computational biologists. CUBE focuses on understanding biological systems, ranging from single species to multi-species systems and ecosystems.

Our research is based on data from large-scale bioanalytical methods. Researchers in our group develop, improve and apply computational methods for the interpretation of molecular information in biology. We establish and analyse quantitative mathematical models.

We develop and provide access to various software and databases, including: PhenDB, VOGDB, NVT,   HoloVir, SIMAP, EffectiveDB, PICA, Gepard, and GenSkew.

We operate and administer Life Science Compute Cluster (LiSC), a specialized high-performance computing infrastructure which is available to life scientists across the University of Vienna.



CeMESS proudly announces that five of its researchers are on the 2023 Clarivate list of the world's most highly cited researchers. This prestigious...


Lukas Lüftinger defended his PhD thesis "Antibiotic Resistance Prediction from Sequencing Data by Machine Learning" with very good grades. During his...


The recently established FWF Cluster of Excellence "Microbiomes Drive Planetary Health" unites microbiome research in Austria, bringing together 8...


We are seeking to appoint a Tenure-Track Professor in the field of Complex Systems Science in Microbiome Research. Thus successful candidate will...


Scientific claims that babies already harbour living bacteria in the womb are incorrect - this has been proven by international researchers involving...


A novel infrastructure for life science data: The project “DataLife - Data Infrastructure for Life Sciences”, coordinated by CUBE head Thomas Rattei,...

 Latest Publications

Blanco-Míguez, A., Beghini, F., Cumbo, F., McIver, L. J., Thompson, K. N., Zolfo, M., Manghi, P., Dubois, L., Huang, K. D., Thomas, A. M., Nickols, W. A., Piccinno, G., Piperni, E., Punčochář, M., Valles-Colomer, M., Tett, A., Giordano, F., Davies, R., Wolf, J., ... Segata, N. (2023). Extending and improving metagenomic taxonomic profiling with uncharacterized species using MetaPhlAn 4. Nature Biotechnology, 41(11), 1633-1644. https://doi.org/10.1038/s41587-023-01688-w

Esser, S. P., Rahlff, J., Zhao, W., Predl, M., Plewka, J., Sures, K., Wimmer, F., Lee, J., Adam, P. S., McGonigle, J., Turzynski, V., Banas, I., Schwank, K., Krupovic, M., Bornemann, T. L. V., Figueroa-Gonzalez, P. A., Jarett, J., Rattei, T., Amano, Y., ... Probst, A. J. (2023). A predicted CRISPR-mediated symbiosis between uncultivated archaea. Nature Microbiology, 8(9), 1619-1633. https://doi.org/10.1038/s41564-023-01439-2