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.

 News

22.05.2024
 

This Friday from 17:00 the University of Vienna Biology Building foyer will become an open space for the general public to experience interactive...

16.05.2024
 

We are searching for a highly motivated person (m/f/d) with professional experience in the coordination of research infrastructures for the position...

16.05.2024
 

CUBE, the Center for Medical Research (ZMF) of the Medical University of Graz and the Austrian Bioinformatics Platform welcome you to Graz to...

29.04.2024
 

We're happy to announce that CUBies are strenghtening in numbers!

 

Lukas Weilguny has recently finished his PhD at EMBL-EBI working on...

29.04.2024
 

We're happy to announce that CUBies are strenghtening in numbers!

 

Nicholas Pullen (Nick) is joining as a post-doc contributing to the DataLife...

16.11.2023
 

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

 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