The increasing use of quantitative high-throughput methods has led to a growing need for automated analysis of large volumes of data.
Biomedical sciences have been revolutionized by high-throughput genomics, transcriptomics, proteomics, and imaging methods. These provide parallel and detailed measurements of a vast number of molecular entities, but also demand highly performant and sophisticated data analysis methods. Extensive experimental data sets can further support the development of mathematical models, which can be used to gain further insights into how biological systems behave.
The Computational & Systems Biology research groups develop mathematical and computational approaches to study a wide range of biological systems, from individual proteins to individual bacterial cells and cell populations to animal organs. A recurrent question in these projects is how cells learn to respond and adapt to their environment, which may involve mutations in their genomes, emergence of specific circuits to regulate gene expression and other mechanisms. Many projects are carried out in the highly interdisciplinary research groups of the focal area, but many are also undertaken in collaboration with other research groups at the Biozentrum or with international consortia.
Group leaders of the Computational & Systems Biology focal area are also research group leaders at the Swiss Institute of Bioinformatics (SIB). Furthermore, they contribute to sciCORE, the competitive scientific computing environment of the University.