University of Luxembourg / Luxembourg Centre for Systems Biomedicine, Luxembourg

lcsbDescription of organization

The University of Luxembourg, founded in 2003, is one of the youngest universities in Europe. It is a research-focused multilingual university with about 5.000 students from many different countries. Systems biomedicine has been identified as a high priority research area. For this purpose the government of Luxembourg has launched a major program in personalized medicine, which includes the establishment of a Luxembourg Biobank and a new Centre for Systems Biomedicine (LCSB). Rudi Balling has been recruited as the founding director of this new Centre in 2009. The mission of the LCSB will be the analysis of disease mechanisms using a wide range of bioinformatic, computational and systems biology methods. High throughput genomics-, proteomics- and metabolomics-technology is used as a basis for the mathematical descriptions of disease networks and the modeling and simulation of disease pathogenesis. A major focus of the LCSB will be on the analysis of neurological diseases, particularly Parkinson's disease.


Previous experience

Rudi Balling is the coordinator of EATRIS, the European Initiative for Advanced Translational Infrastructure. He was also the coordinator of the Bill and Melinda Gates Grand Challenge Projects in Global Public Health (GC4) and one of the coordinators of the German Human Genome Project.


Profile of staff members

Antonio del Sol is Professor of Bioinformatics at the University of Luxembourg since 4/2010. He is a theoretical physicist with more than 10 years experience in computational biology. Nikos Vlassis is a senior researcher with intensive experience in Artificial Intelligence and Robotics. Karsten Hiller is head of a young investigator group in metabolomics. Kirsten Roomp, Serge Eifes and Wiktor Jurkowski are bioinformaticians with many years of experience in large scale data analysis. The LCSB will study key network components involved in the process of neurodegeneration, the interaction between these components and their dynamic behavior after specific chemical or genetic perturbations. A range of bioinformatics and computational biology tools will be used to develop mathematical models of disease pathogenesis and progression. The goal is to obtain sufficient insight into aspects such as robustness, fragility, emergence and modularity of the underlying networks, which then allows a better prediction of how chronic neurodegenerative diseases can be prevented or treated.



Luxembourg Centre for Systems Biomedicine



Five recent publications relevant to the project

1. del Sol, A., R. Balling, et al. (2010). "Diseases as network perturbations." Curr Opin Biotechnol 21(4): 566-71.


2. Hrabe de Angelis, M. H., H. Flaswinkel, et al. (2000). "Genome-wide, large-scale production of mutant mice by ENU mutagenesis." Nat Genet 25(4): 444-7.


3. He, F., R. Balling, et al. (2009). "Reverse engineering and verification of gene networks: principles, assumptions, and limitations of present methods and future perspectives." J Biotechnol 144(3): 190-203.


4. Legrand, N., A. Ploss, et al. (2009). "Humanized mice for modeling human infectious disease: challenges, progress, and outlook." Cell Host Microbe 6(1): 5-9.Cell Host Microbe 6(1): 5-9.


5. He, F., Buer, J., Zengh, A.P. & Balling, R. Dynamic cumulative activity of transcription factors as a mechanism ofquantitative gene regulation. Genome Biol. 2007, 8, R 181