Our group participates in the Freiburg Initiative for Systems Biology (FRISYS).
The programmatic focus of FRISYS is modelling and system analysis of
signalling networks in growth and differentiation of well developed model
organisms at phylogenetic key positions. The understanding of the regulatory
principles of these networks requires mathematical models which must be tightly
linked to experimental data. Within FRISYS the Systems Biology approach will be
applied to networks relevant for signalling in growth and differentiation.
Initially, the mathematical models will be based on existing qualitative
knowledge about the biological processes. Based on these models, experiments
will be designed that will quantitatively measure the dynamic behaviour of the
biological system.
In particular we are involved in the FRISYS subprojects
As part of WP2 we deal with regulatory RNAs, their interactions, targets and resulting regulatory networks. Important features of many regulatory networks are feedback loops. Some are known to involve regulatory RNAs. We analyze and model an example of an RNA-based reversible switch in detail to develop it into a general paradigm for RNA-RNA based regulation. Furthermore, we develop and extend various algorithms for predicting RNA targeting.
Within WP3 we model and predict cis-regulatory elements by transcription factor binding site prediction and elucidate evolutionary conserved transcriptional regulatory networks that control stem cell identity, differentiation and survival in the vertebrate model organism Danio rerio. We will apply new models and search algorithms to detect binding sites of factors involved in these processes. Here we are in particular interested in the role of the homeodomain transcription factor Pou5f1 which is highly conserved among vertebrates at the levels of sequence, expression pattern, and function. Pou5f1 interacts with other transcription factors and is involved in early embryonic transcription circuits like tissue specification and maintenance of the pluripotent state of earlier embryonic blastomers. The identification of new target genes that are under the control of Pou5f1 will help to improve the existing Pou5f1 dependent gene regulatory network and allow not only qualitative, but also quantitative modeling of the network.