Help Guide Disclaimer Contact us Login
  Advanced SearchBrowse




Journal Article

Petri net modelling of gene regulation of the Duchenne muscular dystrophy


Koch,  Ina
Max Planck Society;

There are no locators available
Fulltext (public)
There are no public fulltexts available
Supplementary Material (public)
There is no public supplementary material available

Grunwald, S., Speer, A., Ackermann, J., & Koch, I. (2008). Petri net modelling of gene regulation of the Duchenne muscular dystrophy. Biosystems, 92(2), 189-205. doi:10.1016/j.biosystems.2008.02.005.

Cite as:
Searching for therapeutic strategies for Duchenne muscular dystrophy, it is of great interest to understand the responsible molecular pathways down-stream of dystrophin completely. For this reason we have performed real-time PCR experiments to compare mRNA expression levels of relevant genes in tissues of affected patients and controls. To bring experimental data in context with the underlying pathway theoretical models are needed. Modelling of biological processes in the cell at higher description levels is still an open problem in the field of systems biology. In this paper, a new application of Petri net theory is presented to model gene regulatory processes of Duchenne muscular dystrophy. We have developed a Petri net model, which is based mainly on own experimental and literature data. We distinguish between up- and down-regulated states of gene expression. The analysis of the model comprises the computation of structural and dynamic properties with focus on a thorough T-invariant analysis, including clustering techniques and the decomposition of the network into maximal common transition sets (MCT-sets), which can be interpreted as functionally related building blocks. All possible pathways, which reflect the complex net behaviour in dependence of different gene expression patterns, are discussed. We introduce Mauritius maps of T-invariants, which enable, for example, theoretical knockout analysis. The resulted model serves as basis for a better understanding of pathological processes, and thereby for planning next experimental steps in searching for new therapeutic possibilities.