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

10.09.2024
 

Lovro Trgovec-Greif successfully defended his PhD thesis "Virus bioinformatics and phage-bacteria interactions".

07.09.2024
 

Roko Sango defended his PhD thesis "Computational metabolic modelling and multi-omics analysis of bone-marrow derived and tissue-resident macrophages"...

02.08.2024
 

Michael Predl defended his PhD thesis "Prediction of cross-feeding interactions in microbial communities using metabolic modelling" with very good...

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...

 Latest Publications

Oberreiter, V., Gelabert, P., Brück, F., Franz, S., Zelger, E., Szedlacsek, S., Cheronet, O., Cano, F. T., Exler, F., Zagorc, B., Karavanić, I., Banda, M., Gasparyan, B., Straus, L. G., Gonzalez Morales, M. R., Kappelman, J., Stahlschmidt, M., Rattei, T., Kraemer, S. M., ... Pinhasi, R. (2024). Maximizing efficiency in sedimentary ancient DNA analysis: a novel extract pooling approach. Scientific Reports, 14(1), 19388. Article 19388. https://doi.org/10.1038/s41598-024-69741-5

Sudo, M., Osvatic, J., Taylor, J. D., Dufour, S. C., Prathep, A., Wilkins, L. G. E., Rattei, T., Yuen, B., & Petersen, J. M. (2024). SoxY gene family expansion underpins adaptation to diverse hosts and environments in symbiotic sulfide oxidizers. mSystems, 9(6), Article e01135-23. https://doi.org/10.1128/msystems.01135-23

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